Seafloor character was derived from interpretations of aerial photograph-derived kelp-distribution data available for Santa Cruz Island in the Santa Barbara Channel, California (Kushner and others 2013). The number of substrate classes was reduced because rugosity could not be derived for all areas.

This Data Release contains GIS data generated by USGS for use in a BOEM funded project to compare natural rockfish nursery habitat to habitat created by manmade structures in the eastern Santa Barbara Channel. The contours were created from published Data Elevation Models of Carignan and others (2009) and Dartnell and others (2012). Contours were generated using the ESRI Contour tool in spatial analyst. The contour interval is 10 meters. The contours were clipped to exclude areas outside the BOEM rockfish nurseries study area.

Seafloor character was derived from interpretations of lidar data available for the mainland coast within the study area from the California State Waters Mapping Program (Johnson and others, 2012; Johnson and others, 2013a; Johnson and others, 2013b; Johnson and others, 2013c). The number of substrate classes was reduced because rugosity could not be derived for all areas. References Cited: Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Greene, H.G., Krigsman, L.M., Kvitek, R.G., Dieter, B.E., Endris, C.A., Seitz, G.G., Sliter, R.W., Erdey, M.E., Gutierrez, C.I., Wong, F.L., Yoklavich, M.M., Draut, A.E., Hart, P.E., and Conrad, J.E. (S.Y. Johnson and S.A. Cochran, eds.), 2013a, California State Waters Map Series—Offshore of Santa Barbara, California: U.S. Geological Survey Scientific Investigations Map 3281, 45 p., 11 sheets, scale 1:24,000, https://doi.org/10.3133/sim3281. Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Kvitek, R.G., Greene, H.G., Endris, C.A., Seitz, G.G., Sliter, R.W., Erdey, M.D., Wong, F.L., Gutierrez, C.I., Krigsman, L.M., Draut, A.E., and Hart, P.E. (S.Y. Johnson and S.A. Cochran, eds.), 2013b, California State Waters Map Series—Offshore of Carpinteria, California: U.S. Geological Survey Scientific Investigations Map 3261, 42 p., 10 sheets, scale 1:24,000, https://pubs.usgs.gov/sim/3261/. Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Kvitek, R.G., Greene, H.G., Krigsman, L.M., Endris, C.A., Clahan, K.B., Sliter, R.W., Wong, F.L., Yoklavich, M.M., and Normark, W.R. (S.Y. Johnson, ed.), 2012, California State Waters Map Series—Hueneme Canyon and Vicinity, California: U.S. Geological Survey Scientific Investigations Map 3225, 41 p., 12 sheets, scale 1:24,000, https://pubs.usgs.gov/sim/3225/. Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Kvitek, R.G., Greene, H.G., Krigsman, L.M., Endris, C.A., Seitz, G.G., Gutierrez, C.I., Sliter, R.W., Erdey, M.D., Wong, F.L., Yoklavich, M.M., Draut, A.E., and Hart, P.E. (S.Y. Johnson and S.A. Cochran, eds.), 2013c, California State Waters Map Series—Offshore of Ventura, California: U.S. Geological Survey Scientific Investigations Map 3254, pamphlet 42 p., 11 sheets, scale 1:24,000, https://pubs.usgs.gov/sim/3254/.

Substrate was classified using the method of (Cochrane 2008) for this study multibeam sonar. Sea floor character derived from multibeam sonar data is available for the mainland coast within the study area from the California State Waters Mapping Program (Johnson and others, 2012; Johnson and others, 2013a; Johnson and others, 2013b; Johnson and others, 2013c). The number of substrate classes was reduced because rugosity could not be derived for all areas due to the lack of bathymetry data for other data sets used in the study. References Cited: Cochrane, G.R., 2008, Video-supervised classification of sonar data for mapping seafloor habitat, in Reynolds, J.R., and Greene, H.G., eds., Marine habitat mapping technology for Alaska: Fairbanks, University of Alaska, Alaska Sea Grant College Program, p. 185-194, accessed April 5, 2011, at http://doc.nprb.org/web/research/research%20pubs/615_habitat_mapping_workshop/Individual%20Chapters%20High-Res/Ch13%20Cochrane.pdf. Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Greene, H.G., Krigsman, L.M., Kvitek, R.G., Dieter, B.E., Endris, C.A., Seitz, G.G., Sliter, R.W., Erdey, M.E., Gutierrez, C.I., Wong, F.L., Yoklavich, M.M., Draut, A.E., Hart, P.E., and Conrad, J.E. (S.Y. Johnson and S.A. Cochran, eds.), 2013a, California State Waters Map Series—Offshore of Santa Barbara, California: U.S. Geological Survey Scientific Investigations Map 3281, 45 p., 11 sheets, scale 1:24,000, https://doi.org/10.3133/sim3281. Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Kvitek, R.G., Greene, H.G., Endris, C.A., Seitz, G.G., Sliter, R.W., Erdey, M.D., Wong, F.L., Gutierrez, C.I., Krigsman, L.M., Draut, A.E., and Hart, P.E. (S.Y. Johnson and S.A. Cochran, eds.), 2013b, California State Waters Map Series—Offshore of Carpinteria, California: U.S. Geological Survey Scientific Investigations Map 3261, 42 p., 10 sheets, scale 1:24,000, https://pubs.usgs.gov/sim/3261/. Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Kvitek, R.G., Greene, H.G., Krigsman, L.M., Endris, C.A., Clahan, K.B., Sliter, R.W., Wong, F.L., Yoklavich, M.M., and Normark, W.R. (S.Y. Johnson, ed.), 2012, California State Waters Map Series—Hueneme Canyon and Vicinity, California: U.S. Geological Survey Scientific Investigations Map 3225, 41 p., 12 sheets, scale 1:24,000, https://pubs.usgs.gov/sim/3225/. Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Kvitek, R.G., Greene, H.G., Krigsman, L.M., Endris, C.A., Seitz, G.G., Gutierrez, C.I., Sliter, R.W., Erdey, M.D., Wong, F.L., Yoklavich, M.M., Draut, A.E., and Hart, P.E. (S.Y. Johnson and S.A. Cochran, eds.), 2013c, California State Waters Map Series—Offshore of Ventura, California: U.S. Geological Survey Scientific Investigations Map 3254, pamphlet 42 p., 11 sheets, scale 1:24,000, https://pubs.usgs.gov/sim/3254/.

Substrate was classified using the method of (Cochrane and Lafferty, 2002) for this study. Sea floor character derived from towed sidescan sonar data is available for the mainland coast within the study area from USGS online publications (Cochrane and others, 2003; Cochrane and others, 2005). The number of substrate classes was reduced because rugosity could not be derived for all areas due to the lack of bathymetry data for other data sets used in the study. References Cited: Cochrane, G.R., Nasby, N.M., Reid, J.A., Waltenberger, B., Lee, K.M., 2003, Nearshore Benthic Habitat GIS for the Channel Islands National Marine Sanctuary and Southern California State Fisheries Reserves Volume 1: U.S. Geological Survey Open-File Report 03-85, http://pubs.usgs.gov/of/2003/0085/. Cochrane, G.R., and Lafferty, K.D., 2002, Use of acoustic classification of sidescan sonar data for mapping benthic habitat in the Northern Channel Islands, California: Continental Shelf Research, v. 22, p. 683-690. Cochrane, G.R., Conrad, J.E., Reid, J.A., Fangman, S., Golden, N.E., 2005, The Nearshore Benthic Habitat GIS for the Channel Islands National Marine Sanctuary and Southern California State Fisheries Reserves, Volume II; Version 1.0: U.S. Geological Survey Open-File Report 2005-1170, http://pubs.usgs.gov/of/2005/1170/.

This Data Release contains data from the U.S. Geological Survey (USGS) survey of the Oregon outer Continental shelf (OCS) Floating Wind Farm Site in 2014. The backscatter intensity data was collected along with bathymetry data by USGS during the period from August 20 to September 1, 2014, using a Reson 7111 multibeam echosounder. The mapping mission collected bathymetry data from about 163 m to 566 m depths on the Oregon outer continental shelf. The acquisition was funded by the U.S. Bureau of Ocean Energy Management. Within the final imagery, brighter tones indicate higher backscatter intensity, and darker tones indicate lower backscatter intensity. The intensity represents a complex interaction between the acoustic pulse and the seafloor, as well as characteristics within the shallow subsurface, providing a general indication of seafloor texture and composition. Backscatter intensity depends on the acoustic source level; the frequency used to image the seafloor; the grazing angle; the composition and character of the seafloor, including grain size, water content, bulk density, and seafloor roughness; and some biological cover. Harder and rougher bottom types such as rocky outcrops or coarse sediment typically return stronger intensities (high backscatter, lighter tones), whereas softer bottom types such as fine sediment return weaker intensities (low backscatter, darker tones).

This Data Release contains data from the U.S. Geological Survey (USGS) survey of the Oregon outer continental shelf (OCS) Floating Wind Farm Site in 2014. The bathymetry raster was generated from bathymetry data collected by USGS during the period from August 20 to September 1, 2014, using a Reson 7111 multibeam echosounder. The mapping mission collected bathymetry data from about 163 m to 566 m depths on the Oregon outer continental shelf. The acquisition was funded by the U.S. Bureau of Ocean Energy Management.

This data release contains data from the USGS field activity 2014-607-FA, a survey of the Oregon Outer Continental Shelf (OCS) Floating Wind Farm Site in 2014. The bathymetry raster was generated from bathymetry data collected by U.S. Geological Survey (USGS) during the period from August 20 to September 1, 2014 using a Reson 7111 multibeam echosounder. The mapping mission collected bathymetry data from about 163 m to 566 m depths on the Oregon outer continental shelf. The acquisition was funded by the U.S. Bureau of Ocean Energy Management. Contours were generated using the ESRI Contour tool in spatial analyst. The contour interval is 10 meters.

This part of the Oregon Outer Continental Shelf (OCS) Floating Windfarm Suite Data Release presents geological observations from video collected on U.S. Geological Survey (USGS) field activity 2014-607-FA in the Floating Wind Farm survey area. The survey was conducted using 12 hour day operations out of Charleston Harbor near Coos Bay, Oregon. The cruise plan consisted of 23 days on site split between sonar mapping and video ground truth surveying. Activities parsed out to nine days of sonar mapping, three days of video surveying, eight days of no operations due to weather, and three days mobilizing and demobilizing (table 1). Typically the Snavely would transit out to the survey area in an hour at a speed of 20 knots. Marine Mammal observations were made during the multibeam sonar mapping portion of the cruise only. Multibeam sonar operations were conducted on north or south oriented tracklines at a speed of 4 to 5 knots depending on sea state. Observations were also made on the transit out to the floating Windfarm site.

This Data Release contains data from the USGS survey of the Oregon OCS Floating Wind Farm Site in 2014. The shaded-relief raster was generated from bathymetry data collected by USGS during the period from August 20 to September 1, 2014. using a Reson 7111 multibeam echosounder. The mapping mission collected bathymetry data from about 163 m to 566 m depths on the Oregon outer continental shelf. The acquisition was funded by the U.S. Bureau of Ocean Energy Management.

This part of the Oregon OCS Data Release presents marine mammal observations from U.S. Geological Survey (USGS) field activity 2014-607-FA in the Oregon Outer continental Shelf (OCS)Floating Wind Farm survey area. The survey was conducted using 12 hour day operations out of Charleston Harbor near Coos Bay, Oregon. The cruise plan consisted of 23 days on site split between sonar mapping and video ground truth surveying. Activities parsed out to nine days of sonar mapping, three days of video surveying, eight days of no operations due to weather, and three days mobilizing and demobilizing (table 1). Typically the Snavely would transit out to the survey area in an hour at a speed of 20 knots. Marine Mammal observations were made during the multibeam sonar mapping portion of the cruise only. Multibeam sonar operations were conducted on north or south oriented tracklines at a speed of 4 to 5 knots depending on sea state. Observations were also made on the transit out to the Floating Windfarm site.

Access to the U.S. Geological Survey (USGS) Coastal and Marine Geology Program’s (CMGP) vast collection of unique and valuable seafloor and coastal imagery is made available in the CMGP Video and Photograph Portal. The portal provides a single location for data discovery and viewing. The CMGP and our research partners invest immense resources collecting, processing, and archiving seafloor and oblique coastal video and photographs. Until the publication of the CMGP Video and Photograph Portal in 2015, only a small number of these data sets were available to the public through static web interfaces. Prior to development of the data portal, retrieving this imagery most often required internal USGS access with specific hardware and software. Furthermore, it was difficult to manage and challenging to share such a large amount of information. The Coastal and Marine Geology Program (CMGP) Video and Photograph Portal contains imagery spanning from 2003 to the present. Video and photographs originally collected on analog film media have been digitized and processed along with more recently collected digital video and photographs to meet a common standard for all CMGP video/photo imagery. The Portal is based on an interactive map allowing users to zoom into an area of interest and find available USGS imagery. The co-located video and still photographs are displayed simultaneously, just as they were acquired in the field. In the portal, videos are ultimately stored and streamed as embedded YouTube videos, and photographs are stored in Picasa. Presenting the imagery in this way requires multiple processing steps and tools, including video and photo editing, database management, and computer scripting to automate processing, formatting and quality assurance tasks. A robust set of processing tools have been developed to streamline and automate portions of the workflow based on the wide range of data types processed so far. However, sometimes the data received are uniquely organized and formatted, requiring individualized processing. In that case processing tools are updated to accept a wider range of data formats and organizational structures.

Underwater video imagery was collected in March 2014 in the nearshore waters of Faga'alu Bay on the Island of Tutuila, American Samoa, as part of the U.S. Geological Survey Coastal and Marine Geology Program's Pacific Coral Reefs Project. Included here are 40 video files in .mpg format and an Environmental Systems Research Institute (ESRI) shapefile with location (navigation) points every two seconds.

Water depth, turbidity, and current velocity time-series data were collected in Little Holland Tract from 2015 to 2017. Depth (from pressure) and velocity were measured in high-frequency (8 Hz) bursts. Burst means represent tidal stage and currents, and burst data can be used to determine wave height, period, direction, and wave-orbital velocity. The turbidity sensors were calibrated to suspended-sediment concentration measured in water samples collected on site. The calibration and fit parameters for all of the turbidity sensors used in the study are tabulated and provided with the data. Data were sequentially added to this data release as they were collected and post-processed. Typically, each zip folder for a deployment period contains one file from a CTD, two files of data from a bursting pressure sensor and two data files from the velocimeter, which includes data from the optical backscatter sensor.

Water depth, turbidity, and current velocity time-series data were collected in Little Holland Tract in 2016. Depth (from pressure) and velocity were measured in high-frequency (8 Hz) bursts. Burst means represent tidal stage and currents, and burst data can be used to determine wave height, period, and direction, and wave-orbital velocity. The turbidity sensors were calibrated to suspended-sediment concentration measured in water samples collected on site. The calibration and fit parameters for all of the turbidity sensors used in the study are tabulated and provided with the data. Data were sequentially added to this data release as they were collected and post-processed. Typically, each zip folder for a deployment period contains two files of data from a bursting pressure sensor and two data files from the velocimeter, which includes data from the optical backscatter sensor.

Water depth, turbidity, and current velocity time-series data were collected in Little Holland Tract in 2016. Depth (from pressure) and velocity were measured in high-frequency (8 Hz) bursts. Burst means represent tidal stage and currents, and burst data can be used to determine wave height, period, direction, and wave-orbital velocity. The turbidity sensors were calibrated to suspended-sediment concentration measured in water samples collected on site. The calibration and fit parameters for all of the turbidity sensors used in the study are tabulated and provided with the data. Data were sequentially added to this data release as they were collected and post-processed. Typically, each zip folder for a deployment period contains two files of data from a bursting pressure sensor and two data files from the velocimeter, which includes data from the optical backscatter sensor.

Water depth and turbidity time-series data were collected in Little Holland Tract (LHT) from 2015 to 2017. Depth (from pressure) was measured in high-frequency (6 or 8 Hz) bursts. Burst means represent tidal stage, and burst data can be used to determine wave height and period. The turbidity sensors were calibrated to suspended-sediment concentration measured in water samples collected on site. The calibration and fit parameters for all of the turbidity sensors used in the study are tabulated and provided with the data. Data were sequentially added to this data release as they were collected and post-processed. Typically, each zip folder for a deployment period contains one file from an optical backscatter sensor and two files of data from a bursting pressure sensor.

Water depth, turbidity, and current velocity time-series data were collected in Liberty Island from 2015 to 2017. Depth (from pressure) and velocity were measured in high-frequency (8 Hz) bursts. Burst means represent tidal stage and currents, and burst data can be used to determine wave height, period, and direction, and wave-orbital velocity. The turbidity sensors were calibrated to suspended-sediment concentration measured in water samples collected on site. The calibration and fit parameters for all of the turbidity sensors used in the study are tabulated and provided with the data. Data were sequentially added to this data release as they were collected and post-processed. Typically, each zip folder for a deployment period contains two files of data from a bursting pressure sensor and two data files from the velocimeter, which includes data from the optical backscatter sensor.

Water depth and turbidity time-series data were collected in Little Holland Tract (LHT) from 2015 to 2017. Depth (from pressure) was measured in high-frequency (6 or 8 Hz) bursts. Burst means represent tidal stage, and burst data can be used to determine wave height and period. The turbidity sensors were calibrated to suspended-sediment concentration measured in water samples collected on site. The calibration and fit parameters for all of the turbidity sensors used in the study are tabulated and provided with the data. Data were sequentially added to this data release as they were collected and post-processed. Typically, each zip folder for a deployment period contains one file from an optical backscatter sensor and two files of data from a bursting pressure sensor.

Water depth, turbidity, and current velocity time-series data were collected in Liberty Island Conservation Bank (WVA) in 2017. The turbidity sensors were not calibrated to suspended-sediment concentration at this location. Typically, each zip folder for a deployment period contains two data files from a velocimeter and one data file from a CTD, each of which include data from an optical backscatter sensor.

This dataset includes navigation data for chirp seismic-reflection data collected in 2014 by the U.S. Geological Survey (USGS) in San Pablo Bay, northern California.

This dataset includes processed, high-resolution chirp seismic-reflection data collected in 2014 by the U.S. Geological Survey (USGS) in San Pablo Bay, northern California.

This dataset includes raw, high-resolution chirp seismic-reflection data collected in 2014 by the U.S. Geological Survey (USGS) in San Pablo Bay, northern California.

This part of the data release presents digital elevation models (DEMs) derived from bathymetry and topography data of northern Monterey Bay, California collected in October 2014. Bathymetry data were collected using two personal watercraft (PWCs), each equipped with single-beam echosounders and survey-grade global navigation satellite system (GNSS) receivers. Topography data were collected on foot with GNSS receivers mounted on backpacks and with an all-terrain vehicle (ATV) using a GNSS receiver mounted at a measured height above the ground. DEM surfaces were produced from all available elevation data using linear interpolation.

This part of the data release presents bathymetry data from northern Monterey Bay, California collected in October 2014 using two personal watercraft (PWCs). The PWCs were equipped with single-beam echosounders and survey-grade global navigation satellite system (GNSS) receivers.

This part of the data release presents topography data from northern Monterey Bay, California collected in October 2014. Topography data were collected on foot with survey-grade global navigation satellite system (GNSS) receivers mounted on backpacks and with an all-terrain vehicle (ATV) using a GNSS receiver mounted at a measured height above the ground.

This part of the data release presents digital elevation models (DEMs) derived from bathymetry and topography data of northern Monterey Bay, California collected in March 2015. Bathymetry data were collected using two personal watercraft (PWCs), each equipped with single-beam echosounders and survey-grade global navigation satellite system (GNSS) receivers. Topography data were collected on foot with GNSS receivers mounted on backpacks and with an all-terrain vehicle (ATV) using a GNSS receiver mounted at a measured height above the ground. Additional topography data were collected with a terrestrial lidar scanner. DEM surfaces were produced from all available elevation data using linear interpolation.

This part of the data release presents bathymetry data from northern Monterey Bay, California collected in March 2015 using two personal watercraft (PWCs). The PWCs were equipped with single-beam echosounders and survey-grade global navigation satellite system (GNSS) receivers.

This part of the data release presents topography data from northern Monterey Bay, California collected in March 2015 with a terrestrial lidar scanner.

This part of the data release presents topography data from northern Monterey Bay, California collected in March 2015. Topography data were collected on foot with survey-grade global navigation satellite system (GNSS) receivers mounted on backpacks and with an all-terrain vehicle (ATV) using a GNSS receiver mounted at a measured height above the ground.

This part of the data release presents digital elevation models (DEMs) derived from bathymetry and topography data of northern Monterey Bay, California collected in September and October 2015. Bathymetry data were collected using two personal watercraft (PWCs), each equipped with single-beam echosounders and survey-grade global navigation satellite system (GNSS) receivers. Topography data were collected on foot with GNSS receivers mounted on backpacks and with an all-terrain vehicle (ATV) using a GNSS receiver mounted at a measured height above the ground. Additional topography data were collected with a terrestrial lidar scanner. DEM surfaces were produced from all available elevation data using linear interpolation.

This part of the data release presents bathymetry data from northern Monterey Bay, California collected in September and October 2015 using two personal watercraft (PWCs). The PWCs were equipped with single-beam echosounders and survey-grade global navigation satellite system (GNSS) receivers.

This part of the data release presents topography data from northern Monterey Bay, California collected in September 2015 with a terrestrial lidar scanner.

This part of the data release presents topography data from northern Monterey Bay, California collected in September and October 2015. Topography data were collected on foot with survey-grade global navigation satellite system (GNSS) receivers mounted on backpacks and with an all-terrain vehicle (ATV) using a GNSS receiver mounted at a measured height above the ground.

This part of the data release presents digital elevation models (DEMs) derived from bathymetry and topography data of northern Monterey Bay, California collected in March 2016. Bathymetry data were collected using two personal watercraft (PWCs), each equipped with single-beam echosounders and survey-grade global navigation satellite system (GNSS) receivers. Topography data were collected on foot with GNSS receivers mounted on backpacks and with an all-terrain vehicle (ATV) using a GNSS receiver mounted at a measured height above the ground. Additional topography data were collected with a terrestrial lidar scanner. DEM surfaces were produced from all available elevation data using linear interpolation.

This part of the data release presents bathymetry data from northern Monterey Bay, California collected in March 2016 using two personal watercraft (PWCs). The PWCs were equipped with single-beam echosounders and survey-grade global navigation satellite system (GNSS) receivers.

This part of the data release presents topography data from northern Monterey Bay, California collected in March 2016 with a terrestrial lidar scanner.

This part of the data release presents topography data from northern Monterey Bay, California collected in March 2016. Topography data were collected on foot with survey-grade global navigation satellite system (GNSS) receivers mounted on backpacks and with an all-terrain vehicle (ATV) using a GNSS receiver mounted at a measured height above the ground.

This part of the data release presents topography data from northern Monterey Bay, California collected in October 2016 with a terrestrial lidar scanner.

This part of the data release presents digital elevation models (DEMs) derived from bathymetry and topography data of northern Monterey Bay, California collected in September and October 2016. Bathymetry data were collected using a personal watercraft (PWC) and small boat, each equipped with single-beam echosounders and survey-grade global navigation satellite system (GNSS) receivers. Topography data were collected on foot with GNSS receivers mounted on backpacks and with an all-terrain vehicle (ATV) using a GNSS receiver mounted at a measured height above the ground. Additional topography data were collected with a terrestrial lidar scanner. DEM surfaces were produced using linear interpolation.

This part of the data release presents bathymetry data from northern Monterey Bay, California collected in September 2016 using a personal watercraft (PWC) and small boat. The survey vessels were equipped with single-beam echosounders and survey-grade global navigation satellite system (GNSS) receivers.

This part of the data release presents topography data from northern Monterey Bay, California collected in September 2016. Topography data were collected on foot with survey-grade global navigation satellite system (GNSS) receivers mounted on backpacks and with an all-terrain vehicle (ATV) using a GNSS receiver mounted at a measured height above the ground.

This part of the data release presents digital elevation models (DEMs) derived from bathymetry and topography data of northern Monterey Bay, California collected in March 2017. Bathymetry data were collected using two personal watercraft (PWCs), each equipped with single-beam echosounders and survey-grade global navigation satellite system (GNSS) receivers. Topography data were collected on foot with GNSS receivers mounted on backpacks and with an all-terrain vehicle (ATV) using a GNSS receiver mounted at a measured height above the ground. Additional topography data were collected with a terrestrial lidar scanner. DEM surfaces were produced from all available elevation data using linear interpolation.

This part of the data release presents bathymetry data from northern Monterey Bay, California collected in March 2017 using personal watercraft (PWC). The survey vessels were equipped with single-beam echosounders and survey-grade global navigation satellite system (GNSS) receivers.

This part of the data release presents topography data from northern Monterey Bay, California collected in March 2017 with a terrestrial lidar scanner.

This part of the data release presents topography data from northern Monterey Bay, California collected in March 2017. Topography data were collected on foot with survey-grade global navigation satellite system (GNSS) receivers mounted on backpacks and with an all-terrain vehicle (ATV) using a GNSS receiver mounted at a measured height above the ground.

This part of the data release presents digital elevation models (DEMs) derived from bathymetry and topography data of northern Monterey Bay, California collected in September 2017. Bathymetry data were collected using two personal watercraft (PWCs), each equipped with single-beam echosounders and survey-grade global navigation satellite system (GNSS) receivers. Topography data were collected on foot with GNSS receivers mounted on backpacks and with an all-terrain vehicle (ATV) using a GNSS receiver mounted at a measured height above the ground. Additional topography data were collected with a terrestrial lidar scanner. DEM surfaces were produced from all available elevation data using linear interpolation.

This part of the data release presents bathymetry data from northern Monterey Bay, California collected in September 2017 using two personal watercraft (PWCs). The PWCs were equipped with single-beam echosounders and survey-grade global navigation satellite system (GNSS) receivers.

This part of the data release presents topography data from northern Monterey Bay, California collected in September 2017 with a terrestrial lidar scanner.

This part of the data release presents topography data from northern Monterey Bay, California collected in September 2017. Topography data were collected on foot with survey-grade global navigation satellite system (GNSS) receivers mounted on backpacks and with an all-terrain vehicle (ATV) using a GNSS receiver mounted at a measured height above the ground.

In February 2016 the U.S. Geological Survey, Pacific Coastal and Marine Science Center in cooperation with North Carolina State University and the National Park Service collected multibeam bathymetry and acoustic backscatter data in Lake Crescent located in Olympic National Park, Washington. Data were collected using a Reson 7111 multibeam echosounder pole-mounted to the 36-foot USGS R/V Parke Snavely. These metadata describe the multibeam acoustic-backscatter data file that is included in "LakeCrescent_backscatter_3m_UTM10_NAD83.zip" which is accessible from https://doi.org/10.5066/F7B56GW5.

In February 2016 the U.S. Geological Survey, Pacific Coastal and Marine Science Center in cooperation with North Carolina State University and the National Park Service collected multibeam bathymetry and acoustic-backscatter data in Lake Crescent located in Olympic National Park, Washington. Data were collected using a Reson 7111 multibeam echosounder pole-mounted to the 36-foot USGS R/V Parke Snavely. These metadata describe the multibeam bathymetry raster data file that is included in "LakeCrescent_bathy_3m_UTM10_NAD83_NAVD88.zip" which is accessible from https://doi.org/10.5066/F7B56GW5.

Time-series data of water depth, velocity, turbidity, and temperature were acquired between 5 October 2015 and 21 March 2017 within the Monterey Canyon off of Monterey, CA, USA. In order to better understand the triggering, progression and evolution of turbidity currents in Monterey Submarine Canyon, an experiment was designed to directly measure velocity, suspended sediment and physical water properties (temperature, salinity and density) along the canyon axis during an 18-month period. Three moorings in the upper canyon (MS1, MS2, MS3) containing oceanographic instruments and Anderson- type sediment traps were deployed during three consecutive six-month periods (A: October 2015 - April 2016; B: April - October 2016; C: October 2016 - March 2017). In addition, a bottom platform to the South of the canyon head (MS0) housed instrumentation to measure currents and waves on the adjacent shelf. The mooring diagram image files are a generalized representation of the deployed instrumentation at each site, and are included as a visual aid for understanding the sampling environment. A text file of the specific sensors listing parameters measured is also included.

This part of the data release includes raw computed tomography (CT) images of sediment cores collected in 2009 offshore of Palos Verdes, California. It is one of seven files included in this U.S. Geological Survey data release that include data from a set of sediment cores acquired from the continental slope, offshore Los Angeles and the Palos Verdes Peninsula, adjacent to the Palos Verdes Fault. Gravity cores were collected by the USGS in 2009 (cruise ID S-I2-09-SC; http://cmgds.marine.usgs.gov/fan_info.php?fan=SI209SC), and vibracores were collected with the Monterey Bay Aquarium Research Institute's remotely operated vehicle (ROV) Doc Ricketts in 2010 (cruise ID W-1-10-SC; http://cmgds.marine.usgs.gov/fan_info.php?fan=W110SC). One spreadsheet (PalosVerdesCores_Info.xlsx) contains core name, location, and length. One spreadsheet (PalosVerdesCores_MSCLdata.xlsx) contains Multi-Sensor Core Logger P-wave velocity, gamma-ray density, and magnetic susceptibility whole-core logs. One zipped folder of .bmp files (PalosVerdesCores_Photos.zip) contains continuous core photographs of the archive half of each core. One spreadsheet (PalosVerdesCores_GrainSize.xlsx) contains laser particle grain size sample information and analytical results. One spreadsheet (PalosVerdesCores_Radiocarbon.xlsx) contains radiocarbon sample information, results, and calibrated ages. One zipped folder of DICOM files (PalosVerdesCores_CT.zip) contains raw computed tomography (CT) image files. One .pdf file (PalosVerdesCores_Figures.pdf) contains combined displays of data for each core, including graphic diagram descriptive logs. This particular metadata file describes the information contained in the file PalosVerdesCores_CT.zip. All cores are archived by the U.S. Geological Survey Pacific Coastal and Marine Science Center.

This part of the data release includes graphical representation (figures) of data from sediment cores collected in 2009 offshore of Palos Verdes, California. This file graphically presents combined data for each core (one core per page). Data on each figure are continuous core photograph, CT scan (where available), graphic diagram core description (graphic legend included at right; visual grain size scale of clay, silt, very fine sand [vf], fine sand [f], medium sand [med], coarse sand [c], and very coarse sand [vc]), multi-sensor core logger (MSCL) p-wave velocity (meters per second) and gamma-ray density (grams per cc), radiocarbon age (calibrated years before present) with analytical error (years), and pie charts that present grain-size data as percent sand (white), silt (light gray), and clay (dark gray). This is one of seven files included in this U.S. Geological Survey data release that include data from a set of sediment cores acquired from the continental slope, offshore Los Angeles and the Palos Verdes Peninsula, adjacent to the Palos Verdes Fault. Gravity cores were collected by the USGS in 2009 (cruise ID S-I2-09-SC; http://cmgds.marine.usgs.gov/fan_info.php?fan=SI209SC), and vibracores were collected with the Monterey Bay Aquarium Research Institute's remotely operated vehicle (ROV) Doc Ricketts in 2010 (cruise ID W-1-10-SC; http://cmgds.marine.usgs.gov/fan_info.php?fan=W110SC). One spreadsheet (PalosVerdesCores_Info.xlsx) contains core name, location, and length. One spreadsheet (PalosVerdesCores_MSCLdata.xlsx) contains Multi-Sensor Core Logger P-wave velocity, gamma-ray density, and magnetic susceptibility whole-core logs. One zipped folder of .bmp files (PalosVerdesCores_Photos.zip) contains continuous core photographs of the archive half of each core. One spreadsheet (PalosVerdesCores_GrainSize.xlsx) contains laser particle grain size sample information and analytical results. One spreadsheet (PalosVerdesCores_Radiocarbon.xlsx) contains radiocarbon sample information, results, and calibrated ages. One zipped folder of DICOM files (PalosVerdesCores_CT.zip) contains raw computed tomography (CT) image files. One .pdf file (PalosVerdesCores_Figures.pdf) contains combined displays of data for each core, including graphic diagram descriptive logs. This particular metadata file describes the information contained in the file PalosVerdesCores_Figures.pdf. All cores are archived by the U.S. Geological Survey Pacific Coastal and Marine Science Center.

This part of the data release includes grain-size analysis of sediment cores collected in 2009 offshore of Palos Verdes, California. It is one of seven files included in this U.S. Geological Survey data release that include data from a set of sediment cores acquired from the continental slope, offshore Los Angeles and the Palos Verdes Peninsula, adjacent to the Palos Verdes Fault. Gravity cores were collected by the USGS in 2009 (cruise ID S-I2-09-SC; http://cmgds.marine.usgs.gov/fan_info.php?fan=SI209SC), and vibracores were collected with the Monterey Bay Aquarium Research Institute's remotely operated vehicle (ROV) Doc Ricketts in 2010 (cruise ID W-1-10-SC; http://cmgds.marine.usgs.gov/fan_info.php?fan=W110SC). One spreadsheet (PalosVerdesCores_Info.xlsx) contains core name, location, and length. One spreadsheet (PalosVerdesCores_MSCLdata.xlsx) contains Multi-Sensor Core Logger P-wave velocity, gamma-ray density, and magnetic susceptibility whole-core logs. One zipped folder of .bmp files (PalosVerdesCores_Photos.zip) contains continuous core photographs of the archive half of each core. One spreadsheet (PalosVerdesCores_GrainSize.xlsx) contains laser particle grain size sample information and analytical results. One spreadsheet (PalosVerdesCores_Radiocarbon.xlsx) contains radiocarbon sample information, results, and calibrated ages. One zipped folder of DICOM files (PalosVerdesCores_CT.zip) contains raw computed tomography (CT) image files. One .pdf file (PalosVerdesCores_Figures.pdf) contains combined displays of data for each core, including graphic diagram descriptive logs. This particular metadata file describes the information contained in the file PalosVerdesCores_GrainSize.xlsx. All cores are archived by the U.S. Geological Survey Pacific Coastal and Marine Science Center.

This part of the data release is a spreadsheet including the name, location, and length of sediment cores collected in 2009 offshore from Palos Verdes, California. It is one of seven files included in this U.S. Geological Survey data release that include data from a set of sediment cores acquired from the continental slope, offshore Los Angeles and the Palos Verdes Peninsula, adjacent to the Palos Verdes Fault. Gravity cores were collected by the USGS in 2009 (cruise ID S-I2-09-SC; http://cmgds.marine.usgs.gov/fan_info.php?fan=SI209SC), and vibracores were collected with the Monterey Bay Aquarium Research Institute’s remotely operated vehicle (ROV) Doc Ricketts in 2010 (cruise ID W-1-10-SC; http://cmgds.marine.usgs.gov/fan_info.php?fan=W110SC). One spreadsheet (PalosVerdesCores_Info.xlsx) contains core name, location, and length. One spreadsheet (PalosVerdesCores_MSCLdata.xlsx) contains Multi-Sensor Core Logger P-wave velocity, gamma-ray density, and magnetic susceptibility whole-core logs. One zipped folder of .bmp files (PalosVerdesCores_Photos.zip) contains continuous core photographs of the archive half of each core. One spreadsheet (PalosVerdesCores_GrainSize.xlsx) contains laser particle grain size sample information and analytical results. One spreadsheet (PalosVerdesCores_Radiocarbon.xlsx) contains radiocarbon sample information, results, and calibrated ages. One zipped folder of DICOM files (PalosVerdesCores_CT.zip) contains raw computed tomography (CT) image files. One .pdf file (PalosVerdesCores_Figures.pdf) contains combined displays of data for each core, including graphic diagram descriptive logs. This particular metadata file describes the information contained in the file PalosVerdesCores_Info.xlsx. All cores are archived by the U.S. Geological Survey Pacific Coastal and Marine Science Center.

This part of the data release includes Multi-Sensor Core Logger (MSCL) P-wave velocity, gamma-ray density, and magnetic susceptibility whole-core logs of sediment cores collected in 2009 offshore of Palos Verdes, California. It is one of seven files included in this U.S. Geological Survey data release that include data from a set of sediment cores acquired from the continental slope, offshore Los Angeles and the Palos Verdes Peninsula, adjacent to the Palos Verdes Fault. Gravity cores were collected by the USGS in 2009 (cruise ID S-I2-09-SC; http://cmgds.marine.usgs.gov/fan_info.php?fan=SI209SC), and vibracores were collected with the Monterey Bay Aquarium Research Institute's remotely operated vehicle (ROV) Doc Ricketts in 2010 (cruise ID W-1-10-SC; http://cmgds.marine.usgs.gov/fan_info.php?fan=W110SC). One spreadsheet (PalosVerdesCores_Info.xlsx) contains core name, location, and length. One spreadsheet (PalosVerdesCores_MSCLdata.xlsx) contains Multi-Sensor Core Logger P-wave velocity, gamma-ray density, and magnetic susceptibility whole-core logs. One zipped folder of .bmp files (PalosVerdesCores_Photos.zip) contains continuous core photographs of the archive half of each core. One spreadsheet (PalosVerdesCores_GrainSize.xlsx) contains laser particle grain size sample information and analytical results. One spreadsheet (PalosVerdesCores_Radiocarbon.xlsx) contains radiocarbon sample information, results, and calibrated ages. One zipped folder of DICOM files (PalosVerdesCores_CT.zip) contains raw computed tomography (CT) image files. One .pdf file (PalosVerdesCores_Figures.pdf) contains combined displays of data for each core, including graphic diagram descriptive logs. This particular metadata file describes the information contained in the file PalosVerdesCores_MSCLdata.xlsx. All cores are archived by the U.S. Geological Survey Pacific Coastal and Marine Science Center.

This part of the data release includes continuous core photographs in bmp format of sediment cores collected in 2009 offshore of Palos Verdes, California. It is one of seven files included in this U.S. Geological Survey data release that include data from a set of sediment cores acquired from the continental slope, offshore Los Angeles and the Palos Verdes Peninsula, adjacent to the Palos Verdes Fault. Gravity cores were collected by the USGS in 2009 (cruise ID S-I2-09-SC; http://cmgds.marine.usgs.gov/fan_info.php?fan=SI209SC), and vibracores were collected with the Monterey Bay Aquarium Research Institute's remotely operated vehicle (ROV) Doc Ricketts in 2010 (cruise ID W-1-10-SC; http://cmgds.marine.usgs.gov/fan_info.php?fan=W110SC). One spreadsheet (PalosVerdesCores_Info.xlsx) contains core name, location, and length. One spreadsheet (PalosVerdesCores_MSCLdata.xlsx) contains Multi-Sensor Core Logger P-wave velocity, gamma-ray density, and magnetic susceptibility whole-core logs. One zipped folder of .bmp files (PalosVerdesCores_Photos.zip) contains continuous core photographs of the archive half of each core. One spreadsheet (PalosVerdesCores_GrainSize.xlsx) contains laser particle grain size sample information and analytical results. One spreadsheet (PalosVerdesCores_Radiocarbon.xlsx) contains radiocarbon sample information, results, and calibrated ages. One zipped folder of DICOM files (PalosVerdesCores_CT.zip) contains raw computed tomography (CT) image files. One .pdf file (PalosVerdesCores_Figures.pdf) contains combined displays of data for each core, including graphic diagram descriptive logs. This particular metadata file describes the information contained in the file PalosVerdesCores_Photos.zip. All cores are archived by the U.S. Geological Survey Pacific Coastal and Marine Science Center.

This part of the data release is a spreadsheet including radiocarbon sample information and calibrated ages of sediment cores collected in 2009 offshore of Palos Verdes, California. It is one of seven files included in this U.S. Geological Survey data release that include data from a set of sediment cores acquired from the continental slope, offshore Los Angeles and the Palos Verdes Peninsula, adjacent to the Palos Verdes Fault. Gravity cores were collected by the USGS in 2009 (cruise ID S-I2-09-SC; http://cmgds.marine.usgs.gov/fan_info.php?fan=SI209SC), and vibracores were collected with the Monterey Bay Aquarium Research Institute's remotely operated vehicle (ROV) Doc Ricketts in 2010 (cruise ID W-1-10-SC; http://cmgds.marine.usgs.gov/fan_info.php?fan=W110SC). One spreadsheet (PalosVerdesCores_Info.xlsx) contains core name, location, and length. One spreadsheet (PalosVerdesCores_MSCLdata.xlsx) contains Multi-Sensor Core Logger P-wave velocity, gamma-ray density, and magnetic susceptibility whole-core logs. One zipped folder of .bmp files (PalosVerdesCores_Photos.zip) contains continuous core photographs of the archive half of each core. One spreadsheet (PalosVerdesCores_GrainSize.xlsx) contains laser particle grain size sample information and analytical results. One spreadsheet (PalosVerdesCores_Radiocarbon.xlsx) contains radiocarbon sample information, results, and calibrated ages. One zipped folder of DICOM files (PalosVerdesCores_CT.zip) contains raw computed tomography (CT) image files. One .pdf file (PalosVerdesCores_Figures.pdf) contains combined displays of data for each core, including graphic diagram descriptive logs. This particular metadata file describes the information contained in the file PalosVerdesCores_Radiocarbon.xlsx. All cores are archived by the U.S. Geological Survey Pacific Coastal and Marine Science Center.

These metadata describe the U.S. Geological Survey (USGS), Pacific Coastal and Marine Science Center (PCMSC) 2004 bathymetry data collected in Skagit Bay Washington that is provided as a 1-m resolution TIFF image, as well as a 1-m resolution shaded-relief TIFF image. In 2004, 2005, 2007, and 2010 the USGS, PCMSC collected bathymetry and acoustic backscatter data in Skagit Bay, Washington using an interferometric bathymetric sidescan-sonar system mounded to the USGS R/V Parke Snavely and the USGS R/V Karluk. The research was conducted in coordination with the Swinomish Indian Tribal Community, Skagit River System Cooperative, Skagit Watershed Council, Puget Sound Nearshore Ecosystem Restoration Project, and U.S. Army Corps of Engineers to characterize estuarine habitats and processes, including the sediment budget of the Skagit River and the influence of river-delta channelization on sediment transport. Information quantifying the distribution of habitats and extent that sediment transport influences habitats and the morphology of the delta is useful for planning for salmon recovery, agricultural resilience, flood risk protection, and coastal change associated with sea-level rise.

These metadata describe the U.S. Geological Survey (USGS), Pacific Coastal and Marine Science Center (PCMSC) 2005 bathymetry data collected in Skagit Bay Washington that is provided as a 1-m resolution TIFF image, as well as a 1-m resolution shaded-relief TIFF image. In 2004, 2005, 2007, and 2010 the U.S. Geological Survey (USGS), Pacific Coastal and Marine Science Center (PCMSC) collected bathymetry and acoustic backscatter data in Skagit Bay, Washington using an interferometric bathymetric sidescan sonar system mounded to the USGS R/V Parke Snavely and the USGS R/V Karluk. The research was conducted in coordination with the Swinomish Indian Tribal Community, Skagit River System Cooperative, Skagit Watershed Council, Puget Sound Nearshore Ecosystem Restoration Project, and U.S. Army Corps of Engineers to characterize estuarine habitats and processes, including the sediment budget of the Skagit River and the influence of river-delta channelization on sediment transport. Information quantifying the distribution of habitats and extent that sediment transport influences habitats and the morphology of the delta is useful for planning for salmon recovery, agricultural resilience, flood risk protection, and coastal change associated with sea-level rise.

These metadata describe the U.S. Geological Survey (USGS), Pacific Coastal and Marine Science Center (PCMSC) 2007 bathymetry data collected in Skagit Bay Washington that is provided as a 1-m resolution TIFF image, as well as a 1-m resolution shaded-relief TIFF image. In 2004, 2005, 2007, and 2010 the U.S. Geological Survey (USGS), Pacific Coastal and Marine Science Center (PCMSC) collected bathymetry and acoustic backscatter data in Skagit Bay, Washington using an interferometric bathymetric sidescan sonar system mounded to the USGS R/V Parke Snavely and the USGS R/V Karluk. The research was conducted in coordination with the Swinomish Indian Tribal Community, Skagit River System Cooperative, Skagit Watershed Council, Puget Sound Nearshore Ecosystem Restoration Project, and U.S. Army Corps of Engineers to characterize estuarine habitats and processes, including the sediment budget of the Skagit River and the influence of river-delta channelization on sediment transport. Information quantifying the distribution of habitats and extent that sediment transport influences habitats and the morphology of the delta is useful for planning for salmon recovery, agricultural resilience, flood risk protection, and coastal change associated with sea-level rise.

These metadata describe the U.S. Geological Survey (USGS), Pacific Coastal and Marine Science Center (PCMSC) 2010 bathymetry data collected in Skagit Bay Washington that is provided as a 1-m resolution TIFF image, as well as a 1-m resolution shaded-relief TIFF image. In 2004, 2005, 2007, and 2010 the U.S. Geological Survey (USGS), Pacific Coastal and Marine Science Center (PCMSC) collected bathymetry and acoustic backscatter data in Skagit Bay, Washington using an interferometric bathymetric sidescan sonar system mounded to the USGS R/V Parke Snavely and the USGS R/V Karluk. The research was conducted in coordination with the Swinomish Indian Tribal Community, Skagit River System Cooperative, Skagit Watershed Council, Puget Sound Nearshore Ecosystem Restoration Project, and U.S. Army Corps of Engineers to characterize estuarine habitats and processes, including the sediment budget of the Skagit River and the influence of river-delta channelization on sediment transport. Information quantifying the distribution of habitats and extent that sediment transport influences habitats and the morphology of the delta is useful for planning for salmon recovery, agricultural resilience, flood risk protection, and coastal change associated with sea-level rise.

These metadata describe the U.S. Geological Survey (USGS), Pacific Coastal and Marine Science Center (PCMSC) merged acoustic-backscatter imagery that was collected in 2005, 2007, and 2010 in Skagit Bay Washington that is provided as a 5-m resolution TIFF image. In 2004, 2005, 2007, and 2010 the U.S. Geological Survey (USGS), Pacific Coastal and Marine Science Center (PCMSC) collected bathymetry and acoustic backscatter data in Skagit Bay, Washington using an interferometric bathymetric sidescan sonar system mounded to the USGS R/V Parke Snavely and the USGS R/V Karluk. The research was conducted in coordination with the Swinomish Indian Tribal Community, Skagit River System Cooperative, Skagit Watershed Council, Puget Sound Nearshore Ecosystem Restoration Project, and U.S. Army Corps of Engineers to characterize estuarine habitats and processes, including the sediment budget of the Skagit River and the influence of river-delta channelization on sediment transport. Information quantifying the distribution of habitats and extent that sediment transport influences habitats and the morphology of the delta is useful for planning for salmon recovery, agricultural resilience, flood risk protection, and coastal change associated with sea-level rise.

These metadata describe the U.S. Geological Survey (USGS), Pacific Coastal and Marine Science Center (PCMSC) merged bathymetry digital terrain model comprised of the 2005, 2007, and 2010 bathymetry data collected in Skagit Bay Washington that is provided as a 1-m resolution TIFF image, as well as a 1-m resolution shaded-relief TIFF image. In 2004, 2005, 2007, and 2010 the U.S. Geological Survey (USGS), Pacific Coastal and Marine Science Center (PCMSC) collected bathymetry and acoustic backscatter data in Skagit Bay, Washington using an interferometric bathymetric sidescan sonar system mounded to the USGS R/V Parke Snavely and the USGS R/V Karluk. The research was conducted in coordination with the Swinomish Indian Tribal Community, Skagit River System Cooperative, Skagit Watershed Council, Puget Sound Nearshore Ecosystem Restoration Project, and U.S. Army Corps of Engineers to characterize estuarine habitats and processes, including the sediment budget of the Skagit River and the influence of river-delta channelization on sediment transport. Information quantifying the distribution of habitats and extent that sediment transport influences habitats and the morphology of the delta is useful for planning for salmon recovery, agricultural resilience, flood risk protection, and coastal change associated with sea-level rise.

This dataset includes 63 still images extracted from digital video imagery of sediment grab samples, along with laboratory grain size analysis of the sediment grab samples, taken from the mouth of the Columbia River, OR and WA, USA. Digital video was collected in September 2014 in the mouth of the Columbia River, USA, as part of the U.S. Geological Survey Coastal and Marine Geology Program contribution to the Office of Naval Research funded River and Inlets Dynamics experiment (RIVET II). Still images were extracted from the underwater video footage whenever the camera was resting on the sediment bed and individual sediment grains were visible and in focus. The images were used to calculate the calibration curve through auto-correlation regressed against the results of laboratory-determined median grain size (D50) of the grab samples (Barnard, 2007), provided in an accompanying .csv file.

This dataset includes 2,523 still images extracted from geo-referenced digital video imagery of the seafloor at the mouth of the Columbia River, OR and WA, USA, along with grain size analysis of the surface sediment. Underwater digital video was collected in September 2014 in the mouth of the Columbia River, USA, as part of the U.S. Geological Survey Coastal and Marine Geology Program contribution to the Office of Naval Research funded River and Inlets Dynamics experiment (RIVET II). Still images were extracted from the underwater video footage whenever the camera was resting on the sediment bed and individual sediment grains were visible and in focus. The images are used to calculate the median grain size through an auto-correlation method (Barnard and other 2007), and are provided in an accompanying .csv file.

We characterized seafloor sediment conditions near the mouth of the Elwha River from underwater photographs taken every four hours from September 2011 to December 2013. A digital camera was affixed to a tripod that was deployed in approximately 10 meters of water. Each photograph was qualitatively characterized as one of six categories: (1) base, or no sediment; (2) low sediment; (3) medium sediment; (4) high sediment; (5) turbid; or (6) kelp. For base conditions, no sediment was present on the seafloor. Low sediment conditions were characterized by a light dusting of sediment; medium sediment conditions were characterized by a layer of sediment that covered all rock surfaces but did not obscure the relief of the seafloor; high sediment conditions were characterized by a layer of sediment that covered all rock surfaces and obscured the relief of the seafloor. During turbid conditions, suspended sediment in the water column obscured the view of the seafloor, and during kelp conditions, blades of kelp covered the camera lens, blocking our view of the seafloor.

Abstract: This data release presents modeled time series of nearshore waves along the southern California coast, from Point Conception to the Mexican border, hindcasted for 1980-2010 and projected using global climate model forcing for 1975-2005 and 2012-2100. Details: As part of the Coastal Storm Modeling System (CoSMoS), time series of hindcast, historical, and 21st-century nearshore wave parameters (wave height, period, and direction) were simulated for the southern California coast from Point Conception to the Mexican border. Changes in deep-water wave conditions directly regulate the energy driving coastal processes. However, a number of physical processes, for example, refraction on continental shelves and/or diffraction by islands, transform deep-water waves as they propagate to the nearshore, which complicates large-scale modeling efforts. In this work, a hindcast of nearshore waves was simulated by forcing a numerical wave model with hindcasted intermediate-water waves and reanalysis winds. A lookup table was created by relating corresponding offshore winds and waves with nearshore wave conditions. Using the lookup table, historical and 21st-century nearshore-wave time series were generated for global climate model-forced offshore winds and waves. Three-hourly wave parameters from the U.S. Army Corps of Engineers Wave Information Studies (WIS; http://wis.usace.army.mil/) and near-surface winds (10 m above ground) from the California Reanalysis Downscaling at 10 km (CaRD10; Kanamitsu and Kanamaru, 2007) were used to force the Simulating Waves Nearshore (SWAN) numerical model in stationary mode over a curvilinear grid extending along the coast from Point Conception to the Mexican border and from the shoreline to approximately 25 km offshore to hindcast the time period 1980-2010. The offshore extent of the model domain was defined by the locations of WIS stations used for forcing. Horizontal-grid resolution varies largely depending on bathymetry and shoreline curvature, ranging from 24 to 543 m in the along- and across-shore directions. Bathymetry data are from the 2013 Coastal California TopoBathy Merge Project (National Oceanic and Atmospheric Administration, 2013). Wave spectra were computed with a JONSWAP shape, 10-degree directional resolution, and 34 frequency bands ranging logarithmically from 0.0418 to 1 Hz. Three-hourly nearshore wave parameters (significant wave height [Hs], mean wave period [Tm], peak wave period [Tp], mean wave direction [Dm], and peak wave direction [Dp]) were output from the simulations at the 10-m bathymetric contour approximately every 100 m in the alongshore direction at a total of 4,802 locations in the nearshore and at an additional 23 locations coincident with California Data Information Program (CDIP; Scripps Institute of Oceanography; http://cdip.ucsd.edu) wave buoys. A lookup table was generated by relating offshore wind and deep-water wave conditions at a single offshore point and nearshore wave conditions simulated by the wave hindcast. The open boundary of the SWAN simulation does not represent deep-water wave conditions, as it is located in intermediate water and shoreward of the Channel Islands. Therefore, the NOAA WW3 Climate Forecast System Reanalysis Reforecast (CFSRR; Chawla and others, 2012) wave time series at a single point (CDIP buoy 067, equivalent to National Data Buoy Center station 46219) defined the deep-water end member. The lookup table was based on binning CFSRR deep-water wave parameters (Hs, Tp, Dp) and CaRD10 wind speed (U) at CDIP 067. Significant wave height was binned from 0.5 to 10.25 m at 0.25-m intervals; peak wave period was binned from 3 to 24 s at 3-s intervals; peak wave direction was binned from 5 to 360 degrees at 5-degree intervals; and wind speed was binned from 0 to 24 m/s at 6-m/s intervals. Interval sizes for Hs and Tp were based on the average RMSE for each variable. For each combination of deep-water Hs, Tp, Dp, and U, time indices falling into each bin were identified. For each nearshore location, median Hs, Tp, Tm, Dp, and Dm corresponding to all time indices of a given set of deep-water binned conditions were computed to complete the lookup table. Because swell travel time from offshore to nearshore is on the order of 1.5 h (assuming an average depth of 100 m and Tp of 15 s over a distance of about 120 km) and the model outputs are at three-hourly intervals, we assume no time lag between deep water and nearshore conditions. Historical (1976-2005) and 21st-century (2012-2100) deep-water wave time series at CDIP 067 were derived from the WaveWatch3 wave model over global (1.25 deg x 1.25 deg) and nested eastern North Pacific regional (0.25 deg x 0.25 deg) grids forced by three-hourly near-surface wind fields from a global climate model (GCM; GFDL-ESM2M RCP 4.5). Wind (CaRD10 and GFDL-ESM2M at CDIP 067) and coincident deep-water wave time series were passed through the lookup table to generate historical and 21st-century nearshore wave conditions. Wind and wave conditions that were not present in the lookup table or that had not occurred in the hindcast were filled using quantile relationships. Outputs include: southern California three-hourly, nearshore wave parameters (Hs, Tp, Dp, Tm, Dm) for 4,802 locations approximately 100 m apart along the 10-m bathymetric contour from Point Conception to the Mexican border and for an additional 23 points collocated with CDIP wave buoys. Wave parameters are available for three periods: 1) a validated hindcast (1980-2010) period derived from reanalysis data, 2) a historical (1976-2005) projection derived from GFDL-ESM2M (GCM-historical), and 3) a 21st-century (2012-2100) projection also derived from GFDL-ESM2M. Data are available as NetCDF files packaged by region, with each file containing the time series for roughly 600 locations. The points collocated with wave buoys are within one separate file. References: Chawla, A., Spindler, D., and Tolman, H., 2012, 30 Year Wave Hindcasts using WAVEWATCH III with CFSR winds--Phase 1: National Oceanic and Atmospheric Administration, National Weather Service, Environmental Modeling Center, Marine Modeling and Analysis Branch, Technical note, MMAB Contribution n. 302, 12 p. with Appendices. Kanamitsu, M., and Kanamaru, H., 2007, 57-Year California Reanalysis Downscaling at 10km (CaRD10) Part 1--System Detail and Validation with Observations: Journal of Climate, v. 20, p. 5,527-5,552. National Oceanic and Atmospheric Administration, 2013, 2013 NOAA Coastal California TopoBathy Merge Project, National Oceanic and Atmospheric Administration, National Centers for Environmental Information database, accessed February 28, 2015 at https://coast.noaa.gov/dataviewer/#/lidar/search/where:ID=2612.

To support Coastal Storm Modeling System (CoSMoS) in the San Francisco Bay (v2.1), time series of historical and 21st-century near-surface wind fields (eastward and northward wind arrays) were simulated throughout the Bay. While global climate models (GCMs) provide useful projections of near-surface wind vectors into the 21st century, resolution is not sufficient enough for use in regional wave modeling projects, such as CoSMoS. Short-duration high wind speeds, on the order of hours, are of key importance in wave and subsequent coastal flood modeling. Here we present temporally-downscaled wind data for historical (1975-2004) and projected (2010-2100) time periods, developed using a method similar to constructed analogues (CA), suitable for use in local wave models.

Underwater video was collected in March 2014 in the nearshore waters of Faga`alu Bay on the island of Tutuila, American Samoa, as part of the U.S. Geological Survey Coastal and Marine Geology Program's Pacific Coral Reefs Project. This dataset includes 2,119 still images extracted from the video footage every 10 seconds and an Environmental Systems Research Institute (ESRI) shapefile of individual still-image locations with benthic habitat interpretations for each image.

Time-series of sediment chemistry, including organic biomarker composition and bulk inorganic geochemical analytes, from samples collected over a one-year period in a sediment trap. The sediment traps were deployed at a depth between 603 m to 1318 m, and they were programmed to rotate a 250 mL sample bottle at 30 d intervals, delivering 12 samples during the 1-year deployment between August 2012 and June 2013. In addition, dissolved water column nutrient concentrations and water column trace element particulate concentrations were collected in Baltimore Canyon on the U.S. Mid-Atlantic Bight (MAB).

This portion of the USGS data release presents sediment grain-size data from samples collected from the mouth of the Columbia River, Oregon and Washington, in 2013. Surface sediment was sampled using a small ponar, or 'grab', sampler on May 9, 2013 from the F/V Cape Windy at 3 locations. A handheld global navigation satellite system (GNSS) receiver was used to determine the locations of sediment samples. The grain size distributions of samples were determined using standard techniques developed by the USGS Pacific Coastal and Marine Science Center sediment lab. The grain-size data are provided in a comma-delimited spreadsheet (.csv).

Ocean surface current results from a physics-based, 3-dimensional coupled ocean-atmosphere numerical model were generated to understand coral larval dispersal patterns in Maui Nui, Hawaii, USA. The model was used to simulate coral larval dispersal patterns from a number of existing State-managed reefs and large tracks of reefs with high coral coverage that might be good candidates for marine-protected areas (MPAs) during 8 spawning events during 2010-2013. The goal of this effort is to provide geophysical data to help provide guidance to sustain coral health in Maui Nui, Hawaii, USA. Each model output run is available as a netCDF file with self-contained attribute information. Each file name is appended with the model-simulation date in YYYYMMDD format; the file name denotes the beginning of simulation portion of the model run, with the model starting and spinning up over two days before the model-simulation date in the file name.

Spatial surveys of water column physical properties were acquired with a conductivity-temperature-depth (CTD) profiler for four days in February 2015 and one day in July 2015 off the north coast of the island of Tutuila, American Samoa in support of a study on the coastal circulation patterns within and in the vicinity of the National Park of American Samoa.

Satellite-tracked, DGPS-equipped Lagrangian surface-current drifter deployments were conducted over 12 weeks between 14 April and 7 July 2015 at various locations within and offshore of the National Park of American Samoa study area to track surface currents. The drifters internally logged their location every 1 minute, and they transmitted their positions to satellites every 5 minutes. A drogue was attached to the drifters at 1 m below sea level in order to track the currents at that depth.

Time-series data of water surface elevation, wave height, and water column currents, temperature, and salinity were acquired for 150 days between 13 April and 14 July 2015 off the north coast of the island of Tutuila, American Samoa in support of a study on the coastal circulation patterns within and in the vicinity of the National Park of American Samoa.

Spatial surveys of water column currents and surface winds were conducted from February 17 to 20, 2015, off the north coast of the island of Tutuila, American Samoa. These data were collected using an acoustic-doppler current profiler (ADCP) and a meterological sensor in support of a study on the coastal circulation patterns within and in the vicinity of the National Park of American Samoa.

Topographic data were collected by the U.S. Geological Survey (USGS) in 2015 for Little Holland Tract in the Sacramento-San Joaquin River Delta, California. The data were collected on foot using a global positioning system (GPS) backpack platform that consisted of survey-grade Trimble R10 and R7 global navigation satellite system (GNSS) receivers with Zephyr 2 antennas. Orthometric elevations relative to NAVD88 were computed using the National Geodetic Survey Geoid12a, and the final data were projected in Cartesian coordinates using the UTM Zone 10 North (meters) (NAD83[2011]) coordinate system. The mean estimated vertical uncertainty of the 2015 USGS GPS backpack survey is 3.5 cm. 

Bathymetric data were collected by the U.S. Geological Survey (USGS) in 2015 for Little Holland Tract in the Sacramento-San Joaquin River Delta, California. The data were collected using a personal watercraft (PWC) platform that consisted of Trimble R7 Global Navigation Satellite System (GNSS) receivers with Zephyr 2 antennas, combined with Odom Echotrac CV-100 single-beam echosounders and 200 kHz transducers. Data was post-processed to remove spurious data points. Raw depths were converted to ellipsoid elevations in the data acquisition software. Orthometric elevations relative to NAVD88 were computed using National Geodetic Survey Geoid12a offsets, and the final data were projected in Cartesian coordinates using the UTM Zone 10 North (meters) (NAD83[2011]) coordinate system. The mean estimated vertical uncertainty of the 2015 USGS PWC survey is 6.1 cm.

This product is a digital elevation model (DEM) for the Little Holland Tract in the Sacramento-San Joaquin River Delta, California based on U.S. Geological Survey (USGS)-collected elevation data, merged with existing topographic and bathymetric elevation data. The USGS collected topographic and bathymetric elevation data in 2015, using a combination of methods. Topographic and shallow-water bathymetric data were collected on foot using a global positioning system (GPS) backpack platform that consisted of survey-grade Trimble R10, and Trimble R7 global navigation satellite system (GNSS) receivers with Zephyr 2 antennas. Bathymetric data were collected using a personal watercraft (PWC) platform that consisted of Trimble R7 GNSS receivers with Zephyr 2 antennas, combined with Odom Echotrac CV-100 single-beam echosounders and 200 kHz transducers. The USGS elevation data were merged with topographic aerial Light Detection and Ranging (lidar) data collected by California Department of Water Resources (DWR) in 2007 and single-beam bathymetric data collected by Environmental Data Solutions (EDS) in 2009 to generate the final DEM. The GeoTIFF raster and comma-delimited text files are available for download at http://doi.org/10.5066/F7RX9954.

This dataset includes swell-filtered, high-resolution seismic-reflection data, collected by the U.S. Geological Survey (USGS) in 2014, between Point Sal and Refugio State Beach in southern California.

This dataset includes navigation data for marine geophysical data, collected by the U.S. Geological Survey (USGS) in 2014, between Point Sal and Refugio State Beach in southern California.

This dataset includes raw, high-resolution seismic-reflection data, collected by the U.S. Geological Survey (USGS) in 2014, between Point Sal and Refugio State Beach in southern California.

This part of the USGS data release presents acoustic backscatter data for the Columbia River Mouth, Oregon and Washington. The acoustic backscatter data of the Columbia River Mouth, Oregon and Washington were collected by the U.S. Geological Survey (USGS). Mapping was completed in 2013, using a 234-kHz SEA SWATHPlus interferometric system. These data are not intended for navigational purposes.

This part of the USGS data release presents bathymetry data for the Columbia River Mouth, Oregon and Washington. The bathymetry data of the Columbia River Mouth, Oregon and Washington were collected by the U.S. Geological Survey (USGS). Mapping was completed in 2013, using a 234-kHz SEA SWATHPlus interferometric system. These data are not intended for navigational purposes.

Surface runoff and submarine groundwater discharge in particular are known vectors to the coastal ocean of elevated nutrients and contaminants leading to eutrophication, algal overgrowth, and coral disease. Freshwater discharging directly from submarine groundwater vents off of Kahekili Beach Park, Kaanapali, in West Maui contains elevated nutrient concentrations and lower pH values. Coral cores were collected in July 2013 from the shallow reef at Kahekili in Kaanapali, West Maui, Hawaii from scleractinian Porites lobata to specifically addresses the relationship between coral reef health and compounding stressors from contaminated submarine groundwater discharge.

Time-series of seawater carbonate chemistry variables, including salinity, dissolved inorganic nutrients, pH, total alkalinity, and dissolved inorganic carbon from sites along Kahekili Beach Park, west Maui near submarine groundwater seeps and living coral reefs. Samples for seawater were collected by pumping bottom water from the seafloor using a peristaltic pump and collecting discrete water samples every 4-hrs over a 6-day period.

This part of the data release presents bathymetry data from the Elwha River delta collected in February 2016 using a kayak. The kayak was equipped with a single-beam echosounder and a survey-grade global navigation satellite system (GNSS) receiver.

This part of the data release presents bathymetry data from the Elwha River delta collected in February 2016 using two personal watercraft (PWCs). The PWCs were equipped with single-beam echosounders and survey-grade global navigation satellite system (GNSS) receivers.

This portion of the USGS data release presents digital elevation models (DEMs) derived from bathymetric and topographic surveys conducted on the Elwha River delta in July 2017 (USGS Field Activity Number 2017-638-FA). Nearshore bathymetry data were collected using two personal watercraft (PWCs) and a kayak equipped with single-beam echosounders and survey-grade global navigation satellite systems (GNSS) receivers. Topographic data were collected on foot with survey-grade GNSS receivers mounted on backpacks. Positions of the survey platforms were referenced to a GNSS base station placed on a benchmark with known horizontal and vertical coordinates relative to the North American Datum of 1983 (CORS96 realization) and North American Vertical Datum of 1988. The final data were projected in Cartesian coordinates using the Washington State Plane North (meters) coordinate system. A total of 1,270,212 individual elevation points were collected within the survey area between July 20 and July 23, 2017. DEM surfaces were produced from all available elevation data using linear interpolation. Two separate DEMs were constructed. A DEM was produced that covered the entire survey area (approximately 511 ha) with 5-m horizontal resolution. A second DEM with 1-m resolution was produced that covered the river mouth and adjacent areas (approximately 131 ha). The DEMs were created by interpolating between measurements as much as 50 meters apart. For this reason, we cannot evaluate the accuracy of each point in the DEM, only the measurements it is based on. The estimated vertical uncertainties of the bathymetric and topographic measurements are 12 and 5 cm, respectively. Digital data files for each DEM are provided in ESRI ARC ASCII (*.asc) format.

This portion of the data release presents sediment grain-size data from samples collected on the Elwha River delta, Washington, in July 2017 (USGS Field Activity 2017-638-FA). Surface sediment was collected from 80 locations using a small ponar, or 'grab', sampler from the R/V Frontier in water depths between about 1 and 17 m around the delta. An additional 31 samples were collected by hand at low tide. A hand-held global satellite navigation system (GNSS) receiver was used to determine the locations of sediment samples. The grain size distributions of suitable samples were determined using standard techniques developed by the USGS Pacific Coastal and Marine Science Center sediment lab. Grab samples that yielded less than 50 g of sediment were omitted from analysis. The grain-size data are provided in a comma-delimited spreadsheet (.csv).

This part of the data release presents bathymetry data from the Elwha River delta collected in July 2017 using a kayak. The kayak was equipped with a single-beam echosounder and a survey-grade global navigation satellite system (GNSS) receiver.

This part of the data release presents bathymetry data from the Elwha River delta collected in July 2017 using two personal watercraft (PWCs). The PWCs were equipped with single beam echosounders and survey-grade global navigation satellite system (GNSS) receivers.

This part of the data release presents topography data from the Elwha River delta collected in July 2017. Topography data were collected on foot with global navigation satellite system (GNSS) receivers mounted on backpacks.

These metadata describe bathymetric data collected during a December 2018 SWATHPlus survey of Whiskeytown Lake, California. Data were collected and processed by the U.S. Geological Survey (USGS), Pacific Coastal and Marine Science Center (PCMSC) during fieldwork activity number 2018-686-FA. The bathymetric data are provided as a GeoTIFF image.

These metadata describe bathymetric data collected during a May 2019 SWATHPlus survey of Whiskeytown Lake, California. Data were collected and processed by the U.S. Geological Survey (USGS), Pacific Coastal and Marine Science Center (PCMSC) during fieldwork activity number 2018-686-FA. The bathymetric data are provided as a GeoTIFF image.

These metadata describe bathymetric data collected during a September 2021 SWATHPlus survey of Whiskeytown Lake, California. Data were collected and processed by the U.S. Geological Survey (USGS), Pacific Coastal and Marine Science Center (PCMSC) during fieldwork activity number 2018-686-FA. The bathymetric data are provided as a GeoTIFF image.

Hydrodynamic and sediment transport time-series data, including water depth, velocity, turbidity, conductivity, and temperature, were collected by the U.S. Geological Survey (USGS) Pacific Coastal and Marine Science Center within two embayments of San Francisco Bay. Data were collected in San Pablo Bay and Grizzly Bay from January to June 2020 at seven locations. Data files are grouped by area (shallows of San Pablo Bay, channel of San Pablo Bay, and shallows of Grizzly Bay). Each shallow site contained a variety of sensors located on two tripods, while the channel site consisted of one tripod. Users are advised to assess data quality carefully, and to check metadata for instrument information, as platform deployment times and data-processing methods varied.

This portion of the USGS data release presents eelgrass distribution and bathymetry data derived from acoustic surveys of the Nisqually River delta, Washington in 2012 (USGS Field Activity Number D-01-12-PS). Eelgrass and bathymetry data were collected from the R/V George Davidson equipped with a single-beam sonar system and global navigation satellite system (GNSS) receiver. The sonar system consisted of a Biosonics DT-X single-beam echosounder and 420 kHz transducer with a 6-degree beam angle. Depths from the echosounder were computed using sound velocity assuming a salinity of 30 psu and temperature of 10 degrees Celsius. Positioning of the survey vessel was determined at 5 to 10 Hz using a Trimble R7 GNSS receiver and Trimble Zephyr Model 2 antenna operating in real time kinematic (RTK) mode. Differential corrections were transmitted by a VHF radio to the GNSS receiver on the survey vessel at 1-Hz from a GNSS base station placed on a nearby benchmark with known horizontal and vertical coordinates relative to the North American Datum of 1983 (CORS96 realization). Output from the GNSS and sonar systems were combined in real time by the Biosonics DT-X deck unit and output to a computer running HYPACK hydrographic survey software. Navigation information was displayed on a video monitor, allowing the vessel operator to navigate along predefined survey lines spaced at 25-50 m intervals alongshore at speeds of 2 to 3 m/s. Acoustic backscatter data were analyzed using a custom graphical user interface that implements a signal processing algorithm applied to each sonar sounding that differentiates and extracts the location of the seafloor apart from the presence of vegetation (Stevens and others, 2008). Individual acoustic returns along a survey line were grouped into packets of ten, and eelgrass percent cover was calculated as the fractional percent of acoustic returns that were classified as vegetated within each group, resulting in an estimate of percent cover every 4 to 5 m (depending on the vessel speed). Orthometric elevations relative to the NAVD88 vertical datum were computed using National Geodetic Survey Geoid12a offsets. The average estimated vertical uncertainty of the bathymetric measurements is 12 cm. The point data are provided in a comma-separated text file and are projected in Cartesian coordinates using the Universal Transverse Mercator (UTM), Zone 10 north, meters coordinate system.

This portion of the USGS data release presents eelgrass distribution and bathymetry data derived from acoustic surveys of the Nisqually River delta, Washington in 2014 (USGS Field Activity Number D-01-14-PS). Eelgrass and bathymetry data were collected from the R/V George Davidson equipped with a single-beam sonar system and global navigation satellite system (GNSS) receiver. The sonar system consisted of a Biosonics DT-X single-beam echosounder and 420 kHz transducer with a 6-degree beam angle. Depths from the echosounder were computed using sound velocity data measured using a YSI CastAway CTD during the survey. Positioning of the survey vessel was determined at 5 to 10 Hz using a Trimble R7 GNSS receiver and Trimble Zephyr Model 2 antenna operating in real time kinematic (RTK) mode. Differential corrections were transmitted by a VHF radio to the GNSS receiver on the survey vessel at 1-Hz from a GNSS base station placed on a nearby benchmark with known horizontal and vertical coordinates relative to the North American Datum of 1983 (CORS96 realization). Output from the GNSS and sonar systems were combined in real time by the Biosonics DT-X deck unit and output to a computer running HYPACK hydrographic survey software. Navigation information was displayed on a video monitor, allowing the vessel operator to navigate along predefined survey lines spaced at 25-50 m intervals alongshore at speeds of 2 to 3 m/s. Acoustic backscatter data were analyzed using a custom graphical user interface that implements a signal processing algorithm applied to each sonar sounding that differentiates and extracts the location of the seafloor apart from the presence of vegetation (Stevens and others, 2008). Individual acoustic returns along a survey line were grouped into packets of ten, and eelgrass percent cover was calculated as the fractional percent of acoustic returns that were classified as vegetated within each group, resulting in an estimate of percent cover every 4 to 5 m (depending on the vessel speed). Orthometric elevations relative to the NAVD88 vertical datum were computed using National Geodetic Survey Geoid12a offsets. The average estimated vertical uncertainty of the bathymetric measurements is 5 cm. The point data are provided in a comma-separated text file and are projected in Cartesian coordinates using the Universal Transverse Mercator (UTM), Zone 10 north, meters coordinate system.

This portion of the USGS data release presents eelgrass distribution and bathymetry data derived from acoustic surveys of the Nisqually River delta, Washington in 2017 (USGS Field Activity Number 2017-614-FA). Eelgrass and bathymetry data were collected from the R/V George Davidson equipped with a single-beam sonar system and global navigation satellite system (GNSS) receiver. The sonar system consisted of a Biosonics DT-X single-beam echosounder and 420 kHz transducer with a 6-degree beam angle. Depths from the echosounder were computed using sound velocity data measured using a YSI CastAway CTD during the survey. Positioning of the survey vessel was determined at 5 to 10 Hz using a Trimble R7 GNSS receiver and Trimble Zephyr Model 2 antenna operating in real time kinematic (RTK) mode. Differential corrections were transmitted by a VHF radio to the GNSS receiver on the survey vessel at 1-Hz from a GNSS base station placed on a nearby benchmark with known horizontal and vertical coordinates relative to the North American Datum of 1983 (CORS96 realization). Output from the GNSS and sonar systems were combined in real time by the Biosonics DT-X deck unit and output to a computer running HYPACK hydrographic survey software. Navigation information was displayed on a video monitor, allowing the vessel operator to navigate along predefined survey lines spaced at 25-50 m intervals alongshore at speeds of 2-3 m/s. Acoustic backscatter data were analyzed using a custom graphical user interface that implements a signal processing algorithm applied to each sonar sounding that differentiates and extracts the location of the seafloor apart from the presence of vegetation (Stevens and others, 2008). Individual acoustic returns along a survey line were grouped into packets of ten, and eelgrass percent cover was calculated as the fractional percent of acoustic returns that were classified as vegetated within each group, resulting in an estimate of percent cover every 4 to 5 m (depending on the vessel speed). Orthometric elevations relative to the NAVD88 vertical datum were computed using National Geodetic Survey Geoid12a offsets. The average estimated vertical uncertainty of the bathymetric measurements is 5 cm. The point data are provided in a comma-separated text file and are projected in Cartesian coordinates using the Universal Transverse Mercator (UTM), Zone 10 north, meters coordinate system.

Hydrodynamic and sediment transport time-series data, including water depth, velocity, turbidity, conductivity, and temperature, were collected by the U.S. Geological Survey (USGS) Pacific Coastal and Marine Science Center within two embayments of San Francisco Bay. Data were collected in San Pablo Bay and Grizzly Bay from June to August 2019 at seven unique stations. Data files are grouped by area (shallows of San Pablo Bay, channel of San Pablo Bay, and shallows of Grizzly Bay). Each shallow site contained a variety of sensors located on two tripods and one surface mooring, while the channel site consisted of one tripod. Users are advised to assess data quality carefully, and to check metadata for instrument information, as platform deployment times and data-processing methods varied.

Time series data of water surface elevation, wave height, water column currents and temperature, and suspended sediment were acquired for 6 weeks on a coral reef off Jurabi Point, Ningaloo Coast UNESCO World Heritage site in Western Australia in support of a study on the circulation and sediment transport patterns of these reefs.

Geochemical analysis (including stable boron, boron:calcium ratio, and carbon and oxygen isotopes) were measured from coral cores collected in July 2013 from the shallow reef at Kahekili in Kaanapali, west Maui, Hawaii from scleractinian Porites lobata.

This data layer (PAC_CLC.txt) is one of five point coverages of known sediment samples, inspections, and probes from the usSEABED data collection for the U.S Pacific continental margin integrated using the software system dbSEABED. This data layer represents the calculated (CLC) output of the dbSEABED mining software. Data in this file extend variables determined through the data extraction (EXT) and data parsing (PRS) processes of dbSEABED, calculated using empirical relations or known functions. The CLC data is the most derivative and least accurate of the usSEABED data files and should be used with caution; however, many users may appreciate that it extends the coverage of map areas with attributes, especially physical properties attributes. Please refer to the dbSEABED page (https://pubs.usgs.gov/ds/2006/182/dbseabed.html), and the Frequently Asked Questions (https://pubs.usgs.gov/ds/2006/182/faq.html) pages for more information on the calculation process. This file contains the same data fields as the extracted (PAC_EXT) and parsed (PAC_PRS) data files, and the three files may be combined.

This data layer (PAC_CMP.txt) is one of five point coverages of known sediment samples, inspections, and probes from the usSEABED data collection for the U.S. Pacific continental margin integrated using the software system dbSEABED. This data file gives numeric data about selected components (for example, minerals, rock type, microfossils, and benthic biota) and sea floor features (for example, bioturbation, structure, and ripples) at a given site. Values in the attribute fields represent the membership to that attribute's fuzzy set. For components such as minerals, rocks, micro-biota and plants, and (or) epifauna and infauna, corals and other geologic and biologic information, the value depends on sentence structure and other components in description. For features (denoted by an '_F') such as ripples, ophiuroids, sponges, shrimp, worm tubes, lamination, lumps, grading, and (or) bioturbation, the value of the fuzzy set depends on the development of the attribute. Only the relative fuzzy presence of components and features can be determined; the absence of information does not indicate a lack of the attribute, only lack of information about that attribute. Table 5 (https://pubs.usgs.gov/ds/2006/182/table5.html) in the Larger_Work_Citation gives more information about the words or phrases that trigger each component and feature.

The facies data layer (PAC_FAC.txt) is one of five point coverages of known sediment samples, inspections, and probes from the usSEABED data collection for the U.S. Pacific margin, integrated using the software system dbSEABED. The facies data layer (PAC_FAC.txt) represents concatenated information about components (minerals and rock type), genesis (igneous, metamorphic, carbonate, terrigenous), and other appropriate groupings of information about the sea floor. These data are parsed from written descriptions from cores, grabs, photographs, and videos, and may apply only to a subsample as denoted by the Top, Bottom, and SamplePhase fields. The value "0" in a defined facies field does not necessarily imply lack of the components defining that field, but may imply a lack of data for that field. Table 6 (https://pubs.usgs.gov/ds/2006/182/table6.html) in the Larger_Work_Citation gives for a list of the facies, the contributing components, and relative weights.

This part of DS 781 presents data for the acoustic-backscatter map of Offshore of Aptos map area, California. Backscatter data are provided as two separate grids depending on mapping system and processing method. This metadata file refers to the data included in "BackscatterB_EM300_OffshoreAptos.zip," which is accessible from https://doi.org/10.5066/F7K35RQB. These data accompany the pamphlet and map sheets of Cochrane, G.R., Johnson, S.Y., Dartnell, P., Greene, H.G., Erdey, M.D, Dieter, B.E., Golden, N.E., Hartwell, S.R., Ritchie, A.C., Kvitek, r.G., Maier, K.L., Endris, C.A., Davenport, C.W., Watt, J.T., Sliter, R.W., Finlayson, D.P., and Krigsman, L.M., (G.R. Cochrane and S.A. Cochran, eds.), 2016, California State Waters Map Series—Offshore of Aptos, California: U.S. Geological Survey Open-File Report 2016–1025, 43 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20161025. The acoustic-backscatter map of Offshore of Aptos, California was generated from backscatter data collected by the U.S. Geological Survey (USGS) and by Monterey Bay Aquarium Research Institute (MBARI). Mapping was completed between 1998 and 2009, using a combination of a 234-kHz SWATHplus bathymetric sidescan-sonar system and a 30-kHz Simrad EM-300 multibeam echosounder. Within the final imagery, brighter tones indicate higher backscatter intensity, and darker tones indicate lower backscatter intensity. The intensity represents a complex interaction between the acoustic pulse and the seafloor, as well as characteristics within the shallow subsurface, providing a general indication of seafloor texture and composition. Backscatter intensity depends on the acoustic source level; the frequency used to image the seafloor; the grazing angle; the composition and character of the seafloor, including grain size, water content, bulk density, and seafloor roughness; and some biological cover. Harder and rougher bottom types such as rocky outcrops or coarse sediment typically return stronger intensities (high backscatter, lighter tones), whereas softer bottom types such as fine sediment return weaker intensities (low backscatter, darker tones).

This part of DS 781 presents data for the bathymetry map of Offshore of Aptos map area, California. Bathymetry data are provided as two separate grids depending on mapping agency and processing method. This metadata file refers to the data included in "BathymetryA_USGS_OffshoreAptos.zip" which are accessible from https://doi.org/10.5066/F7K35RQB. These data accompany the pamphlet and map sheets of Cochrane, G.R., Johnson, S.Y., Dartnell, P., Greene, H.G., Erdey, M.D, Dieter, B.E., Golden, N.E., Hartwell, S.R., Ritchie, A.C., Kvitek, r.G., Maier, K.L., Endris, C.A., Davenport, C.W., Watt, J.T., Sliter, R.W., Finlayson, D.P., and Krigsman, L.M., (G.R. Cochrane and S.A. Cochran, eds.), 2016, California State Waters Map Series—Offshore of Aptos, California: U.S. Geological Survey Open-File Report 2016–1025, 43 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20161025. The bathymetry and shaded-relief maps of Offshore of Aptos, California, were generated from bathymetry data collected by the U.S. Geological Survey (USGS) and by California State University, Monterey Bay (CSUMB). Mapping was completed between 2006 and 2009 using a combination of a 244-kHz Reson 8101 multibeam echosounder and a 234-kHz SEA SWATHplus bathymetric sidescan-sonar system. The mapping missions collected bathymetry data from about the 10-m isobath to beyond the 3-nautical-mile limit of California's State Waters. NOTE: The horizontal datum of this bathymetry data (NAD83) differs from the horizontal datum of other layers in this data release (WGS84).

This part of DS 781 presents data for the bathymetry map of Offshore of Aptos map area, California. Bathymetry data are provided as two separate grids depending on mapping agency and processing method. This metadata file refers to the data included in "BathymetryB_CSUMB_OffshoreAptos.zip" which are accessible from https://doi.org/10.5066/F7K35RQB. These data accompany the pamphlet and map sheets of Cochrane, G.R., Johnson, S.Y., Dartnell, P., Greene, H.G., Erdey, M.D, Dieter, B.E., Golden, N.E., Hartwell, S.R., Ritchie, A.C., Kvitek, r.G., Maier, K.L., Endris, C.A., Davenport, C.W., Watt, J.T., Sliter, R.W., Finlayson, D.P., and Krigsman, L.M., (G.R. Cochrane and S.A. Cochran, eds.), 2016, California State Waters Map Series—Offshore of Aptos, California: U.S. Geological Survey Open-File Report 2016–1025, 43 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20161025. The bathymetry and shaded-relief maps of Offshore Aptos, California, were generated from bathymetry data collected by the U.S. Geological Survey (USGS) and by California State University, Monterey Bay (CSUMB). Mapping was completed between 2006 and 2009 using a combination of a 244-kHz Reson 8101 multibeam echosounder and a 234-kHz SEA SWATHplus bathymetric sidescan-sonar system. The mapping missions collected bathymetry data from about the 10-m isobath to beyond the 3-nautical-mile limit of California's State Waters. NOTE: The horizontal datum of this bathymetry data (NAD83) differs from the horizontal datum of other layers in this data release (WGS84).

This part of DS 781 presents data for the bathymetric contours for the Offshore of Aptos map area, California. The vector data file is included in "Contours_OffshoreAptos.zip," which is accessible from https://doi.org/10.5066/F7K35RQB. These data accompany the pamphlet and map sheets of Cochrane, G.R., Johnson, S.Y., Dartnell, P., Greene, H.G., Erdey, M.D, Dieter, B.E., Golden, N.E., Hartwell, S.R., Ritchie, A.C., Kvitek, r.G., Maier, K.L., Endris, C.A., Davenport, C.W., Watt, J.T., Sliter, R.W., Finlayson, D.P., and Krigsman, L.M., (G.R. Cochrane and S.A. Cochran, eds.), 2016, California State Waters Map Series—Offshore of Aptos, California: U.S. Geological Survey Open-File Report 2016–1025, 43 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20161025. 10-m interval contours of the Offshore Aptos map area, California, were generated from bathymetry data collected by the U.S. Geological Survey (USGS) and by California State University, Monterey Bay (CSUMB). Mapping was completed between 2006 and 2009 using a combination of a 244-kHz Reson 8101 multibeam echosounder and a 234-kHz SEA SWATHplus bathymetric sidescan-sonar system. The mapping missions collected bathymetry data from about the 10-m isobath to beyond the 3-nautical-mile limit of California's State Waters.

This part of DS 781 presents 2-m-resolution data for the acoustic-backscatter map of the Offshore of Point Conception Map Area, California. The GeoTiff is included in "Backscatter_OffshorePointConception.zip," which is accessible from https://doi.org/10.5066/F7QN64XQ. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Hartwell, S.R., Golden, N.E., Kvitek, R.G., and Davenport, C.W. (S.Y. Johnson and S.A. Cochran, eds.), 2018, California State Waters Map Series—Offshore of Point Conception, California: U.S. Geological Survey Open-File Report 2018–1024, pamphlet 36 p., 9 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20181024. This acoustic-backscatter map of the Offshore of Point Conception map area in southern California was generated from acoustic-backscatter data collected by Fugro Pelagos Inc. Acoustic mapping was completed in 2008 using a combination of 400-kHz Reson 7125, 240-kHz Reson 8101, and 100-kHz Reson 8111 multibeam echosounders. These acoustic-backscatter data cover the area from about the 10-m isobath to beyond the limit of California’s State Waters.

This part of DS 781 presents data for bathymetry for several seafloor maps of the Offshore of Point Conception Map Area, California. The vector data file is included in "Bathymetry_OffshorePointConception.zip," which is accessible from https://doi.org/10.5066/F7QN64XQ. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Hartwell, S.R., Golden, N.E., Kvitek, R.G., and Davenport, C.W. (S.Y. Johnson and S.A. Cochran, eds.), 2018, California State Waters Map Series—Offshore of Point Conception, California: U.S. Geological Survey Open-File Report 2018–1024, pamphlet 36 p., 9 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20181024. Shaded-relief bathymetry of the Offshore of Point Conception map area in southern California was generated largely from acoustic-bathymetry data collected by Fugro Pelagos Inc. Acoustic mapping was completed in 2008 using a combination of 400-kHz Reson 7125, 240-kHz Reson 8101, and 100-kHz Reson 8111 multibeam echosounders. Bathymetric-lidar data was collected in the nearshore area by the U.S. Army Corps of Engineers (USACE) Joint Lidar Bathymetry Technical Center of Expertise in 2009 and 2010. These mapping missions combine to provide continuous bathymetric data from the shoreline as well as acoustic-backscatter data from about the 10-m isobath to beyond the limit of California's State Waters.

This part of DS 781 presents data for bathymetry for several seafloor maps of the Offshore of Point Conception Map Area, California. The GeoTiff is included in "Bathymetry_OffshorePointConception.zip," which is accessible from https://doi.org/10.5066/F7QN64XQ. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Hartwell, S.R., Golden, N.E., Kvitek, R.G., and Davenport, C.W. (S.Y. Johnson and S.A. Cochran, eds.), 2018, California State Waters Map Series—Offshore of Point Conception, California: U.S. Geological Survey Open-File Report 2018–1024, pamphlet 36 p., 9 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20181024. Bathymetry map of the Offshore of Point Conception map area in southern California was generated largely from acoustic-bathymetry data collected by Fugro Pelagos Inc. Acoustic mapping was completed in 2008 using a combination of 400-kHz Reson 7125, 240-kHz Reson 8101, and 100-kHz Reson 8111 multibeam echosounders. Bathymetric-lidar data was collected in the nearshore area by the U.S. Army Corps of Engineers (USACE) Joint Lidar Bathymetry Technical Center of Expertise in 2009 and 2010. These mapping missions combine to provide continuous bathymetric data from the shoreline as well as acoustic-backscatter data from about the 10-m isobath to beyond the limit of California's State Waters.

This part of DS 781 presents data for bathymetric contours for several seafloor maps of the Offshore of Point Conception Map Area, California. The vector data file is included in "Contours_OffshorePointConception.zip," which is accessible from https://doi.org/10.5066/F7QN64XQ. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Hartwell, S.R., Golden, N.E., Kvitek, R.G., and Davenport, C.W. (S.Y. Johnson and S.A. Cochran, eds.), 2018, California State Waters Map Series—Offshore of Point Conception, California: U.S. Geological Survey Open-File Report 2018–1024, pamphlet 36 p., 9 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20181024. Bathymetry contours of the Offshore of Point Conception map area in southern California were generated from acoustic-bathymetry data collected by Fugro Pelagos Inc. Acoustic mapping was completed in 2008 using a combination of 400-kHz Reson 7125, 240-kHz Reson 8101, and 100-kHz Reson 8111 multibeam echosounders. Bathymetric-lidar data was collected in the nearshore area by the U.S. Army Corps of Engineers (USACE) Joint Lidar Bathymetry Technical Center of Expertise in 2009 and 2010. These mapping missions combine to provide continuous bathymetric data from the shoreline as well as acoustic-backscatter data from about the 10-m isobath to beyond the limit of California's State Waters. Bathymetric contours at 10-m intervals were generated from a modified 2-m-resolution bathymetric surface. The most continuous contour segments were preserved; smaller segments and isolated island polygons were excluded from the final output. Contours were smoothed using a polynomial approximation with exponential kernel algorithm and a tolerance value of 60 m. The contours were then clipped to the boundary of the map area.

This part of DS 781 presents data for the geologic and geomorphic map of the Offshore of Point Conception map area, California. The vector data file is included in "Geology_OffshorePointConception.zip," which is accessible from https://doi.org/10.5066/F7QN64XQ. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Hartwell, S.R., Golden, N.E., Kvitek, R.G., and Davenport, C.W. (S.Y. Johnson and S.A. Cochran, eds.), 2018, California State Waters Map Series-Offshore of Point Conception, California: U.S. Geological Survey Open-File Report 2018-1024, pamphlet 36 p., 9 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20181024. Marine geology and geomorphology was mapped in the Offshore of Point Conception map area, California, from approximate Mean High Water (MHW) to the 3-nautical-mile limit of California's State Waters. Offshore geologic units were delineated on the basis of integrated analyses of adjacent onshore geology with multibeam bathymetry and backscatter imagery, seafloor-sediment and rock samples, digital camera and video imagery, and high-resolution seismic-reflection profiles.

This part of DS 781 presents data for the habitat map of the Offshore of Point Conception Map Area, California. The vector data file is included in "Habitat_OffshorePointConception.zip," which is accessible from https://doi.org/10.5066/F7QN64XQ. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Hartwell, S.R., Golden, N.E., Kvitek, R.G., and Davenport, C.W. (S.Y. Johnson and S.A. Cochran, eds.), 2018, California State Waters Map Series—Offshore of Point Conception, California: U.S. Geological Survey Open-File Report 2018–1024, pamphlet 36 p., 9 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20181024. This map shows physical marine benthic habitats in the Offshore of Point Conception map area. Marine benthic habitats represent a particular type of water quality, substrate, geomorphology, seafloor process, or any other attribute that may provide a habitat for a specific species or an assemblage of organisms. Marine benthic habitats are classified using the Coastal and Marine Ecological Classification Standard (CMECS), developed by representatives from a consortium of federal agencies. CMECS is the U.S. government standard for marine habitat characterization. The standard provides an ecologically relevant structure for biologic, geologic, chemical, and physical habitat attributes. This map illustrates the geoform and substrate components of the standard. This map was derived from geologic and geomorphic map units by translation of the unit description into the best-fit values of CMECS classes. The CMECS classes are documented at https://www.fgdc.gov/standards/projects/FGDC-standards-projects/cmecs-folder/CMECS_Version_06-2012_FINAL.pdf.

This part of DS 781 presents data for the Seafloor character map of the Offshore of Point Conception Map Area, California. The vector data file is included in "SeafloorCharacter_OffshorePointConception.zip," which is accessible from https://doi.org/10.5066/F7QN64XQ. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Hartwell, S.R., Golden, N.E., Kvitek, R.G., and Davenport, C.W. (S.Y. Johnson and S.A. Cochran, eds.), 2018, California State Waters Map Series—Offshore of Point Conception, California: U.S. Geological Survey Open-File Report 2018–1024, pamphlet 36 p., 9 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20181024. This raster-format seafloor-character map shows four substrate classes in the Offshore of Point Conception map area, California. The substrate classes mapped in this area have been colored to indicate which of the following California Marine Life Protection Act depth zones and slope classes they belong: Depth Zone 2 (intertidal to 30 m), Depth Zone 3 (30 to 100 m), Depth Zone 4 (100 to 200 m), Depth Zone 5 (deeper than 200 m), Slope Class 1 (0 degrees - 5 degrees; flat), and Slope Class 2 (5 degrees - 30 degrees; sloping). Depth Zone 1 (intertidal), and Slopes Classes 3 and 4 (greater than 30 degrees) are not present in this map area. The map is created using a supervised classification method described by Cochrane (2008), using multibeam echosounder (MBES) bathymetry and backscatter data collected and processed between 1998 and 2014. References Cited: Cochrane, G.R., 2008, Video-supervised classification of sonar data for mapping seafloor habitat, in Reynolds, J.R., and Greene, H.G., eds., Marine habitat mapping technology for Alaska: Fairbanks, University of Alaska, Alaska Sea Grant College Program, p. 185-194, available at http://doc.nprb.org/web/research/research%20pubs/615_habitat_mapping_workshop/Individual%20Chapters%20High-Res/Ch13%20Cochrane.pdf.

This part of DS 781 presents 2-m-resolution data collected by Fugro Pelagos for the acoustic-backscatter map of the Offshore of Gaviota Map Area, California. The GeoTiff is included in "Backscatter_[Fugro]_OffshoreGaviota.zip," which is accessible from https://doi.org/10.5066/F7TH8JWJ. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Hartwell, S.R., Golden, N.E., Kvitek, R.G., and Davenport, C.W. (S.Y. Johnson and S.A. Cochran, eds.), 2018, California State Waters Map Series—Offshore of Gaviota, California: U.S. Geological Survey Open-File Report 2018–1023, pamphlet 41 p., 9 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20181023. The acoustic-backscatter map of the Offshore of Gaviota map area in southern California was generated from acoustic-backscatter data collected by the U.S. Geological Survey (USGS) and by Fugro Pelagos Inc. Acoustic mapping was completed between 2007 and 2008 using a combination of 400-kHz Reson 7125, 240-kHz Reson 8101, and 100-kHz Reson 8111 multibeam echosounders, as well as a 234-kHz SEA SWATHplus bathymetric sidescan-sonar system. These mapping missions combined to collect acoustic-backscatter data from about the 10-m isobath to beyond the limit of California's State Waters.

This part of DS 781 presents 2-m-resolution data collected by the U.S. Geological Survey in 2007 for the acoustic-backscatter map of the Offshore of Gaviota Map Area, California. The GeoTiff is included in "Backscatter_[USGS07]_OffshoreGaviota.zip," which is accessible from https://doi.org/10.5066/F7TH8JWJ. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Hartwell, S.R., Golden, N.E., Kvitek, R.G., and Davenport, C.W. (S.Y. Johnson and S.A. Cochran, eds.), 2018, California State Waters Map Series—Offshore of Gaviota, California: U.S. Geological Survey Open-File Report 2018–1023, pamphlet 41 p., 9 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20181023. The acoustic-backscatter map of the Offshore of Gaviota map area in southern California was generated from acoustic-backscatter data collected by the U.S. Geological Survey (USGS) and by Fugro Pelagos Inc. Acoustic mapping was completed between 2007 and 2008 using a combination of 400-kHz Reson 7125, 240-kHz Reson 8101, and 100-kHz Reson 8111 multibeam echosounders, as well as a 234-kHz SEA SWATHplus bathymetric sidescan-sonar system. These mapping missions combined to collect acoustic-backscatter data from about the 10-m isobath to beyond the limit of California's State Waters.

This part of DS 781 presents 2-m-resolution data collected by the U.S. Geological Survey in 2008 for the acoustic-backscatter map of the Offshore of Gaviota Map Area, California. The GeoTiff is included in "Backscatter_[USGS08]_OffshoreGaviota.zip," which is accessible from https://doi.org/10.5066/F7TH8JWJ. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Hartwell, S.R., Golden, N.E., Kvitek, R.G., and Davenport, C.W. (S.Y. Johnson and S.A. Cochran, eds.), 2018, California State Waters Map Series—Offshore of Gaviota, California: U.S. Geological Survey Open-File Report 2018–1023, pamphlet 41 p., 9 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20181023. The acoustic-backscatter map of the Offshore of Gaviota map area in southern California was generated from acoustic-backscatter data collected by the U.S. Geological Survey (USGS) and by Fugro Pelagos Inc. Acoustic mapping was completed between 2007 and 2008 using a combination of 400-kHz Reson 7125, 240-kHz Reson 8101, and 100-kHz Reson 8111 multibeam echosounders, as well as a 234-kHz SEA SWATHplus bathymetric sidescan-sonar system. These mapping missions combined to collect acoustic-backscatter data from about the 10-m isobath to beyond the limit of California's State Waters.

This part of DS 781 presents data for bathymetry for several seafloor maps of the Offshore of Gaviota Map Area, California. The vector data file is included in "BathymetryHS_OffshoreGaviota.zip," which is accessible from https://doi.org/10.5066/F7TH8JWJ. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Hartwell, S.R., Golden, N.E., Kvitek, R.G., and Davenport, C.W. (S.Y. Johnson and S.A. Cochran, eds.), 2018, California State Waters Map Series—Offshore of Gaviota, California: U.S. Geological Survey Open-File Report 2018–1023, pamphlet 41 p., 9 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20181023. Shaded-relief bathymetry of the Offshore of Gaviota map area in southern California was generated from acoustic-bathymetry data collected largely by the U.S. Geological Survey (USGS) and by Fugro Pelagos Inc. Acoustic mapping was completed between 2007 and 2008 using a combination of 400-kHz Reson 7125, 240-kHz Reson 8101, and 100-kHz Reson 8111 multibeam echosounders, as well as a 234-kHz SEA SWATHplus bathymetric sidescan-sonar system. In addition, bathymetric-lidar data was collected in the nearshore area by the U.S. Army Corps of Engineers (USACE) Joint Lidar Bathymetry Technical Center of Expertise in 2009 and 2010. These mapping missions combine to provide continuous bathymetric data from the shoreline to beyond the limit of California's State Waters.

This part of DS 781 presents data for bathymetry for several seafloor maps of the Offshore of Gaviota Map Area, California. The GeoTiff is included in "Bathymetry_OffshoreGaviota.zip," which is accessible from https://doi.org/10.5066/F7TH8JWJ. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Hartwell, S.R., Golden, N.E., Kvitek, R.G., and Davenport, C.W. (S.Y. Johnson and S.A. Cochran, eds.), 2018, California State Waters Map Series—Offshore of Gaviota, California: U.S. Geological Survey Open-File Report 2018–1023, pamphlet 41 p., 9 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20181023. Bathymetry of the Offshore of Gaviota map area in southern California was generated from acoustic-bathymetry data collected largely by the U.S. Geological Survey (USGS) and by Fugro Pelagos Inc. Acoustic mapping was completed between 2007 and 2008 using a combination of 400-kHz Reson 7125, 240-kHz Reson 8101, and 100-kHz Reson 8111 multibeam echosounders, as well as a 234-kHz SEA SWATHplus bathymetric sidescan-sonar system. In addition, bathymetric-lidar data was collected in the nearshore area by the U.S. Army Corps of Engineers (USACE) Joint Lidar Bathymetry Technical Center of Expertise in 2009 and 2010. These mapping missions combine to provide continuous bathymetric data from the shoreline to beyond the limit of California's State Waters.

This part of DS 781 presents data for bathymetric contours for several seafloor maps of the Offshore of Gaviota Map Area, California. The vector data file is included in "Contours_OffshoreGaviota.zip," which is accessible from https://doi.org/10.5066/F7TH8JWJ. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Hartwell, S.R., Golden, N.E., Kvitek, R.G., and Davenport, C.W. (S.Y. Johnson and S.A. Cochran, eds.), 2018, California State Waters Map Series—Offshore of Gaviota, California: U.S. Geological Survey Open-File Report 2018–1023, pamphlet 41 p., 9 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20181023. Bathymetry contours of the Offshore of Gaviota map area in southern California was generated from acoustic-bathymetry data collected largely by the U.S. Geological Survey (USGS) and by Fugro Pelagos Inc. Acoustic mapping was completed between 2007 and 2008 using a combination of 400-kHz Reson 7125, 240-kHz Reson 8101, and 100-kHz Reson 8111 multibeam echosounders, as well as a 234-kHz SEA SWATHplus bathymetric sidescan-sonar system. In addition, bathymetric-lidar data was collected in the nearshore area by the U.S. Army Corps of Engineers (USACE) Joint Lidar Bathymetry Technical Center of Expertise in 2009 and 2010. These mapping missions combine to provide continuous bathymetric data from the shoreline to beyond the limit of California's State Waters. Bathymetric contours at 10-m intervals were generated from a modified 2-m-resolution bathymetric surface. The most continuous contour segments were preserved; smaller segments and isolated island polygons were excluded from the final output. Contours were smoothed using a polynomial approximation with exponential kernel algorithm and a tolerance value of 60 m. The contours were then clipped to the boundary of the map area.

This part of DS 781 presents data for the geologic and geomorphic map of the Offshore of Gaviota map area, California. The vector data file is included in "Geology_OffshoreGaviota.zip," which is accessible from https://doi.org/10.5066/F7TH8JWJ. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Hartwell, S.R., Golden, N.E., Kvitek, R.G., and Davenport, C.W. (S.Y. Johnson and S.A. Cochran, eds.), 2018, California State Waters Map Series-Offshore of Gaviota, California: U.S. Geological Survey Open-File Report 2018-1023, pamphlet 41 p., 9 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20181023. Marine geology and geomorphology was mapped in the Offshore of Gaviota map area, California, from approximate Mean High Water (MHW) to the 3-nautical-mile limit of California's State Waters. Offshore geologic units were delineated on the basis of integrated analyses of adjacent onshore geology with multibeam bathymetry and backscatter imagery, seafloor-sediment and rock samples, digital camera and video imagery, and high-resolution seismic-reflection profiles.

This part of DS 781 presents data for the habitat map of the Offshore of Gaviota Map Area, California. The vector data file is included in "Habitat_OffshoreGaviota.zip," which is accessible from https://doi.org/10.5066/F7TH8JWJ. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Hartwell, S.R., Golden, N.E., Kvitek, R.G., and Davenport, C.W. (S.Y. Johnson and S.A. Cochran, eds.), 2018, California State Waters Map Series—Offshore of Gaviota, California: U.S. Geological Survey Open-File Report 2018–1023, pamphlet 41 p., 9 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20181023. This map shows physical marine benthic habitats in the Offshore of Gaviota map area. Marine benthic habitats represent a particular type of water quality, substrate, geomorphology, seafloor process, or any other attribute that may provide a habitat for a specific species or an assemblage of organisms. Marine benthic habitats are classified using the Coastal and Marine Ecological Classification Standard (CMECS), developed by representatives from a consortium of federal agencies. CMECS is the U.S. government standard for marine habitat characterization. The standard provides an ecologically relevant structure for biologic, geologic, chemical, and physical habitat attributes. This map illustrates the geoform and substrate components of the standard. This map was derived from geologic and geomorphic map units by translation of the unit description into the best-fit values of CMECS classes. The CMECS classes are documented at https://www.fgdc.gov/standards/projects/FGDC-standards-projects/cmecs-folder/CMECS_Version_06-2012_FINAL.pdf.

This part of DS 781 presents data for the Seafloor character map of the Offshore of Gaviota map area, California. The vector data file is included in "SeafloorCharacter_OffshoreGaviota.zip," which is accessible from https://doi.org/10.5066/F7TH8JWJ. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Hartwell, S.R., Golden, N.E., Kvitek, R.G., and Davenport, C.W. (S.Y. Johnson and S.A. Cochran, eds.), 2018, California State Waters Map Series-Offshore of Gaviota, California: U.S. Geological Survey Open-File Report 2018-1023, pamphlet 41 p., 9 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20181023. This raster-format seafloor-character map shows five substrate classes in the Offshore of Gaviota map area, California. The substrate classes mapped in this area have been colored to indicate which of the following California Marine Life Protection Act depth zones and the Coastal and Marine Ecological Classification Standard (CMECS) slope classes they belong: Depth Zone 2 (intertidal to 30 m), Depth Zone 3 (30 to 100 m), Depth Zone 4 (100 to 200 m), Slope Class 1 (0 degrees - 5 degrees; flat), and Slope Class 2 (5 degrees - 30 degrees; sloping). Depth Zone 1 (intertidal), Depth Zone 5 (greater than 200 m), and Slope Classes 3 and 4 (greater than 30 degrees) are not present in this map area. The map is created using a supervised classification method described by Cochrane (2008), using multibeam echosounder (MBES) bathymetry and backscatter data collected and processed between 1998 and 2014. References Cited: Cochrane, G.R., 2008, Video-supervised classification of sonar data for mapping seafloor habitat, in Reynolds, J.R., and Greene, H.G., eds., Marine habitat mapping technology for Alaska: Fairbanks, University of Alaska, Alaska Sea Grant College Program, p. 185-194, available at http://doc.nprb.org/web/research/research%20pubs/615_habitat_mapping_workshop/Individual%20Chapters%20High-Res/Ch13%20Cochrane.pdf.

A benthic habitat polygon coverage has been created of the coral reef ecosystem on the south shore of Moloka'i. Polygons were hand-digitized from visual interpretation of aerial photography and SHOALS bathymetry data. We also utilized in situ knowledge from towed instruments, underwater photography and videography, and diver and snorkeler observations. The polygons have attributes for Main Structure/Substrate, Dominant Structure/Substrate, Major Biological Cover, Percent of Major Biological Cover, Reef Zone, and Unique ID, and measurements of acreage, area (m2) and perimeter (m) of each polygon.

ArcInfo GRID format data generated from the 2004 multibeam sonar survey of the Northeastern Channel Islands, CA Region. The data include high-resolution, acoustic, corrected backscatter.

A benthic habitat polygon coverage has been created of the coral reef ecosystem within the U.S. Coral Reef Task Force Watershed Partnership Initiative Kaanapali priority study area and the State of Hawaii Kahekili Herbivore Fisheries Management Area, West-Central Maui, Hawaii. Polygons were hand-digitized from visual interpretation of QuickBird-2 satellite imagery (2005), and SHOALS bathymetry data. We also utilized in situ knowledge from underwater photography and videography (2002-2011), side-scan sonar data, and diver and snorkeler observations. The polygons have attributes for Main Structure/Substrate, Dominant Structure/Substrate, Major Biological Cover, Percent of Major Biological Cover, Reef Zone, Unique ID, and measurements of Area (in square meters) of each polygon.

A benthic habitat polygon coverage has been created of the coral reef ecosystem off the coast of Pu'ukohola Heiau (PUHE) National Historic Site on the Kona Coast of Hawai'i. Polygons were hand-digitized from visual interpretation of aerial photography and SHOALS bathymetry data. We also utilized in situ knowledge from towed instruments, underwater photography and videography, and diver and snorkeler observations. The polygons have attributes for Main Structure/Substrate, Dominant Structure/Substrate, Major Biological Cover, Percent of Major Biological Cover, Reef Zone, and Unique ID, and measurements of area (m2) of each polygon.

A benthic habitat polygon coverage has been created of the coral reef ecosystem within and adjacent to Kaloko-Honokohau (KAHO) National Historical Park on the Kona Coast of Hawai'i. Polygons were hand-digitized from visual interpretation of aerial photography and SHOALS bathymetry data. We also utilized in situ knowledge from towed instruments, underwater photography and videography, and diver and snorkeler observations. The polygons have attributes for Main Structure/Substrate, Dominant Structure/Substrate, Major Biological Cover, Percent of Major Biological Cover, Reef Zone, Unique ID, and measurements of Area (m2) of each polygon.

A benthic habitat polygon coverage has been created of the coral reef ecosystem off the coast of Pu'uhonua O Honaunau (PUHO) National Historical Park on the Kona Coast of Hawai'i. Polygons were hand-digitized from visual interpretation of aerial photography and SHOALS bathymetry data. We also utilized in situ knowledge from towed instruments, underwater photography and videography, and diver and snorkeler observations. The polygons have attributes for Main Structure/Substrate, Dominant Structure/Substrate, Major Biological Cover, Percent of Major Biological Cover, Reef Zone, Unique ID, and measurements of area (m2) of each polygon.

The 2015 Mississippi coastal shorelines were originally extracted from 2015 Landsat imagery and published within United States Geological Survey (USGS) Open-File Report (OFR) 2015-1179 (https://doi.org/10.3133/ofr20151179). Shoreline files for Ship, Horn, and Petit Bois Islands were merged to a single shapefile and spatially adjusted using 2015/2016 USGS bathymetric survey tracklines (Dewitt and others, 2017) to more closely match island shoreline positions during USGS surveys.

Assessing the physical change to shorelines and wetlands is critical in determining the resiliency of wetland systems that protect adjacent habitat and communities. The wetland and back-barrier shorelines of Assateague Island, located in Maryland and Virginia, changed as a result of wave action and storm surge that occurred during Hurricane Sandy, which made landfall on October 29, 2012. The impact of Hurricane Sandy will be assessed and placed in its historical context to understand the future vulnerability of wetland systems. Making these assessments will rely on data extracted from current and historical resources such as maps, aerial photographs, satellite imagery, and lidar elevation data, which document physical changes over time. This USGS Data Series publication includes includes several open-ocean shorelines, back-island shorelines, back-island shoreline points, sand area polygons, and sand lines for Assateague Island that were extracted from orthoimagery (ortho aerial photography)dated from April 12, 1989 to September 5, 2013.

Multichannel seismic-reflection (MCS) data were collected in the California Continental Borderland as part of southern California Earthquake Hazards Task. Five data acquisition cruises conducted over a six-year span collected MCS data from offshore Santa Barbara, California south to the Exclusive Economic Zone boundary with Mexico. The primary mission was to map late Quaternary deformation as well as identify and characterize fault zones that have potential to impact high population areas of southern California. To meet its objectives, the project work focused on the distribution, character, and relative intensity of active (i.e., Holocene) deformation along the continental shelf and basins adjacent to the most highly populated areas. In addition, the project examined the Pliocene-Pleistocene record of how deformation shifted in space and time to help identify actively deforming structures that may constitute current significant seismic hazards. The MCS data accessible through this report cover the first four years of survey activity and include data from offshore Malibu coastal area west of Santa Monica, California to the southern survey limit offshore San Diego. The MCS data, which were collected with a 250-m-long, 24-channel streamer used a small gas-injector airgun source. This system provided optimum resolution of the upper 1 to 2 km of sediment for mapping active fault systems. The report includes trackline maps showing the location of the data, as well as both digital data files (SEG-Y) and images of all of the profiles. These data are also available via GeoMapApp (http://www.geomapapp.org/) and Virtual Ocean ( http://www.virtualocean.org/) earth science exploration and visualization applications.

CCALBATC consists of bathymetric contours at 10-m and 50-m intervals for the area offshore of central California between Point Arena to the north and Point Sur to the south. The lines were digitized from 1:250,000-scale NOAA charts. This is one of a collection of digital files of a geographic information system of spatially referenced data related to the USGS Coastal and Marine Geology Program Monterey Bay National Marine Sanctuary Project (see this and other older Monterey Bay USGS works archived at https://archive.usgs.gov/archive/sites/walrus.wr.usgs.gov/monterey/index.html.

This dataset contains bathymetric contours for the greater Monterey Bay area between Point Ano Nuevo to the north and Point Sur to the south. Contours are provided at 10-m intervals to a depth of 200 m and 100-m intervals to maximum depth. The data from which the contours were derived were hydrographic survey points published by NOAA NOS in 1998. This is one of a collection of digital files of a geographic information system of spatially referenced data related to the USGS Coastal and Marine Geology Program Monterey Bay National Marine Sanctuary Project (see this and other older Monterey Bay USGS works archived at https://archive.usgs.gov/archive/sites/walrus.wr.usgs.gov/monterey/index.html.

This part of the data release contains a grid of standard deviations of bathymetric soundings within each 0.5 m x 0.5 m grid cell. The bathymetry was collected on February 1, 2011, in the Sacramento River from the confluence of the Feather River to Knights Landing. The standard deviations represent one component of bathymetric uncertainty in the final digital elevation model (DEM), which is also available in this data release. The bathymetry data were collected by the USGS Pacific Coastal and Marine Science Center (PCMSC) team with collaboration and funding from the U.S. Army Corps of Engineers. This project used interferometric sidescan sonar to characterize the riverbed and channel banks along a 12 mile reach of the Sacramento River near the town of Knights Landing, California (River Mile 79 through River Mile 91) to aid in the understanding of fish response to the creation of safe habitat associated with levee restoration efforts in two 1.5 mile reaches of the Sacramento River between River Mile 80 and 86.

This part of the data release presents acoustic backscatter data collected on February 1, 2011, in the Sacramento River from the confluence of the Feather River to Knights Landing. The data were collected by the USGS Pacific Coastal and Marine Science Center (PCMSC) team with collaboration and funding from the U.S. Army Corp of Engineers. This project used interferometric sidescan sonar to characterize the riverbed and channel banks along a 12 mile reach of the Sacramento River, California (River Mile 79 through River Mile 91) to aid in the understanding of fish response to the creation of safe habitat associated with levee restoration efforts in two 1.5 mile reaches of the Sacramento River between River Mile 80 and 86.

This part of the data release presents a digital elevation model (DEM) created from bathymetry data collected on February 1, 2011, in the Sacramento River from the confluence of the Feather River to Knights Landing. The data were collected by the USGS Pacific Coastal and Marine Science Center (PCMSC) team with collaboration and funding from the U.S. Army Corps of Engineers. This project used interferometric sidescan sonar to characterize the riverbed and channel banks along a 12 mile reach of the Sacramento River, California (River Mile 79 through River Mile 91) to aid in the understanding of fish response to the creation of safe habitat associated with levee restoration efforts in two 1.5 mile reaches of the Sacramento River between River Mile 80 and 86.

This portion of the data release presents fish abundance data from samples collected in the Elwha River estuary, Washington, in 2006, 2007, 2013, and 2014 (no associated USGS Field Activities numbers because data were collected predominantly by biologists from the Lower Elwha Klallam Tribe). We used the Puget Sound beach seining protocol (Simenstad and others, 1991) to sample fish populations in the Elwha River estuary complex. The beach seine was 38 m long x 2 m deep, with a 2 m x 2 m bag in the center of the net; mesh size was 3.18 mm, 6.35 mm, and 31.75 mm, for the bag, center panel, and wings, respectively. The seine net was deployed from bank to bank by a small skiff and then pulled on shore. The number of seines conducted each month varied based on estuary conditions and staff availability. Captured fish were quickly transferred to 20-liter plastic buckets filled with aerated estuary water, individually identified, counted, measured, and released at the point of capture. The locations of seines were determined with a hand-held global positioning system (GPS). Fish abundance is reported as catch per unit effort (CPUE), calculated as the total number of each fish species caught in all seines at each site and date, divided by the number of seines conducted. Fish abundance data are provided in a comma-delimited spreadsheet (.csv).

This portion of the data release presents fish diet data from Chinook and coho salmon collected in the Elwha River estuary, Washington, in 2006, 2007, 2013, and 2014 (there are no associated USGS Field Activities numbers because data were collected predominantly by biologists from the Lower Elwha Klallam Tribe). Fish were collected using a beach seine at six locations throughout the estuary. Fish were transferred to buckets containing aerated ambient water and kept cool until handling. We anesthetized fish in a diluted solution of tricaine methanesulfonate (MS-222) to count, identify, and measure fork length (FL) to the nearest mm and weight to the nearest 0.1 g. After recovery from anesthesia, all fish were released at the point of capture. Stomach contents from a sub-sample of Chinook and coho were extracted via non-lethal gastric lavage and preserved in ethanol. When possible, stomach contents from ten individuals of each species between 55–199 mm fork length were collected at each site during each sampling event. Fish with no regurgitated prey were recorded as empty stomachs. Fish diet samples were sent to a professional taxonomist for processing and identification to the lowest practical taxonomic level. Aquatic taxa were typically identified to the genus or species level and terrestrial taxa to family or genus. Some less-common taxa or partially-digested prey items were identified to Order or Class. The locations of samples were determined with a hand-held global positioning system. Fish diet data are provided in a comma-delimited spreadsheet.

This portion of the data release presents terrestrial invertebrate abundance data from samples collected in emergent and shrub vegetation along the edge of the Elwha River estuary, Washington, in 2007 and 2013 (no associated USGS Field Activities numbers because data were collected predominantly by biologists from the Lower Elwha Klallam Tribe). We deployed terrestrial insect fallout traps at ten locations in the east estuary, five replicates each in shrub and emergent (littoral) vegetation habitats. Clear, rectangular traps (2,400 cm2 in 2007 and 3,526 cm2 in 2013) were filled with 5 cm of filtered soapy water and deployed for 72 hours. Invertebrate counts from 2013 were standardized to the 2007 bin size to account for the different area of the fallout traps between years. Samples were filtered through a funnel sieve and stored in 70 percent ethanol until processing. Invertebrates were identified to genera when possible. However, taxonomic resolution was not consistent across species so we grouped data by Order for our analyses (unless otherwise noted in the attributes). The locations of samples were determined with a hand-held global positioning system (GPS). Terrestrial invertebrate abundance data are provided in a comma-delimited spreadsheet (.csv).

This portion of the data release presents water column dissolved nutrient concentration data and water quality parameters from samples collected in the Elwha River estuary, Washington, in 2006, 2007, 2013, and 2014 (USGS Field Activities L-15-13-PS, L-24-13-PS, T-R5-13-PS, T-R6-13-PS, T-RA-14-PS, 2014-614-FA, 2014-628-FA, 2014-633-FA, 2014-666-FA). Water column samples were collected by hand in acid-washed opaque bottles from multiple locations. Water quality was measured using a handheld Hydolab Data Sonde 4a. The locations of water sample collections were determined with a hand-held global positioning system (GPS). The water samples were filtered through GF/F filters immediately after collection. The filtrate was collected in scintillation vials and frozen until analysis at either the University of Washington marine chemistry lab (2006 and 2007 samples) or the University of California Santa Barbara Marine Science Institute analytical lab (2013 and 2014 samples). Nutrient concentration and water quality data are provided in a comma-delimited spreadsheet (.csv).

This data release provides seafloor-characteristics point data across the Gulf of Alaska, as digitized directly from National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS) smooth sheets published from 1892 to 2001, and archived at the National Geophysics Data Center (NGDC). Geo-rectification and digitization methods were adapted from Zimmermann and Benson (2013). Each location includes information for the smooth sheet number (H#####), a unique site number location, latitude, longitude, collection date, seafloor notation, and the translation of the notation. Unique site numbers were assigned randomly to each notation on a smooth sheet, starting at “_0”. Examples of seafloor notations include: rk (= rock); bu C (= blue clay); hrd (= hard); fne S (= fine sand); Co (= coral) or similar codes; the full code key is given in the Department of Commerce and Department of Defense Chart 1 (2013). In some cases, a diagrammatic indication of the seafloor character is used on the smooth sheet, such as a “*”. During digitization, the corresponding value given in “Chart 1” is assigned to the location; in this case, “*” denotes “rk” or “rock”. Distribution of NOS seafloor-characteristics data across the Gulf of Alaska varies widely: nearer the shoreline, data are more densely distributed; on the mid and outer continental shelf, data are more sparsely spaced. The cited locations of the points were adjusted as necessary in GIS to match the location on the geo-rectified smooth sheet in GIS as projected in North American Datum of 1983. NOAA has published the companion regional bathymetric data and its derivatives and sediment characteristics data for Cook Inlet and areas of the Aleutian Islands at http://www.afsc.noaa.gov/RACE/groundfish/bathymetry/. The project was funded through the USGS Coastal and Marine Geology Program, NOAA National Marine Fisheries Service, Alaska Fisheries Science Center, and Alaska Fisheries Science Center Interagency Agreement AKC-119 (May 2012). References: Zimmermann, M., and Benson, J., 2013, Smooth sheets: How to work with them in a GIS to derive bathymetry, features and substrates: U.S. Department of Commerce, NOAA Tech. Memo. NMFS-AFSC-249, 52 p., available at http://www.afsc.noaa.gov/Publications/AFSC-TM/NOAA-TM-AFSC-249.pdf. Department of Commerce, National Oceanic and Atmospheric Administration and Department of Defense, National Geospatial-Intelligence Agency, 2013, U.S. Chart No. 1: Symbols, abbreviations and terms used on paper and electronic navigational charts, 12th edition, 132 p., available at http://www.nauticalcharts.noaa.gov/mcd/chartno1.htm.

This table lists the NOS smooth sheets included in the associated shapefile (GulfofAlaskaDigitizationProject_NOSSeafloorCharacter.zip; N = 329, plus insets), the number of samples for each smooth sheet, the year of collection (1892 to 2001), and the smooth sheet scale (from 1:2,000 to 1:600,000). Smooth sheets are available through the National Geophysics Data Center’s online data portal (NDGC, http://www.ngdc.noaa.gov).

This part of the data release includes 10-m resolution multibeam acoustic-backscatter data collected in 2016 in Catalina Basin, southern California. The data are presented as a TIFF file. In February 2016 the University of Washington in cooperation with the U.S. Geological Survey, Pacific Coastal and Marine Science Center (USGS, PCMSC) collected multibeam bathymetry and acoustic backscatter data in Catalina Basin aboard the University of Washington's Research Vessel Thomas G. Thompson. Data were collected using a Kongsberg EM300 multibeam echosounder hull-mounted to the 274-foot R/V Thomas G. Thompson. The USGS, PCMSC processed these data and produced a series of bathymetric surfaces and acoustic-backscatter images for scientific research purposes.

This part of the data release includes 10-m resolution multibeam-bathymetry data collected in 2016 in Catalina Basin, southern California. The data are presented as a TIFF image. In February 2016 the University of Washington in cooperation with the U.S. Geological Survey, Pacific Coastal and Marine Science Center (USGS, PCMSC) collected multibeam bathymetry and acoustic backscatter data in Catalina Basin aboard the University of Washington's Research Vessel Thomas G. Thompson. Data were collected using a Kongsberg EM300 multibeam echosounder hull-mounted to the 274-foot R/V Thomas G. Thompson. The USGS, PCMSC processed these data and produced a series of bathymetric surfaces and acoustic-backscatter images for scientific research purposes.

This part of the data release includes 10-m resolution merged multibeam-bathymetry data of Catalina Basin and northern Gulf of Santa Catalina. The data are presented as a TIFF file. In February 2016 the University of Washington in cooperation with the U.S. Geological Survey, Pacific Coastal and Marine Science Center (USGS, PCMSC) collected multibeam bathymetry and acoustic backscatter data in Catalina Basin aboard the University of Washington's Research Vessel Thomas G. Thompson. Data were collected using a Kongsberg EM300 multibeam echosounder hull-mounted to the 274-foot R/V Thomas G. Thompson. The USGS, PCMSC processed these data and produced a series of bathymetric surfaces and acoustic backscatter images for scientific research purposes. A 10-m bathymetric surface produced from this work (available in this report) was merged with re-processed 10-m resolution multibeam bathymetry data collected in the Gulf of Santa Catalina in 2013 by Scripps Institution of Oceanography and processed by USGS, PCMSC (available at, https://pubs.usgs.gov/sim/3324/). These data can be used to assess the hazards posed by offshore faults, submarine landslides, and tsunamis as well as map sediment transport pathways and sedimentary sinks.

This part of the data release includes 25-m resolution merged multibeam-bathymetry data of the northern portion of the Southern California Continental Borderland. The data are presented as a TIFF file. In February 2016 the University of Washington in cooperation with the U.S. Geological Survey, Pacific Coastal and Marine Science Center (USGS, PCMSC) collected multibeam bathymetry and acoustic backscatter data in Catalina Basin aboard the University of Washington's Research Vessel Thomas G. Thompson. Data were collected using a Kongsberg EM300 multibeam echosounder hull-mounted to the 274-foot R/V Thomas G. Thompson. The USGS, PCMSC processed these data and produced a series of bathymetric surfaces and acoustic backscatter images for scientific research purposes. A 25-m bathymetric surface produced from this work was merged with publically available multibeam bathymetry data, as well as 2015, 2016, and 2017 multibeam bathymetry data collected in the continental borderland region by the Ocean Exploration Trust's Nautilus Exploration Program. The USGS, PCMSC processed the survey line files received from the Nautilus Exploration Program to include in the overall merged 25-m multibeam bathymetry surface of the northern portion of the Southern California Continental Borderland region that is available in this data release. These data can be used to assess the hazards posed by offshore faults, submarine landslides, and tsunamis as well as map sediment transport pathways and sedimentary sinks.

This part of the data release includes graphical representation (figures) of data of sediment cores collected in 2014 in Monterey Canyon. It is one of five files included in this U.S. Geological Survey data release that include data from a set of sediment cores acquired from the continental slope, north of Monterey Canyon, offshore central California. Vibracores and push cores were collected with the Monterey Bay Aquarium Research Institute’s (MBARI’s) remotely operated vehicle (ROV) Doc Ricketts in 2014 (cruise ID 2014-615-FA). One spreadsheet (NorthernFlankMontereyCanyonCores_Info.xlsx) contains core name, location, and length. One spreadsheet (NorthernFlankMontereyCanyonCores_MSCLdata.xlsx) contains Multi-Sensor Core Logger P-wave velocity and gamma-ray density whole-core logs of vibracores. One zipped folder of .bmp files (NorthernFlankMontereyCanyonCores_Photos.zip) contains continuous core photographs of the archive half of each vibracore. One spreadsheet (NorthernFlankMontereyCanyonCores_Radiocarbon.xlsx) contains radiocarbon sample information, results, and calibrated ages. One .pdf file (NorthernFlankMontereyCanyonCores_Figures.pdf) contains combined displays of data for each vibracore, including graphic diagram descriptive logs. This particular metadata file describes the information contained in the file NorthernFlankMontereyCanyon_Figures.pdf. All vibracores are archived by the U.S. Geological Survey Pacific Coastal and Marine Science Center. Other remaining core material, if available, is archived at MBARI.

This part of the data release is a spreadsheet including the name, location, and length of sediment cores collected in 2014 in Monterey Canyon. It is one of five files in this U.S. Geological Survey data release that include data from a set of sediment cores acquired from the continental slope, north of Monterey Canyon, offshore central California. Vibracores and push cores were collected with the Monterey Bay Aquarium Research Institute’s (MBARI’s) remotely operated vehicle (ROV) Doc Ricketts in 2014 (USGS cruise ID 2014-615-FA). One spreadsheet (NorthernFlankMontereyCanyonCores_Info.xlsx) contains core name, location, and length. One spreadsheet (NorthernFlankMontereyCanyonCores_MSCLdata.xlsx) contains Multi-Sensor Core Logger P-wave velocity and gamma-ray density whole-core logs of vibracores. One zipped folder of .bmp files (NorthernFlankMontereyCanyonCores_Photos.zip) contains continuous core photographs of the archive half of each vibracore. One spreadsheet (NorthernFlankMontereyCanyonCores_Radiocarbon.xlsx) contains radiocarbon sample information, results, and calibrated ages. One .pdf file (NorthernFlankMontereyCanyonCores_Figures.pdf) contains combined displays of data for each vibracore, including graphic diagram descriptive logs. This particular metadata file describes the information contained in the file NorthernFlankMontereyCanyonCores_Info.xlsx. All vibracores are archived by the U.S. Geological Survey Pacific Coastal and Marine Science Center. Other remaining core material, if available, is archived at MBARI.

This part of the data release includes Multi-Sensor Core Logger (MSCL) P-wave velocity and gamma-ray density whole-core logs of sediment cores collected in 2014 from the northern flank of Monterey Canyon, offshore California. It is one of five files in this U.S. Geological Survey data release that include data from a set of sediment cores acquired from the continental slope, north of Monterey Canyon, offshore central California. Vibracores and push cores were collected with the Monterey Bay Aquarium Research Institute’s (MBARI’s) remotely operated vehicle (ROV) Doc Ricketts in 2014 (USGS cruise ID 2014-615-FA). One spreadsheet (NorthernFlankMontereyCanyonCores_Info.xlsx) contains core name, location, and length. One spreadsheet (NorthernFlankMontereyCanyonCores_MSCLdata.xlsx) contains Multi-Sensor Core Logger P-wave velocity and gamma-ray density whole-core logs of vibracores. One zipped folder of .bmp files (NorthernFlankMontereyCanyonCores_Photos.zip) contains continuous core photographs of the archive half of each vibracore. One spreadsheet (NorthernFlankMontereyCanyonCores_Radiocarbon.xlsx) contains radiocarbon sample information, results, and calibrated ages. One .pdf file (NorthernFlankMontereyCanyonCores_Figures.pdf) contains combined displays of data for each core, including graphic diagram descriptive logs. This particular metadata file describes the information contained in the file NorthernFlankMontereyCanyonCores_MSCL.xlsx. All vibracores are archived by the U.S. Geological Survey Pacific Coastal and Marine Science Center. Other remaining core material, if available, is archived at MBARI.

This part of the data release includes continuous core photographs in bmp format of sediment cores collected in 2014 from the northern flank of Monterey Canyon, offshore California. It is one of five files in this U.S. Geological Survey data release that include data from a set of sediment cores acquired from the continental slope, north of Monterey Canyon, offshore central California. Vibracores and push cores were collected with the Monterey Bay Aquarium Research Institute’s (MBARI’s) remotely operated vehicle (ROV) Doc Ricketts in 2014 (USGS cruise ID 2014-615-FA). One spreadsheet (NorthernFlankMontereyCanyonCores_Info.xlsx) contains core name, location, and length. One spreadsheet (NorthernFlankMontereyCanyonCores_MSCLdata.xlsx) contains Multi-Sensor Core Logger P-wave velocity and gamma-ray density whole-core logs of vibracores. One zipped folder of .bmp files (NorthernFlankMontereyCanyonCores_Photos.zip) contains continuous core photographs of the archive half of each vibracore. One spreadsheet (NorthernFlankMontereyCanyonCores_Radiocarbon.xlsx) contains radiocarbon sample information, results, and calibrated ages. One .pdf file (NorthernFlankMontereyCanyonCores_Figures.pdf) contains combined displays of data for each vibracore, including graphic diagram descriptive logs. This particular metadata file describes the information contained in the file NorthernFlankMontereyCanyonCores_Photos. All vibracores are archived by the U.S. Geological Survey Pacific Coastal and Marine Science Center. Other remaining core material, if available, is archived at MBARI.

This part of the data release is a spreadsheet including radiocarbon sample information and calibrated ages of sediment cores collected in 2014 from the northern flank of Monterey Canyon, offshore California. It is one of five files in this U.S. Geological Survey data release that include data from a set of sediment cores acquired from the continental slope, north of Monterey Canyon, offshore central California. Vibracores and push cores were collected with the Monterey Bay Aquarium Research Institute’s (MBARI’s) remotely operated vehicle (ROV) Doc Ricketts in 2014 (USGS cruise ID 2014-615-FA). One spreadsheet (NorthernFlankMontereyCanyonCores_Info.xlsx) contains core name, location, and length. One spreadsheet (NorthernFlankMontereyCanyonCores_MSCLdata.xlsx) contains Multi-Sensor Core Logger P-wave velocity and gamma-ray density whole-core logs of vibracores. One zipped folder of .bmp files (NorthernFlankMontereyCanyonCores_Photos.zip) contains continuous core photographs of the archive half of each vibracore. One spreadsheet (NorthernFlankMontereyCanyonCores_Radiocarbon.xlsx) contains radiocarbon sample information, results, and calibrated ages. One .pdf file (NorthernFlankMontereyCanyonCores_Figures.pdf) contains combined displays of data for each vibracore, including graphic diagram descriptive logs. This particular metadata file describes the information contained in the file NorthernFlankMontereyCanyonCores_Radiocarbon.xlsx. All vibracores are archived by the U.S. Geological Survey Pacific Coastal and Marine Science Center. Other remaining core material, if available, is archived at MBARI.

This data release contains high-resolution multichannel seismic (MCS) reflection data collected in August of 2016 along the southeast Alaska continental margin. Structure perpendicular MCS profiles were collected along the Queen Charlotte-Fairweather fault. The data were collected aboard the R/V Norseman using a Delta sparker sound source and recorded on a 64-channel digital streamer. Subbottom acoustic penetration spans up to several hundreds of meters, and is variable by location.

This portion of the data release contains image mosaics generated using digitized 1:24K natural color photographs collected in June 2000 by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS). These four image mosaics have 1.0 meter-per-pixel resolution, and intermittently cover approximately 53 km (33 mi) of shallow, coastal waters along the west, Kona coast, of the island of Hawai'i, including (from north to south) the Kawaihae, Waikoloa, Kukio, and Kailua-Kona areas. Each digital image mosaic area is downloadable as a separate zip file (area_1m.zip) that contains two versions of the image mosaic--one with and one without a lidar bathymetry shaded-relief image digitally combined with the aerial photography mosaic results. The shaded-relief image was derived using airborne SHOALS (Scanning Hydrographic Operational Lidar Survey) lidar (LIght Detection And Ranging) data collected for the U.S. Geological Survey (USGS) by the U.S. Army Corp of Engineers (USACE) in April 1999. Also included in each zip file is a lower-resolution 'browse' graphic of each image mosaic and associated metadata.

This portion of the data release contains an image mosaic generated using digitized 1:35K natural color photographs collected in September 1993 by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS) of the Napili-Honokowai area along the northwest coast of Maui. The area is downloadable as a zip file (napili_honokowai_1m.zip) and includes a high-resolution (1.0 meter per pixel) digital image mosaic, as well as a lower-resolution 'browse' image and associated metadata.

This portion of the data release contains digital image mosaics along the southeast coast of O'ahu. Digital mosaics at 1-foot (0.3048-meter) resolution, including the areas of Waikiki, Diamond Head, Wai'alae, Maunalua Bay, and Portlock, were generated from 1:10K aerial photography and are presented in one zip file (oahu_1ft.zip) that also contains lower-resolution 'browse' graphics of each image mosaic area, as well as associated metadata. All of the digital image areas (from Waikiki to Portlock) were combined into one large digital mosaic at 1-meter resolution, which is presented in another zip file (oahu_1m.zip) that includes a 'browse' graphic of the image mosaic area and associated metadata. The 1-meter resolution digital image mosaic was also combined with lidar bathymetry data to create a shaded-relief image, which is presented in a third zip file (oahu_1m_shaded.zip), along with a 'browse' graphic of the image mosaic area and associated metadata.

This data release contains high-resolution seismic reflection data collected in August of 2015 to explore marine geologic hazards of inland waterways of southeastern Alaska. Sub-bottom profiles were acquired in the inland waters between Glacier Bay and Juneau, including Cross Sound and Chatham Strait. High-resolution seismic-reflection profiles were acquired to assess evidence for active seabed faulting and submarine landslide hazards. The data were collected aboard the US Geological Survey R/V Alaskan Gyre. The seismic-reflection data were acquired using a tow-fish Edgetech 512 chirp subbottom profiler. Subbottom acoustic penetration spans up to several tens of meters, and is variable by location. This data release contains processed digital SEG-Y. This data release will be updated as subsequent lines of data from this field activity are published.

This data release contains high-resolution multichannel seismic (MCS) reflection data collected in August of 2015 to explore marine geologic hazards of inland waterways of southeastern Alaska. Sub-bottom profiles were acquired in the inland waters between Glacier Bay and Juneau, including Cross Sound and Chatham Strait. High-resolution seismic-reflection profiles were acquired to assess evidence for active seabed faulting and submarine landslide hazards. The data were collected aboard the US Geological Survey R/V Alaskan Gyre. The seismic-reflection data were acquired using a 500-Joule minisparker source and a 48-channel Geometrics GeoEel digital streamer. Subbottom acoustic penetration spans up to several hundreds of meters, and is variable by location. This data release contains CMP sorted digital data in SEG-Y format. This data release will be updated as subsequent lines of data from this field activity are published.

This data release presents data for 5-m resolution acoustic-backscatter data of the northern Channel Islands region, southern California. In 2004 the U.S. Geological Survey, Pacific Coastal and Marine Science Center collected multibeam-bathymetry and acoustic-backscatter data in the northern Channel Islands region, southern California. The region was mapped aboard the R/V Ewing using a Kongsberg Simrad EM-1002 multibeam echosounder. These data were previously published on-line at http://pubs.usgs.gov/of/2005/1153/. In this data release the data have been reprocessed to a finer spatial resolution (5-m versus 15-m) using more modern processing techniques. Due to the large file sizes the entire survey area is provided as two ASCIIRaster files (one for the north portion of the study area and another for the south). A few survey line files in the northern region did not process and are missing from the ASCIIRaster file.

This data release presents data for 5-m resolution multibeam-bathymetry data of the northern Channel Islands region, southern California. In 2004 The U.S. Geological Survey, Pacific Coastal and Marine Science Center collected multibeam-bathymetry and acoustic-backscatter data in the northern Channel Islands region, southern California. The region was mapped aboard the R/V Ewing using a Kongsberg Simrad EM-1002 multibeam echosounder. These data were previously published on-line at http://pubs.usgs.gov/of/2005/1153/. In this data release the data have been reprocessed to a finer spatial resolution (5-m versus 15-m) using more modern processing techniques. Due to the large file sizes the entire survey area is provided as two ASCIIRaster files (one for the north portion of the study area and another for the south).

This part of the data release presents a digital elevation model (DEM) derived from bathymetry and topography data of the Elwha River delta collected in January 2015. Two dams on the Elwha River, Washington State, USA trapped over 20 million m3 of sediment, reducing downstream sediment fluxes and contributing to erosion of the river's coastal delta. The removal of the Elwha and Glines Canyon dams between 2011 and 2014 induced massive increases in river sediment supply and provided an unprecedented opportunity to examine the response of a delta system to changes in sediment supply. The U.S. Geological Survey developed an integrated research program aimed at understanding the ecosystem responses following dam removal that included regular monitoring of coastal and nearshore bathymetry and topography. As part of this monitoring program, the USGS conducted a bathymetric and topographic survey in the Strait of Juan de Fuca on the Elwha River delta, Washington (USGS Field Activity Number 2015-605-FA). Bathymetry data were collected using two personal watercraft (PWCs) and a kayak, each equipped with single beam echosounders and survey-grade global navigation satellite systems (GNSS). Topography data were collected on foot with GNSS receivers mounted on backpacks. DEM surfaces were produced from all available elevation data using linear interpolation.

This portion of the data release presents sediment grain-size data from samples collected on the Elwha River delta, Washington, in January 2015 (USGS Field Activity 2015-605-FA). Surface sediment was collected from 61 locations using a small ponar, or 'grab', sampler from the R/V Frontier in depths between about 1 and 17 m around the delta. A handheld global satellite navigation system (GNSS) receiver was used to determine the locations of sediment samples. The grain-size distributions of samples were determined using standard techniques developed by the USGS Pacific Coastal and Marine Science Center sediment lab. The grain-size data are provided in a comma-delimited spreadsheet (.csv).

This part of the data release presents bathymetry data from the Elwha River delta collected in January 2015 using a kayak. The kayak was equipped with a single-beam echosounder and a survey-grade global navigation satellite system (GNSS) receiver.

This part of the data release presents bathymetry data from the Elwha River delta collected in January 2015 using two personal watercraft (PWCs). The PWCs were equipped with single-beam echosounders and survey-grade global navigation satellite system (GNSS) receivers.

This part of the data release presents topography data from the Elwha River delta collected in January 2015. Topography data were collected on foot with global navigation satellite system (GNSS) receivers mounted on backpacks.

Sediment cores were collected from San Pablo Bay, in the Sacramento-San Joaquin Delta in California by the U.S. Geological Survey Pacific Coastal and Marine Science Center (PCMSC) during multiple surveys from 2011 to 2012. The cores were analyzed for grain-size distributions at the PCMSC sediment lab.

The U.S. Geological Survey Pacific Coastal and Marine Science Center collected data to investigate sediment dynamics in the shallows of San Pablo Bay in two deployments: February to March 2011 (ITX11) and May to June 2012 (ITX12). This data release includes time-series data and grain-size distributions from sediment grabs collected during the deployments. During each deployment, time series of current velocity, water depth, and turbidity were collected at several stations in the shallows, and one station in the channel. Velocity and depth (pressure) were collected at high frequency (10 Hz) to allow calculation of wave parameters and turbulence statistics.

This part of the data release contains high-resolution acoustic-backscatter data collected by the U.S. Geological Survey (USGS) Pacific Coastal and Marine Science Center at three study locations in the Sacramento-San Joaquin Delta, California. Data were collected in Lindsey Slough in April 2017, Middle River in March 2018, and Mokelumne River in March 2018, using an interferometric bathymetric sidescan sonar systems mounted to the USGS R/V Parke Snavely. Data are provided in 1-m resolution GeoTIFF formats. These data were collected as part of a study of the effects of invasive aquatic vegetation on sediment transport in the Sacramento-San Joaquin Delta.

Bed sediment samples were collected in Lindsey Slough in April 2017, and Middle River and the Mokelumne River in March 2018, to analyze for sediment properties, including bulk density, particle size distribution, and percent organic carbon. Sediment samples were collected within the vegetation with push corers deployed from a small vessel, and in the unvegetated channel with a Gomex box corer, which was subsampled with three push cores per Gomex core. Data are provided in a comma-delimited values spreadsheet. These data were collected as part of a cooperative project, with the USGS California Water Science Center and the California Department of Fish and Wildlife, on the effects of invasive aquatic vegetation on sediment transport in the Sacramento-San Joaquin Delta.

Hydrodynamic and sediment transport time-series data, including water depth, velocity, turbidity, conductivity, and temperature, were collected by the U.S. Geological Survey (USGS) Pacific Coastal and Marine Science Center at three locations in the Sacramento-San Joaquin Delta. Data were collected in Lindsey Slough in April 2017, and Middle River and the Mokelumne River in March 2018. Data files are grouped by location. At each of the three sites, data were collected at stations outside and within patches of vegetation, to determine how submerged invasive vegetation influences tidal currents and suspended-sediment concentration. The Table below shows the data types collected at each station, and classifies stations as Vegetated (V) or Unvegetated (U). These data were collected as part of a study of the effects of invasive aquatic vegetation on sediment transport in the Sacramento-San Joaquin Delta. At times, vegetation caught on instrument frames (both within and outside patches) compromised data quality. Users are advised to check data quality carefully, and to check metadata and instrument information, as individual instrument deployment times vary.

This part of the data release contains high-resolution swath bathymetry data collected by the U.S. Geological Survey (USGS) Pacific Coastal and Marine Science Center at three locations in the Sacramento-San Joaquin Delta. Data were collected in Lindsey Slough in April 2017, Middle River in March 2018, and Mokelumne River in March 2018 using an interferometric bathymetric sidescan sonar systems mounted to the USGS R/V Parke Snavely. Data are provided in 1-m resolution GeoTIFF formats. These data were collected as part of a study on the effects of invasive aquatic vegetation on sediment transport in the Sacramento-San Joaquin Delta.

This data release presents eelgrass distributions and bathymetry data derived from acoustic surveys of Bellingham Bay, Washington. Survey operations were conducted between February 16 and February 21, 2019 (USGS Field Activity Number 2019-606-FA) by a team of scientists from the U.S. Geological Survey Pacific Coastal and Marine Science Center and Washington State Department of Ecology. Eelgrass and bathymetry data were collected from the R/V George Davidson equipped with a single-beam sonar system and global navigation satellite system (GNSS) receiver. The sonar system consisted of a Biosonics DT-X single-beam echosounder and 420 kHz transducer with a 6-degree beam angle. Depths from the echosounder were computed using sound velocity data measured using a YSI CastAway CTD during the survey. Positioning of the vessel was determined at 5 Hz using a Trimble R9s GNSS receiver and Trimble Zephyr Model 2 antenna operating in real time kinematic (RTK) mode. Differential corrections were transmitted by a cellular modem to the GNSS receiver on the survey vessel at 1-Hz from a GNSS continuously operating reference station operated by the Washington State Reference Network (WSRN; http://www.wsrn3.org/) located in the city of Bellingham (station BELI). Output from the GNSS and sonar systems were combined in real time by the Biosonics DT-X deck unit and output to a computer running HYPACK hydrographic survey software. Navigation information was displayed on a video monitor, allowing the vessel operator to navigate along predefined survey lines spaced at 25- to 100-m intervals alongshore at speeds of approximately 2 m/s. Acoustic backscatter data were analyzed using a custom graphical user interface (GUI) that implements a signal processing algorithm applied to each sonar sounding to extract the location of the bottom and presence of vegetation (Stevens and others, 2008 ). Individual acoustic returns along a survey line were grouped into packets of ten, and eelgrass percent cover was calculated as the fractional percent of acoustic returns that were classified as vegetated within each group, resulting in a estimate of percent cover every 4 to 5 m (depending on vessel speed). The positioning data from the bathymetric survey were postprocessed using Waypoint Grafnav to apply differential corrections with data recorded at the GNSS base station BELI and archived by the WSRN; these data superseded the original positions recorded in real time. The GUI was used to combine filtered sonar data with postprocessed positioning data and orthometric elevations relative to the NAVD88 vertical datum were computed using National Geodetic Survey Geoid12a offsets. The estimated vertical uncertainty of the bathymetric measurements ranged from 2.0 cm to 18.3 cm with a mean of 6.7 cm. Uncertainty in the vertical positions associated with pitch and roll of the survey vessel is unknown. The final point data are provided in a comma-separated text file and are projected in Cartesian coordinates using the Universal Transverse Mercator (UTM), Zone 10 north, meters coordinate system.

This metadata describes a digital elevation model (DEM) created from bathymetric and topographic data collected between 2004 and 2019 in the Cache Slough Complex (CSC), northern Sacramento-San Joaquin Delta, California. We merged the newly collected bathymetric and topographic data presented in this data release (DOI:10.5066/P9AQSRVH) with 2019 surveys by the California Department of Water Resources (DWR), 2017 USGS Sacramento Delta Lidar, and 2004 bathymetry data from the Army Corp of Engineers. Small gaps of missing data were filled with existing DWR/USGS Delta DEMs to produce a seamless DEM of the Cache Slough Complex with a grid resolution of 1 m. Remaining gaps in the DEM are areas where there is currently no available data.

This metadata describes a digital elevation model (DEM) created from bathymetric and topographic data collected between 2017 and 2019 in the Sacramento River Deep Water Ship Channel (DWSC), northern Sacramento-San Joaquin Delta, California. We merged the newly collected bathymetric and topographic data presented in this data release (DOI:10.5066/P9AQSRVH) with 2019 surveys by the California Department of Water Resources (DWR) and 2017 USGS Sacramento Delta Lidar, to produce a seamless digital elevation model of the DWSC at a grid resolution of 1 m.

Seamless unconfined groundwater heads for coastal California groundwater systems were modeled with homogeneous, steady-state MODFLOW simulations. The geographic extent examined was limited primarily to low-elevation (i.e. land surface less than approximately 10 m above mean sea level) areas. In areas where coastal elevations increase rapidly (e.g., bluff stretches), the model boundary was set approximately 1 kilometer inland of the present-day shoreline. Steady-state MODFLOW groundwater flow models were used to obtain detailed (10-meter-scale) predictions over large geographic scales (100s of kilometers) of groundwater heads for both current and future sea-level rise (SLR) scenarios (0 to 2 meters (m) in 0.25 m increments, 2.5 m, 3 m, and 5 m) using a range of horizontal hydraulic conductivity (Kh) scenarios (0.1, 1, and 10 m/day). For each SLR/Kh combination, results are provided for two marine boundary conditions, local mean sea level (LMSL) and mean higher-high water (MHHW), and two model versions. In the first model version, groundwater reaching the land surface is removed from the model, simulating loss via natural drainage. In the second model version, groundwater reaching the land surface is retained, simulating the worst-case "linear" response of groundwater head to sea-level rise. Modeled groundwater heads were then subtracted from high-resolution topographic digital elevation model (DEM) data to obtain the water table depths, which are represented as polygons for specific depth ranges in this dataset. Additional details about the groundwater model and data sources are outlined in Befus and others (2020) and in Groundwater_model_methods.pdf (available at https://www.sciencebase.gov/catalog/file/get/5b8ef008e4b0702d0e7ec72b?name=Groundwater_model_methods.pdf). Methods specific to groundwater head and water table depth products are outlined in Groundwater_head_and_water_table_depth_methods.pdf (available at https://www.sciencebase.gov/catalog/file/get/5bda1563e4b0b3fc5cec39b4?name=Groundwater_head _and_water_table_depth_methods.pdf). Methods specific to groundwater emergence and shoaling products are outlined in Groundwater_emergence_and_shoaling_methods.pdf (available at https://www.sciencebase.gov/catalog/file/get/5bd9f318e4b0b3fc5cec20ed?name=Groundwater_emergence_and_shoaling_methods.pdf). Please read the model details, data sources and methods summaries and inspect model output carefully. Data are complete for the information presented. Users should note that while the metadata Spatial Reference Information/UTM Zone Number in this document is 10, some files in southern California are in UTM Zone 11, as noted in the Format Specification for individual downloadable files. As a result users may need to modify the metadata for automated import and display of Zone 11 datafiles.

Seamless unconfined groundwater heads for coastal California groundwater systems were modeled with homogeneous, steady-state MODFLOW simulations. The geographic extent examined was limited primarily to low-elevation (i.e. land surface less than approximately 10 m above mean sea level) areas. In areas where coastal elevations increase rapidly (e.g., bluff stretches), the model boundary was set approximately 1 kilometer inland of the present-day shoreline. Steady-state MODFLOW groundwater flow models were used to obtain detailed (10-meter-scale) predictions over large geographic scales (100s of kilometers) of groundwater heads for both current and future sea-level rise (SLR) scenarios (0 to 2 meters (m) in 0.25 m increments, 2.5 m, 3 m, and 5 m) using a range of horizontal hydraulic conductivity (Kh) scenarios (0.1, 1, and 10 m/day). For each SLR/Kh combination, results are provided for two marine boundary conditions, local mean sea level (LMSL) and mean higher-high water (MHHW), and two model versions. In the first model version, groundwater reaching the land surface is removed from the model, simulating loss via natural drainage. In the second model version, groundwater reaching the land surface is retained, simulating the worst-case "linear" response of groundwater head to sea-level rise. Additional details about the groundwater model and data sources are outlined in Befus and others (2020) and in Groundwater_model_methods.pdf (available at https://www.sciencebase.gov/catalog/file/get/5b8ef008e4b0702d0e7ec72b?name=Groundwater_model_methods.pdf). Methods specific to groundwater head and water table depth products are outlined in Groundwater_head_and_water_table_depth_methods.pdf (available at https://www.sciencebase.gov/catalog/file/get/5bda1563e4b0b3fc5cec39b4?name=Groundwater_head _and_water_table_depth_methods.pdf). Please read the model details, data sources and methods summaries and inspect model output carefully. Data are complete for the information presented. Users should note that while the metadata Spatial Reference Information/UTM Zone Number in this document is 10, some files in southern California are in UTM Zone 11, as noted in the Format Specification for individual downloadable files. As a result users may need to modify the metadata for automated import and display of Zone 11 datafiles.

Seamless unconfined groundwater heads for coastal California groundwater systems were modeled with homogeneous, steady-state MODFLOW simulations. The geographic extent examined was limited primarily to low-elevation (i.e. land surface less than approximately 10 m above mean sea level) areas. In areas where coastal elevations increase rapidly (e.g., bluff stretches), the model boundary was set approximately 1 kilometer inland of the present-day shoreline. Steady-state MODFLOW groundwater flow models were used to obtain detailed (10-meter-scale) predictions over large geographic scales (100s of kilometers) of groundwater heads for both current and future sea-level rise (SLR) scenarios (0 to 2 meters (m) in 0.25 m increments, 2.5 m, 3 m, and 5 m) using a range of horizontal hydraulic conductivity (Kh) scenarios (0.1, 1, and 10 m/day). For each SLR/Kh combination, results are provided for two marine boundary conditions, local mean sea level (LMSL) and mean higher-high water (MHHW), and two model versions. In the first model version, groundwater reaching the land surface is removed from the model, simulating loss via natural drainage. In the second model version, groundwater reaching the land surface is retained, simulating the worst-case "linear" response of groundwater head to sea-level rise. Modeled groundwater heads were then subtracted from high-resolution topographic digital elevation model (DEM) data to obtain the water table depths. Additional details about the groundwater model and data sources are outlined in Befus and others (2020) and in Groundwater_model_methods.pdf (available at https://www.sciencebase.gov/catalog/file/get/5b8ef008e4b0702d0e7ec72b?name=Groundwater_model_methods.pdf). Methods specific to groundwater head and water table depth products are outlined in Groundwater_head_and_water_table_depth_methods.pdf (available at https://www.sciencebase.gov/catalog/file/get/5bda1563e4b0b3fc5cec39b4?name=Groundwater_head _and_water_table_depth_methods.pdf). Please read the model details, data sources and methods summaries, and inspect model output carefully. Data are complete for the information presented. Users should note that while the metadata Spatial Reference Information/UTM Zone Number in this document is 10, some files in southern California are in UTM Zone 11, as noted in the Format Specification for individual downloadable files. As a result users may need to modify the metadata for automated import and display of Zone 11 datafiles.

Transects of near-surface seawater properties were collected over the fringing reef off Makua, HI, on the north shore of Kauai using a Conductivity-Temperature-Depth (CTD) logger, either hand-carried or mounted to a kayak. The instrument returns temperature, salinity as a function of depth, and latitude/longitude.

Along-shore surface-based 2D electrical resistivity tomography (ERT) surveys were collected in the nearshore region of Makua, Kauai.

Satellite-tracked, DGPS-equipped Lagrangian surface-current drifter deployments were conducted over 6 days between 30 July and 4 August 2016 at various locations and stages of the tide over the coral reef off Makua, HI. The drifters internally logged their location every 1 minute, and they transmitted their positions to satellites every 5 minutes. A drogue was attached to the drifters at 1 m below sea level in order to track the currents at that depth.

Time-series data of water-surface elevation, wave height, water-column currents, temperature were acquired for 6 days off the north coast of the island of Kauai, Hawaii in support of a study on the coastal circulation patterns and groundwater input to the coral reefs of Makua.

This dataset contains spatial projections of coastal cliff retreat (and associated uncertainty) for future scenarios of sea-level rise (SLR) in Central California. Present-day cliff-edge positions used as the baseline for projections are also included. Projections were made using numerical models and field observations such as historical cliff retreat rate, nearshore slope, coastal cliff height, and mean annual wave power, as part of Coastal Storm Modeling System (CoSMoS). Read metadata and references carefully. Details: Cliff-retreat position projections and associated uncertainties are for scenarios of 0.25, 0.5, 0.75, 0.92, 1, 1.25, 1.5, 1.75, 2, 2.5, 3.0 and 5 meters of SLR. Projections were made at CoSMoS cross-shore transects (CST) spaced 100-200 m alongshore using a baseline sea-cliff edge from 2016 (included in the dataset). Within the zip file, there are two separate datasets available: 1) one that ignores coastal armoring, such as seawalls and revetments, and allows the cliff to retreat unimpeded (“Do Not Hold the Line”); and 2) another that assumes that current coastal armoring will be maintained and 100% effective at stopping future cliff erosion ("Hold the Line"). An ensemble of four numerical models synthesized from literature were used to make projections. All models relate breaking-wave height and period to cliff rock or unconsolidated sediment erosion. As sea level rises, waves break closer to the sea cliff, more wave energy impacts the cliffs, and cliff erosion rates accelerate. The final projections are a weighted average of all models (weighted by model performance), and the final uncertainties are proportional to 1) underlying uncertainties in the model input data, such as historical cliff retreat rates, and 2) the differences between individual model forecasts at each CST so that uncertainty is larger when the models do not agree. Uncertainty represents the 95% confidence level (two standard deviations about the mean projection). Model behavior also includes wave run-up and wave set-up that raises the water level during big-wave events. Please refer to Limber and others (2018) for more detailed information on the model and data sources.

This dataset contains projections of shoreline positions and uncertainty bands for future scenarios of sea-level rise. Projections were made using the Coastal Storm Modeling System - Coastal One-line Assimilated Simulation Tool (CoSMoS-COAST), a numerical model forced with global-to-local nested wave models and assimilated with lidar-derived shoreline vectors. Read metadata carefully. Details: Projections of shoreline position in the Central Coast of California are made for scenarios of 25, 50, 75, 92, 100, 125, 150, 175, 200, 250, 300 and 500 centimeters (cm) of SLR by the year 2100. SLR scenarios for 25, 50 and 75 cm are included in the National Research Council (NRC) excel and KMZ files. Four datasets are available for different management conditions: shorelines are allowed to retreat unimpeded past urban structures ("NO Hold the Line") or are limited to this urban boundary ("Hold the Line"), and shorelines are allowed to progress with projected increases in sediment ("Continued Nourishment") or with no projected increases ("No Nourishment"). Projections are made at CoSMoS Monitoring and Observation Points, which represent shore-normal transects spaced 100 m alongshore. The CoSMoS-COAST model solves a coupled set of partial differential equations that resembles conservation of sediment for the series of transects. The model is synthesized from several shoreline models in the scientific literature, which is described in more detail, along with the CoSMoS-Coast methodology, in Vitousek and others 2017. Significant uncertainty is associated with the process noise of the model and unresolved coastal processes. This makes estimation of uncertainty difficult. The uncertainty bands predicted here represent 95 percent confidence bands associated with the modeled shoreline fluctuations. Unresolved processes are not accounted for in the uncertainty bands and could lead to significantly more uncertainty than reported in these predictions.

This portion of the USGS data release presents bathymetry data collected during surveys performed in the Columbia River littoral cell, Washington and Oregon in 2014 (USGS Field Activity Number 2014-631-FA). Bathymetry data were collected using four personal watercraft (PWCs) equipped with single-beam sonar systems and global navigation satellite system (GNSS) receivers. The sonar systems consisted of an Odom Echotrac CV-100 single-beam echosounder and 200 kHz transducer with a 9° beam angle. Raw acoustic backscatter returns were digitized by the echosounder with a vertical resolution of 1.25 cm. Depths from the echosounders were computed using sound velocity profiles measured using a YSI CastAway CTD during the survey. Positioning of the survey vessels was determined at 5 to 10 Hz using Trimble R7 GNSS receivers. Output from the GNSS receivers and sonar systems were combined in real time on the PWC by a computer running HYPACK hydrographic survey software. Navigation information was displayed on a video monitor, allowing PWC operators to navigate along survey lines at speeds of 2–3 m/s. Survey-grade positions of the PWCs were achieved with a single-base station and differential post-processing. Positioning data from the GNSS receivers were post-processed using Waypoint Grafnav to apply differential corrections from a GNSS base station with known horizontal and vertical coordinates relative to the North American Datum of 1983. Orthometric elevations relative to the NAVD88 vertical datum were computed using National Geodetic Survey Geoid12a offsets. Bathymetric data were merged with post-processed positioning data and spurious soundings were removed using a custom Graphical User Interface (GUI) programmed with the computer program MATLAB. The average estimated vertical uncertainty of the bathymetric measurements is 10 cm. The final point data from the PWCs are provided in a comma-separated text file and are projected in cartesian coordinates using the Washington State Plane South, meters coordinate system.

This portion of the USGS data release presents topography data collected during surveys performed in the Columbia River littoral cell, Washington and Oregon, in 2014 (USGS Field Activity Number 2014-631-FA). Topographic profiles were collected by walking along survey lines with global navigation satellite system (GNSS) receivers mounted on backpacks. Prior to data collection, vertical distances between the GNSS antennas and the ground were measured using a tape measure. Hand-held data collectors were used to log raw data and display navigational information allowing surveyors to navigate survey lines spaced at 100- to 1,000-m intervals along the beach. Profiles were surveyed from the landward edge of the study area (either the base of a bluff, engineering structure, or just landward of the primary dune) over the beach foreshore, to wading depth on the same series of transects as nearshore bathymetric surveys that were conducted during the same time period. Additional topographic data were collected between survey lines in some areas with an all-terrain vehicle (ATV) equipped with a GNSS receiver to constrain the elevations and alongshore extent of major morphological features. During the 2014 survey, mechanical problems resulted in limited data collection with the ATV. Positioning data from the survey platforms were referenced to a GNSS base station with known horizontal and vertical coordinates relative to the North American Datum of 1983. Differential corrections from the GNSS base stations to the survey platforms were either applied in real-time with a VHF radio link, or post-processed using Trimble Business Center software. Orthometric elevations relative to the NAVD88 vertical datum were computed using National Geodetic Survey Geoid12a offsets. The average estimated vertical uncertainty of the topographic measurements is 4 cm. The final point data are provided in comma-separated text format and are projected in Cartesian coordinates using the Washington State Plane South, meters coordinate system.

This portion of the USGS data release presents bathymetry data collected during surveys performed in the Columbia River littoral cell, Washington and Oregon in 2015 (USGS Field Activity Number 2015-647-FA). Bathymetry data were collected using four personal watercraft (PWCs) equipped with single-beam sonar systems and global navigation satellite system (GNSS) receivers. The sonar systems consisted of an Odom Echotrac CV-100 single-beam echosounder and 200 kHz transducer with a 9 degree beam angle. Raw acoustic backscatter returns were digitized by the echosounder with a vertical resolution of 1.25 cm. Depths from the echosounders were computed using sound velocity profiles measured using a YSI CastAway CTD during the survey. Positioning of the survey vessels was determined at 5 to 10 Hz using Trimble R7 GNSS receivers. Output from the GNSS receivers and sonar systems were combined in real time on the PWC by a computer running HYPACK hydrographic survey software. Navigation information was displayed on a video monitor, allowing PWC operators to navigate along survey lines at speeds of 2 to 3 m/s. Survey-grade positions of the PWCs were achieved with a single-base station and differential post-processing. Positioning data from the GNSS receivers were post-processed using Waypoint Grafnav to apply differential corrections from a GNSS base station with known horizontal and vertical coordinates relative to the North American Datum of 1983. Orthometric elevations relative to the NAVD88 vertical datum were computed using National Geodetic Survey Geoid12a offsets. Bathymetric data were merged with post-processed positioning data and spurious soundings were removed using a custom Graphical User Interface (GUI) programmed with the computer program MATLAB. The average estimated vertical uncertainty of the bathymetric measurements is 10 cm. The final point data from the PWCs are provided in a comma-separated text file and are projected in cartesian coordinates using the Washington State Plane South, meters coordinate system.

This portion of the USGS data release presents topography data collected during surveys performed in the Columbia River littoral cell, Washington and Oregon, in 2015 (USGS Field Activity Number 2015-647-FA). Topographic profiles were collected by walking along survey lines with global navigation satellite system (GNSS) receivers mounted on backpacks. Prior to data collection, vertical distances between the GNSS antennas and the ground were measured using a tape measure. Hand-held data collectors were used to log raw data and display navigational information allowing surveyors to navigate survey lines spaced at 100- to 1000-m intervals along the beach. Profiles were surveyed from the landward edge of the study area (either the base of a bluff, engineering structure, or just landward of the primary dune) over the beach foreshore, to wading depth on the same series of transects as nearshore bathymetric surveys that were conducted during the same time period. Additional topographic data were collected between survey lines in some areas with an all-terrain vehicle (ATV) equipped with a GNSS receiver to constrain the elevations and alongshore extent of major morphological features. Positioning data from the survey platforms were referenced to a GNSS base station with known horizontal and vertical coordinates relative to the North American Datum of 1983. Differential corrections from the GNSS base stations to the survey platforms were either applied in real-time with a VHF radio link, or post-processed using Trimble Business Center software. Orthometric elevations relative to the NAVD88 vertical datum were computed using National Geodetic Survey Geoid12a offsets. The average estimated vertical uncertainty of the topographic measurements is 4 cm. The final point data are provided in comma-separated text format and are projected in Cartesian coordinates using the Washington State Plane South, meters coordinate system.

This portion of the USGS data release presents bathymetry data collected during surveys performed in the Columbia River littoral cell, Washington and Oregon in 2016 (USGS Field Activity Number 2016-663-FA). Bathymetry data were collected using four personal watercraft (PWCs) equipped with single-beam sonar systems and global navigation satellite system (GNSS) receivers. The sonar systems consisted of an Odom Echotrac CV-100 single-beam echosounder and 200 kHz transducer with a 9 degree beam angle. Raw acoustic backscatter returns were digitized by the echosounder with a vertical resolution of 1.25 cm. Depths from the echosounders were computed using sound velocity profiles measured using a YSI CastAway CTD during the survey. Positioning of the survey vessels was determined at 5 to 10 Hz using Trimble R7 GNSS receivers. Output from the GNSS receivers and sonar systems were combined in real time on the PWC by a computer running HYPACK hydrographic survey software. Navigation information was displayed on a video monitor, allowing PWC operators to navigate along survey lines at speeds of 2 to 3 m/s. Survey-grade positions of the PWCs were achieved with a single-base station and differential post-processing. Positioning data from the GNSS receivers were post-processed using Waypoint Grafnav to apply differential corrections from a GNSS base station with known horizontal and vertical coordinates relative to the North American Datum of 1983. Orthometric elevations relative to the NAVD88 vertical datum were computed using National Geodetic Survey Geoid12a offsets. Bathymetric data were merged with post-processed positioning data and spurious soundings were removed using a custom Graphical User Interface (GUI) programmed with the computer program MATLAB. The average estimated vertical uncertainty of the bathymetric measurements is 10 cm. The final point data from the PWCs are provided in a comma-separated text file and are projected in cartesian coordinates using the Washington State Plane South, meters coordinate system.

This portion of the USGS data release presents topography data collected during surveys performed in the Columbia River littoral cell, Washington and Oregon, in 2016 (USGS Field Activity Number 2016-663-FA). Topographic profiles were collected by walking along survey lines with global navigation satellite system (GNSS) receivers mounted on backpacks. Prior to data collection, vertical distances between the GNSS antennas and the ground were measured using a tape measure. Hand-held data collectors were used to log raw data and display navigational information allowing surveyors to navigate survey lines spaced at 100- to 1000-m intervals along the beach. Profiles were surveyed from the landward edge of the study area (either the base of a bluff, engineering structure, or just landward of the primary dune) over the beach foreshore, to wading depth on the same series of transects as nearshore bathymetric surveys that were conducted during the same time period. Additional topographic data were collected between survey lines in some areas with an all-terrain vehicle (ATV) equipped with a GNSS receiver to constrain the elevations and alongshore extent of major morphological features. Positioning data from the survey platforms were referenced to a GNSS base station with known horizontal and vertical coordinates relative to the North American Datum of 1983. Differential corrections from the GNSS base stations to the survey platforms were either applied in real-time with a VHF radio link, or post-processed using Trimble Business Center software. Orthometric elevations relative to the NAVD88 vertical datum were computed using National Geodetic Survey Geoid12a offsets. The average estimated vertical uncertainty of the topographic measurements is 4 cm. The final point data are provided in comma-separated text format and are projected in Cartesian coordinates using the Washington State Plane South, meters coordinate system.

This portion of the USGS data release presents bathymetry data collected during surveys performed in the Columbia River littoral cell, Washington and Oregon in 2017 (USGS Field Activity Number 2017-666-FA). Bathymetry data were collected using four personal watercraft (PWCs) equipped with single-beam sonar systems and global navigation satellite system (GNSS) receivers. The sonar systems consisted of an Odom Echotrac CV-100 single-beam echosounder and 200 kHz transducer with a 9 degree beam angle. Raw acoustic backscatter returns were digitized by the echosounder with a vertical resolution of 1.25 cm. Depths from the echosounders were computed using sound velocity profiles measured using a YSI CastAway CTD during the survey. Positioning of the survey vessels was determined at 5 to 10 Hz using Trimble R7 GNSS receivers. Output from the GNSS receivers and sonar systems were combined in real time on the PWC by a computer running HYPACK hydrographic survey software. Navigation information was displayed on a video monitor, allowing PWC operators to navigate along survey lines at speeds of 2 to 3 m/s. Survey-grade positions of the PWCs were achieved with a single-base station and differential post-processing. Positioning data from the GNSS receivers were post-processed using Waypoint Grafnav to apply differential corrections from a GNSS base station with known horizontal and vertical coordinates relative to the North American Datum of 1983. Orthometric elevations relative to the NAVD88 vertical datum were computed using National Geodetic Survey Geoid12a offsets. Bathymetric data were merged with post-processed positioning data and spurious soundings were removed using a custom Graphical User Interface (GUI) programmed with the computer program MATLAB. The average estimated vertical uncertainty of the bathymetric measurements is 10 cm. The final point data from the PWCs are provided in a comma-separated text file and are projected in cartesian coordinates using the Washington State Plane South, meters coordinate system.

This portion of the USGS data release presents topography data collected during surveys performed in the Columbia River littoral cell, Washington and Oregon, in 2017 (USGS Field Activity Number 2017-666-FA). Topographic profiles were collected by walking along survey lines with global navigation satellite system (GNSS) receivers mounted on backpacks. Prior to data collection, vertical distances between the GNSS antennas and the ground were measured using a tape measure. Hand-held data collectors were used to log raw data and display navigational information allowing surveyors to navigate survey lines spaced at 100- to 1000-m intervals along the beach. Profiles were surveyed from the landward edge of the study area (either the base of a bluff, engineering structure, or just landward of the primary dune) over the beach foreshore, to wading depth on the same series of transects as nearshore bathymetric surveys that were conducted during the same time period. Additional topographic data were collected between survey lines in some areas with an all-terrain vehicle (ATV) equipped with a GNSS receiver to constrain the elevations and alongshore extent of major morphological features. Positioning data from the survey platforms were referenced to a GNSS base station with known horizontal and vertical coordinates relative to the North American Datum of 1983. Differential corrections from the GNSS base stations to the survey platforms were either applied in real-time with a VHF radio link, or post-processed using Trimble Business Center software. Orthometric elevations relative to the NAVD88 vertical datum were computed using National Geodetic Survey Geoid12a offsets. The average estimated vertical uncertainty of the topographic measurements is 4 cm. The final point data are provided in comma-separated text format and are projected in Cartesian coordinates using the Washington State Plane South, meters coordinate system.

This portion of the USGS data release presents bathymetry data collected during surveys performed in the Columbia River littoral cell, Washington and Oregon in 2018 (USGS Field Activity Number 2018-652-FA). Bathymetry data were collected using four personal watercraft (PWCs) equipped with single-beam sonar systems and global navigation satellite system (GNSS) receivers. The sonar systems consisted of an Odom Echotrac CV-100 single-beam echosounder and 200 kHz transducer with a 9 degree beam angle. Raw acoustic backscatter returns were digitized by the echosounder with a vertical resolution of 1.25 cm. Depths from the echosounders were computed using sound velocity profiles measured using a YSI CastAway CTD during the survey. Positioning of the survey vessels was determined at 5 to 10 Hz using Trimble R7 GNSS receivers. Output from the GNSS receivers and sonar systems were combined in real time on the PWC by a computer running HYPACK hydrographic survey software. Navigation information was displayed on a video monitor, allowing PWC operators to navigate along survey lines at speeds of 2 to 3 m/s. Survey-grade positions of the PWCs were achieved with a single-base station and differential post-processing. Positioning data from the GNSS receivers were post-processed using Waypoint Grafnav to apply differential corrections from a GNSS base station with known horizontal and vertical coordinates relative to the North American Datum of 1983. Orthometric elevations relative to the NAVD88 vertical datum were computed using National Geodetic Survey Geoid12a offsets. Bathymetric data were merged with post-processed positioning data and spurious soundings were removed using a custom Graphical User Interface (GUI) programmed with the computer program MATLAB. The average estimated vertical uncertainty of the bathymetric measurements is 10 cm. The final point data from the PWCs are provided in a comma-separated text file and are projected in cartesian coordinates using the Washington State Plane South, meters coordinate system.

This portion of the USGS data release presents topography data collected during surveys performed in the Columbia River littoral cell, Washington and Oregon, in 2018 (USGS Field Activity Number 2018-652-FA). Topographic profiles were collected by walking along survey lines with global navigation satellite system (GNSS) receivers mounted on backpacks. Prior to data collection, vertical distances between the GNSS antennas and the ground were measured using a tape measure. Hand-held data collectors were used to log raw data and display navigational information allowing surveyors to navigate survey lines spaced at 100- to 1000-m intervals along the beach. Profiles were surveyed from the landward edge of the study area (either the base of a bluff, engineering structure, or just landward of the primary dune) over the beach foreshore, to wading depth on the same series of transects as nearshore bathymetric surveys that were conducted during the same time period. Additional topographic data were collected between survey lines in some areas with an all-terrain vehicle (ATV) equipped with a GNSS receiver to constrain the elevations and alongshore extent of major morphological features. Positioning data from the survey platforms were referenced to a GNSS base station with known horizontal and vertical coordinates relative to the North American Datum of 1983. Differential corrections from the GNSS base stations to the survey platforms were either applied in real-time with a VHF radio link, or post-processed using Trimble Business Center software. Orthometric elevations relative to the NAVD88 vertical datum were computed using National Geodetic Survey Geoid12a offsets. The average estimated vertical uncertainty of the topographic measurements is 4 cm. The final point data are provided in comma-separated text format and are projected in Cartesian coordinates using the Washington State Plane South, meters coordinate system.

This portion of the USGS data release presents bathymetry data collected during surveys performed in the Columbia River littoral cell, Washington and Oregon in 2019 (USGS Field Activity Number 2019-632-FA). Bathymetry data were collected using four personal watercraft (PWCs) equipped with single-beam sonar systems and global navigation satellite system (GNSS) receivers. The sonar systems consisted of an Odom Echotrac CV-100 single-beam echosounder and 200 kHz transducer with a 9-degree beam angle. Raw acoustic backscatter returns were digitized by the echosounder with a vertical resolution of 1.25 cm. Depths from the echosounders were computed using sound velocity profiles measured using a YSI CastAway CTD during the survey. Positioning of the survey vessels was determined at 5 to 10 Hz using Trimble R7 GNSS receivers. Output from the GNSS receivers and sonar systems were combined in real time on the PWC by a computer running HYPACK hydrographic survey software. Navigation information was displayed on a video monitor, allowing PWC operators to navigate along survey lines at speeds of 2 to 3 m/s. Survey-grade positions of the PWCs were achieved with a single-base station and differential post-processing. Positioning data from the GNSS receivers were post-processed using Waypoint Grafnav to apply differential corrections from a GNSS base station with known horizontal and vertical coordinates relative to the North American Datum of 1983. Orthometric elevations relative to the NAVD88 vertical datum were computed using National Geodetic Survey Geoid12a offsets. Bathymetric data were merged with post-processed positioning data and spurious soundings were removed using a custom Graphical User Interface (GUI) programmed with the computer program MATLAB. The average estimated vertical uncertainty of the bathymetric measurements is 10 cm. The final point data from the PWCs are provided in a comma-separated text file and are projected in cartesian coordinates using the Washington State Plane South, meters coordinate system.

This portion of the USGS data release presents topography data collected during surveys performed in the Columbia River littoral cell, Washington and Oregon, in 2019 (USGS Field Activity Number 2019-632-FA). Topographic profiles were collected by walking along survey lines with global navigation satellite system (GNSS) receivers mounted on backpacks. Prior to data collection, vertical distances between the GNSS antennas and the ground were measured using a tape measure. Hand-held data collectors were used to log raw data and display navigational information allowing surveyors to navigate survey lines spaced at 100- to 1000-m intervals along the beach. Profiles were surveyed from the landward edge of the study area (either the base of a bluff, engineering structure, or just landward of the primary dune) over the beach foreshore, to wading depth on the same series of transects as nearshore bathymetric surveys that were conducted during the same time period. Additional topographic data were collected between survey lines in some areas with an all-terrain vehicle (ATV) equipped with a GNSS receiver to constrain the elevations and alongshore extent of major morphological features. Positioning data from the survey platforms were referenced to a GNSS base station with known horizontal and vertical coordinates relative to the North American Datum of 1983. Differential corrections from the GNSS base stations to the survey platforms were either applied in real-time with a VHF radio link, or post-processed using Trimble Business Center software. Orthometric elevations relative to the NAVD88 vertical datum were computed using National Geodetic Survey Geoid12a offsets. The average estimated vertical uncertainty of the topographic measurements is 4 cm. The final point data are provided in comma-separated text format and are projected in Cartesian coordinates using the Washington State Plane South, meters coordinate system.

Projected coastal squeeze derived from CoSMoS Phase 2 shoreline change and cliff retreat projections. Projected coastal squeeze extents illustrate the available area between shoreline (mean high water; MHW) positions and man-made structures and barriers (referred to as non-erodible structures) or cliff-top retreat, as applicable, for a range of sea-level rise scenarios. The coastal squeeze polygons include results from the Coastal Storm Modeling System (CoSMoS) shoreline change (CoSMoS-COAST; Vitousek and others, 2017; available at https://www.sciencebase.gov/catalog/item/57f426b9e4b0bc0bec033fad) and cliff retreat models (Limber and others, 2015; available at https://www.sciencebase.gov/catalog/item/57f4234de4b0bc0bec033f90) using future wave-climate conditions derived from Global Climate Models (GCMs). Coastal squeeze areas are identified and defined from combined model projections, using model scenarios where erosion was limited by non-erodible structures (for shoreline change models) and armoring (for cliff retreat models; both cliff and shoreline cases referred to as 'hold the line') and where no beach-nourishment was included. Coastal squeeze projections are defined for each sea-level rise scenario. Shoreline change and cliff retreat model details and data sources are outlined in CoSMoS_3.0_Phase_2_Southern_California_Bight:_Summary_of_data_and_methods (available at https://www.sciencebase.gov/catalog/file/get/57f1d4f3e4b0bc0bebfee139?name=CoSMoS_SoCalv3_Phase2_summary_of_methods.pdf). Phase 2 data for Southern California include information for the coast from the border of Mexico to Pt. Conception. Please read the Summary of methods and inspect output carefully. Data are complete for the information presented.

Geographic extent of projected runup associated with the sea-level rise and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Model details and data sources are outlined in CoSMoS_3.0_Phase_2_Southern_California_Bight:_Summary_of_data_and_methods (available at https://www.sciencebase.gov/catalog/file/get/57f1d4f3e4b0bc0bebfee139?name=CoSMoS_SoCalv3_Phase2_summary_of_methods.pdf). Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the Summary of methods and inspect output carefully. Data are complete for the information presented.

This part of the data release presents a digital elevation model (DEM) derived from bathymetry and topography data of the Elwha River delta collected in May 2011. Two dams on the Elwha River, Washington State, USA trapped over 20 million m3 of sediment, reducing downstream sediment fluxes and contributing to erosion of the river's coastal delta. The removal of the Elwha and Glines Canyon dams between 2011 and 2014 induced massive increases in river sediment supply and provided an unprecedented opportunity to examine the response of a delta system to changes in sediment supply. The U.S. Geological Survey developed an integrated research program aimed at understanding the ecosystem responses following dam removal that included regular monitoring of coastal and nearshore bathymetry and topography. As part of this monitoring program, the USGS conducted a bathymetric and topographic survey in the Strait of Juan de Fuca on the Elwha River delta, Washington (USGS Field Activity Number W-04-11-PS). Bathymetry data were collected using two personal watercraft (PWCs), each equipped with single-beam echosounders and survey-grade global navigation satellite system (GNSS) receivers. Topography data were collected on foot with GNSS receivers mounted on backpacks. DEM surfaces were produced from all available elevation data using linear interpolation.

This part of the data release presents bathymetry data from the Elwha River delta collected in May 2011 using two personal watercraft (PWCs). The PWCs were equipped with single-beam echosounders and survey-grade global navigation satellite system (GNSS) receivers.

This part of the data release presents topography data from the Elwha River delta collected in May 2011. Topography data were collected on foot with global navigation satellite system (GNSS) receivers mounted on backpacks.

Water depth and turbidity time-series data were collected in Little Holland Tract (LHT) in 2015. Depth (from pressure) was measured in high-frequency (6 or 8 Hz) bursts. Burst means represent tidal stage, and burst data can be used to determine wave height and period. The turbidity sensors were calibrated to suspended-sediment concentration measured in water samples collected on site. The calibration and fit parameters for all of the turbidity sensors used in the study are tabulated and provided with the data. Data were sequentially added to this data release as they were collected and post-processed. Typically, each zip folder for a deployment period contains one file from an optical backscatter sensor and two files of data from a bursting pressure sensor.

This part of the data release presents a digital elevation model (DEM) derived from bathymetry and topography data of the Elwha River delta collected in August 2011. Two dams on the Elwha River, Washington State, USA trapped over 20 million m3 of sediment, reducing downstream sediment fluxes and contributing to erosion of the river's coastal delta. The removal of the Elwha and Glines Canyon dams between 2011 and 2014 induced massive increases in river sediment supply and provided an unprecedented opportunity to examine the response of a delta system to changes in sediment supply. The U.S. Geological Survey developed an integrated research program aimed at understanding the ecosystem responses following dam removal that included regular monitoring of coastal and nearshore bathymetry and topography. As part of this monitoring program, the USGS conducted a bathymetric and topographic survey in the Strait of Juan de Fuca on the Elwha River delta, Washington (USGS Field Activity Number W-06-11-PS). Bathymetry data were collected using two personal watercraft (PWCs), each equipped with single-beam echosounders and survey-grade global navigation satellite system (GNSS) receivers. Topography data were collected on foot with GNSS receivers mounted on backpacks. DEM surfaces were produced from all available elevation data using linear interpolation.

This part of the data release presents bathymetry data from the Elwha River delta collected in August 2011 using two personal watercraft (PWCs). The PWCs were equipped with single-beam echosounders and survey-grade global navigation satellite system (GNSS) receivers.

This part of the data release presents topography data from the Elwha River delta collected in August 2011. Topography data were collected on foot with global navigation satellite system (GNSS) receivers mounted on backpacks.

This part of the data release presents a digital elevation model (DEM) derived from bathymetry and topography data of the Elwha River delta collected in April 2014. Two dams on the Elwha River, Washington State, USA trapped over 20 million m3 of sediment, reducing downstream sediment fluxes and contributing to erosion of the river's coastal delta. The removal of the Elwha and Glines Canyon dams between 2011 and 2014 induced massive increases in river sediment supply and provided an unprecedented opportunity to examine the response of a delta system to changes in sediment supply. The U.S. Geological Survey developed an integrated research program aimed at understanding the ecosystem responses following dam removal that included regular monitoring of coastal and nearshore bathymetry and topography. As part of this monitoring program, the USGS conducted a bathymetric and topographic survey in the Strait of Juan de Fuca on the Elwha River delta, Washington (USGS Field Activity Number 2014-620-FA). Bathymetry data were collected using two personal watercraft (PWCs), each equipped with single-beam echosounders and survey-grade global navigation satellite system (GNSS) receivers. Topography data were collected on foot with GNSS receivers mounted on backpacks. DEM surfaces were produced from all available elevation data using linear interpolation.

This part of the data release presents bathymetry data from the Elwha River delta collected in April 2014 using two personal watercraft (PWCs). The PWCs were equipped with single-beam echosounders and survey-grade global navigation satellite system (GNSS) receivers.

This part of the data release presents topography data from the Elwha River delta collected in April 2014. Topography data were collected on foot with global navigation satellite system (GNSS) receivers mounted on backpacks.

This portion of the data release presents sediment grain-size data from samples collected on the Elwha River delta, Washington, in May 2014 (USGS Field Activity 2014-620-FA). Surface sediment was collected from 43 locations using a small ponar, or 'grab', sampler from a small boat on May 12, 2014 in depths between about 1 and 12 m around the delta. The locations of grab samples were determined with a hand-held global navigation satellite system (GNSS). The grain-size distributions of samples were determined using standard techniques developed by the USGS Pacific Coastal and Marine Science Center sediment lab. Grab samples that yielded less than 50 g of sediment were omitted from analysis and are classified as "no sample". The grain-size data are provided in a comma-delimited spreadsheet (.csv).

This part of the data release presents a digital elevation model (DEM) derived from bathymetry and topography data of the Elwha River delta collected in May 2012. Two dams on the Elwha River, Washington State, USA trapped over 20 million m3 of sediment, reducing downstream sediment fluxes and contributing to erosion of the river's coastal delta. The removal of the Elwha and Glines Canyon dams between 2011 and 2014 induced massive increases in river sediment supply and provided an unprecedented opportunity to examine the response of a delta system to changes in sediment supply. The U.S. Geological Survey developed an integrated research program aimed at understanding the ecosystem responses following dam removal that included regular monitoring of coastal and nearshore bathymetry and topography. As part of this monitoring program, the USGS conducted a bathymetric and topographic survey in the Strait of Juan de Fuca on the Elwha River delta, Washington (USGS Field Activity Number W-03-12-PS). Bathymetry data were collected using two personal watercraft (PWCs), each equipped with single-beam echosounders and survey-grade global navigation satellite system (GNSS) receivers. Topography data were collected on foot with GNSS receivers mounted on backpacks. DEM surfaces were produced from all available elevation data using linear interpolation.

This part of the data release presents bathymetry data from the Elwha River delta collected in May 2012 using two personal watercraft (PWCs). The PWCs were equipped with single-beam echosounders and survey-grade global navigation satellite system (GNSS) receivers.

This part of the data release presents topography data from the Elwha River delta collected in May 2012. Topography data were collected on foot with global navigation satellite system (GNSS) receivers mounted on backpacks.

This part of the data release presents bathymetry data from the Elwha River delta collected in September 2010 using a personal watercraft (PWC) and a small boat. Both survey vessels were equipped with single-beam echosounders and survey-grade global navigation satellite system (GNSS) receivers.

This part of the data release presents a digital elevation model (DEM) derived from bathymetry and topography data of the Elwha River delta collected in September 2010. Two dams on the Elwha River, Washington State, USA trapped over 20 million m3 of sediment, reducing downstream sediment fluxes and contributing to erosion of the river's coastal delta. The removal of the Elwha and Glines Canyon dams between 2011 and 2014 induced massive increases in river sediment supply and provided an unprecedented opportunity to examine the response of a delta system to changes in sediment supply. The U.S. Geological Survey developed an integrated research program aimed at understanding the ecosystem responses following dam removal that included regular monitoring of coastal and nearshore bathymetry and topography. As part of this monitoring program, the USGS conducted a bathymetric and topographic survey in the Strait of Juan de Fuca on the Elwha River delta, Washington (USGS Field Activity Number W-03-10-PS). Bathymetry data were collected using a personal watercraft (PWC) and a small boat, each equipped with single-beam echosounders and survey-grade global navigation satellite system (GNSS) receivers. Topography data were collected on foot with GNSS receivers mounted on backpacks. DEM surfaces were produced from all available elevation data using linear interpolation.

This part of the data release presents topography data from the Elwha River delta collected in September 2010. Topography data were collected on foot with global navigation satellite system (GNSS) receivers mounted on backpacks.

A high-resolution (10-meter per pixel) digital elevation model (DEM) was created for the Sacramento-San Joaquin Delta using both bathymetry and topography data. This DEM is the result of collaborative efforts of the U.S. Geological Survey (USGS) and the California Department of Water Resources (DWR). The base of the DEM is from a 10-m DEM released in 2004 and updated in 2005 (Foxgrover and others, 2005) that used Environmental Systems Research Institute(ESRI), ArcGIS Topo to Raster module to interpolate grids from single beam bathymetric surveys collected by DWR, the Army Corp of Engineers (COE), the National Oceanic and Atmospheric Administration (NOAA), and the USGS, into a continuous surface. The Topo to Raster interpolation method was specifically designed to create hydrologically correct DEMs from point, line, and polygon data (Environmental Systems Research Institute, Inc., 2015). Elevation contour lines were digitized based on the single beam point data for control of channel morphology during the interpolation process. Checks were performed to ensure that the interpolated surfaces honored the source bathymetry, and additional contours and(or) point data were added as needed to help constrain the data. The original data were collected in the tidal datum Mean Lower or Low Water (MLLW), or the National Geodetic Vertical Datum of 1929 (NGVD29). All data were converted to NGVD29. The 2005 USGS DEM was updated by DWR, first by converting the DEM to the current modern datum of National Geodetic Vertical Datum of 1988 (NGVD88) and then by following the methodology of the USGS DEM, established for the 2005 DEM (Foxgrover and others, 2005) for adding newly collected single and multibeam bathymetric data. They then included topographic data from lidar surveys, providing the first DEM that included the land/water interface (Wang and Ateljevich, 2012). The USGS further updated and expanded the DWR DEM with the inclusion of USGS interpolated sections of single beam bathymetry data collected by the COE and USGS scientists, expanding the DEM to include the northernmost areas of the Sacramento-San Joaquin Delta, and by making use of a two-meter seamless bathymetric/topographic DEM from the USGS EROS Data Center (2013) of the San Francisco Bay region. The resulting 10-meter USGS DEM encompasses the entirety of Suisun Bay, beginning with the Carquinez Strait in the west, east to California Interstate 5, north following the path of the Yolo Bypass and the Sacramento River up to Knights Landing, and the American River northeast to the Nimbus Dam, and south to areas around Tracy. The DEM incorporates the newest available bathymetry data at the time of release, as well as including, at minimum, a 100-meter band of available topography data adjacent to most shorelines. No data areas within the DEM are areas where no elevation data exists, either due to a gap in the land/water interface, or because lidar was collected over standing water that was then cut out of the DEM.

This part of the data release presents a digital elevation model (DEM) derived from bathymetry and topography data of the Elwha River delta collected in July 2016. Two dams on the Elwha River, Washington State, USA trapped over 20 million m3 of sediment, reducing downstream sediment fluxes and contributing to erosion of the river's coastal delta. The removal of the Elwha and Glines Canyon dams between 2011 and 2014 induced massive increases in river sediment supply and provided an unprecedented opportunity to examine the response of a delta system to changes in sediment supply. The U.S. Geological Survey developed an integrated research program aimed at understanding the ecosystem responses following dam removal that included regular monitoring of coastal and nearshore bathymetry and topography. As part of this monitoring program, the USGS conducted a bathymetric and topographic survey in the Strait of Juan de Fuca on the Elwha River delta, Washington (USGS Field Activity Number 2016-653-FA). Bathymetry data were collected using two personal watercraft (PWCs) and a kayak, each equipped with single beam echosounders and survey-grade global navigation satellite systems (GNSS). Topography data were collected on foot with GNSS receivers mounted on backpacks. DEM surfaces were produced from all available elevation data using linear interpolation.

This portion of the data release presents sediment grain-size data from samples collected on the Elwha River delta, Washington, in July 2016 (USGS Field Activity 2016-653-FA). Surface sediment was collected from 67 locations using a small ponar, or 'grab', sampler from the R/V Frontier in water depths between about 1 and 17 m around the delta. An additional 38 samples were collected by hand at low tide. A hand-held global satellite navigation system (GNSS) receiver was used to determine the locations of sediment samples. The grain size distributions of suitable samples were determined using standard techniques developed by the USGS Pacific Coastal and Marine Science Center sediment lab. Grab samples that yielded less than 50 g of sediment were omitted from analysis and are classified as "no sample". The grain-size data are provided in a comma-delimited spreadsheet (.csv).

This part of the data release presents bathymetry data from the Elwha River delta collected in July 2016 using a kayak. The kayak was equipped with a single-beam echosounder and a survey-grade global navigation satellite system (GNSS) receiver.

This part of the data release presents bathymetry data from the Elwha River delta collected in July 2016 using two personal watercraft (PWCs). The PWCs were equipped with single beam echosounders and survey-grade global navigation satellite system (GNSS) receivers.

This part of the data release presents topography data from the Elwha River delta collected in July 2016. Topography data were collected on foot with global navigation satellite system (GNSS) receivers mounted on backpacks.

This portion of the data release contains a digital image mosaic with 1.0 foot-per-pixel (0.3048 meter-per-pixel) resolution of the Diamond Head area on the southeast coast of O'ahu. This image mosaic was generated using digitized 1:10K natural color photographs collected by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service. Also available is a lower-resolution 'browse' graphic of the image mosaic area and associated metadata.

This portion of the data release contains a digital image mosaic with 1 meter-per-pixel resolution of the Haleolono Point area on the south coast of Moloka'i. This image mosaic was generated using digitized 1:35K natural color photographs collected in September 1993 by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS). Also available is a lower-resolution 'browse' graphic of the image mosaic and associated metadata.

This portion of the data release contains an image mosaic with 1.0 meter-per-pixel resolution of the Kailua-Kona area on the west 'Kona' coast of the island of Hawai'i. This image mosaic was generated using digitized 1:24K natural color photographs collected in June 2000 by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS). Two versions of the image mosaic are available--one with and one without a lidar bathymetry shaded-relief image digitally combined with the aerial photography mosaic results. The shaded-relief image was derived using airborne SHOALS (Scanning Hydrographic Operational Lidar Survey) lidar (LIght Detection And Ranging) data collected for the U.S. Geological Survey (USGS) by the U.S. Army Corp of Engineers (USACE) in April 1999. Also available is a lower-resolution 'browse' graphic of the image mosaic and associated metadata.

This portion of the data release contains a digital image mosaic with 1.0 foot-per-pixel resolution of the Kalaeloa area on the south coast of Moloka'i. This image mosaic was generated using digitized 1:10K natural color photographs collected in January 2000 by Air Survey Hawai'i, Inc. for the U.S. Geological Survey. Also available is a lower-resolution 'browse' graphic of the image mosaic area and associated metadata.

This portion of the data release contains a digital image mosaic with 1.0 foot-per-pixel resolution of the Kamalo area on the south coast of Moloka'i. This image mosaic was generated using digitized 1:10K natural color photographs collected in January 2000 by Air Survey Hawai'i, Inc. for the U.S. Geological Survey. Also available is a lower-resolution 'browse' graphic of the image mosaic area and associated metadata.

This portion of the data release contains a digital image mosaic with 1 meter-per-pixel resolution of the Kamalo area on the south coast of Moloka'i. This image mosaic was generated using digitized 1:35K natural color photographs collected in September 1993 by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS). Also available is a lower-resolution 'browse' graphic of the image mosaic and associated metadata.

This portion of the data release contains a digital image mosaic with 1.0 foot-per-pixel resolution of the Kamiloloa area on the south coast of Moloka'i. This image mosaic was generated using digitized 1:10K natural color photographs collected in January 2000 by Air Survey Hawai'i, Inc. for the U.S. Geological Survey. Also available is a lower-resolution 'browse' graphic of the image mosaic area and associated metadata.

This portion of the data release contains a digital image mosaic with 1 meter-per-pixel resolution of the Kamiloloa area on the south coast of Moloka'i. This image mosaic was generated using digitized 1:35K natural color photographs collected in September 1993 by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS). Also available is a lower-resolution 'browse' graphic of the image mosaic and associated metadata.

This portion of the data release contains a digital image mosaic with 1.0 foot-per-pixel resolution of the Kaunakakai area on the south coast of Moloka'i. This image mosaic was generated using digitized 1:10K natural color photographs collected in January 2000 by Air Survey Hawai'i, Inc. for the U.S. Geological Survey. Also available is a lower-resolution 'browse' graphic of the image mosaic area and associated metadata.

This portion of the data release contains a digital image mosaic with 1 meter-per-pixel resolution of the Kaunakakai area on the south coast of Moloka'i. This image mosaic was generated using digitized 1:35K natural color photographs collected in September 1993 by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS). Also available is a lower-resolution 'browse' graphic of the image mosaic and associated metadata.

This portion of the data release contains an image mosaic of the Kawaihae area on the west 'Kona' coast of the island of Hawai'i. This image mosaic was generated using digitized 1:24K natural color photographs collected in June 2000 by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS). Two versions of the image mosaic are available--one with and one without a lidar bathymetry shaded-relief image digitally combined with the aerial photography mosaic results. The shaded-relief image was derived using airborne SHOALS (Scanning Hydrographic Operational Lidar Survey) lidar (LIght Detection And Ranging) data collected for the U.S. Geological Survey (USGS) by the U.S. Army Corp of Engineers (USACE) in April 1999. Also available is a lower-resolution 'browse' graphic of the image mosaic and associated metadata.

This portion of the data release contains a digital image mosaic with 1.0 foot-per-pixel resolution of the Kawela area on the south coast of Moloka'i. This image mosaic was generated using digitized 1:10K natural color photographs collected in January 2000 by Air Survey Hawai'i, Inc. for the U.S. Geological Survey. Also available is a lower-resolution 'browse' graphic of the image mosaic area and associated metadata.

This portion of the data release contains a digital image mosaic with 1 meter-per-pixel resolution of the Kawela area on the south coast of Moloka'i. This image mosaic was generated using digitized 1:35K natural color photographs collected in September 1993 by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS). Also available is a lower-resolution 'browse' graphic of the image mosaic and associated metadata.

This portion of the data release contains an image mosaic of the Kukio area on the west 'Kona' coast of the island of Hawai'i. This image mosaic was generated using digitized 1:24K natural color photographs collected in June 2000 by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS). Two versions of the image mosaic are available--one with and one without a lidar bathymetry shaded-relief image digitally combined with the aerial photography mosaic results. The shaded-relief image was derived using airborne SHOALS (Scanning Hydrographic Operational Lidar Survey) lidar (LIght Detection And Ranging) data collected for the U.S. Geological Survey (USGS) by the U.S. Army Corp of Engineers (USACE) in April 1999. Also available is a lower-resolution 'browse' graphic of the image mosaic and associated metadata.

This portion of the data release contains a digital image mosaic with 1 meter-per-pixel resolution of the La'au Point area on the south coast of Moloka'i. This image mosaic was generated using digitized 1:35K natural color photographs collected in September 1993 by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS). Also available is a lower-resolution 'browse' graphic of the image mosaic and associated metadata.

This portion of the data release contains a digital image mosaic with 1.0 foot-per-pixel (0.3048 meter-per-pixel) resolution of the Maunalua Bay area on the southeast coast of O'ahu. This image mosaic was generated using digitized 1:10K natural color photographs collected by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service. Also available is a lower-resolution 'browse' graphic of the image mosaic area and associated metadata.

This portion of the data release contains an image mosaic of the Napili-Honokowai area on the northwest coast of Maui. This image mosaic was generated using digitized 1:35K natural color photographs collected in September 1993 by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS). The image mosaic has been geometrically corrected using lidar data. Also available is a lower-resolution 'browse' image, and associated metadata.

This portion of the data release contains a digital image mosaic with 1.0 foot-per-pixel resolution of the Pala'au area on the south coast of Moloka'i. This image mosaic was generated using digitized 1:10K natural color photographs collected in January 2000 by Air Survey Hawai'i, Inc. for the U.S. Geological Survey. Also available is a lower-resolution 'browse' graphic of the image mosaic area and associated metadata.

This portion of the data release contains a digital image mosaic with 1 meter-per-pixel resolution of the Pala'au area on the south coast of Moloka'i. This image mosaic was generated using digitized 1:35K natural color photographs collected in September 1993 by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS). Also available is a lower-resolution 'browse' graphic of the image mosaic and associated metadata.

This portion of the data release contains a digital image mosaic with 1.0 foot-per-pixel (0.3048 meter-per-pixel) resolution of the Portlock area on the southeast coast of O'ahu. This image mosaic was generated using digitized 1:10K natural color photographs collected by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service. Also available is a lower-resolution 'browse' graphic of the image mosaic area and associated metadata.

This portion of the data release contains a digital image mosaic with 1 meter-per-pixel resolution of the Puko'o area on the south coast of Moloka'i. This image mosaic was generated using digitized 1:35K natural color photographs collected in September 1993 by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS). Also available is a lower-resolution 'browse' graphic of the image mosaic and associated metadata.

This portion of the data release contains a shaded-relief image mosaic of the nearshore coastal waters along southcentral Moloka'i. This image mosaic was generated using digitized 1:35K natural color photographs collected in September 1993 by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS) and scanned in at 1-meter resolution. Several of the 1-meter-resolution images have been merged together and combined with lidar bathymetry data to create a large shaded-relief image. Also available is a lower-resolution 'browse' graphic and associated metadata.

This portion of the data release contains a shaded-relief image mosaic of the nearshore coastal waters along southeast Moloka'i. This image mosaic was generated using digitized 1:35K natural color photographs collected in September 1993 by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS) and scanned in at 1-meter resolution. Several of the 1-meter-resolution images have been merged together and combined with lidar bathymetry data to create a large shaded-relief image. Also available is a lower-resolution 'browse' graphic and associated metadata.

This portion of the data release contains a shaded-relief image mosaic of the nearshore coastal waters along southwest Moloka'i. This image mosaic was generated using digitized 1:35K natural color photographs collected in September 1993 by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS) and scanned in at 1-meter resolution. Several of the 1-meter-resolution images have been merged together and combined with lidar bathymetry data to create a large shaded-relief image. Also available is a lower-resolution 'browse' graphic and associated metadata.

This portion of the data release contains a digital image mosaic with 1.0 foot-per-pixel resolution of the Umipa'a area on the south coast of Moloka'i. This image mosaic was generated using digitized 1:10K natural color photographs collected in January 2000 by Air Survey Hawai'i, Inc. for the U.S. Geological Survey. Also available is a lower-resolution 'browse' graphic of the image mosaic area and associated metadata.

This portion of the data release contains a digital image mosaic with 1 meter-per-pixel resolution of the Waiakane area on the south coast of Moloka'i. This image mosaic was generated using digitized 1:35K natural color photographs collected in September 1993 by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS). Also available is a lower-resolution 'browse' graphic of the image mosaic and associated metadata.

This portion of the data release contains a digital image mosaic with 1.0 foot-per-pixel (0.3048 meter-per-pixel) resolution of the Wai'alae area on the southeast coast of O'ahu. This image mosaic was generated using digitized 1:10K natural color photographs collected by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service. Also available is a lower-resolution 'browse' graphic of the image mosaic area and associated metadata.

This portion of the data release contains a digital image mosaic with 1.0 foot-per-pixel (0.3048 meter-per-pixel) resolution of the Waikiki area on the southeast coast of O'ahu. This image mosaic was generated using digitized 1:10K natural color photographs collected by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service. Also available is a lower-resolution 'browse' graphic of the image mosaic area and associated metadata.

This portion of the data release contains a digital image mosaic from Waikiki to Portlock along the southeast coast of O'ahu. Digital mosaics at 1-foot (0.3048-meter) resolution, including the areas of Waikiki, Diamond Head, Wai'alae, Maunalua Bay, and Portlock, were generated from 1:10K aerial photography. These five image mosaics were then combined into one larger mosaic and resampled to 1-meter resolution.

This portion of the data release contains a digital image mosaic from Waikiki to Portlock along the southeast coast of O'ahu. Digital mosaics at 1-foot (0.3048-meter) resolution, including the areas of Waikiki, Diamond Head, Wai'alae, Maunalua Bay, and Portlock, were generated from 1:10K aerial photography. These five image mosaics were then combined into one larger mosaic, resampled to 1-meter resolution, and merged with lidar bathymetry data to produce the shaded-relief image.

This portion of the data release contains an image mosaic of the Waikoloa area on the west 'Kona' coast of the island of Hawai'i. This image mosaic was generated using digitized 1:24K natural color photographs collected in June 2000 by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS). Two versions of the image mosaic are available--one with and one without a lidar bathymetry shaded-relief image digitally combined with the aerial photography mosaic results. The shaded-relief image was derived using airborne SHOALS (Scanning Hydrographic Operational Lidar Survey) lidar (LIght Detection And Ranging) data collected for the U.S. Geological Survey (USGS) by the U.S. Army Corp of Engineers (USACE) in April 1999. Also available is a lower-resolution 'browse' graphic of the image mosaic and associated metadata.

This part of the data release presents a digital elevation model (DEM) derived from bathymetry and topography data of the Elwha River delta collected in September 2014. Two dams on the Elwha River, Washington State, USA trapped over 20 million m3 of sediment, reducing downstream sediment fluxes and contributing to erosion of the river's coastal delta. The removal of the Elwha and Glines Canyon dams between 2011 and 2014 induced massive increases in river sediment supply and provided an unprecedented opportunity to examine the response of a delta system to changes in sediment supply. The U.S. Geological Survey developed an integrated research program aimed at understanding the ecosystem responses following dam removal that included regular monitoring of coastal and nearshore bathymetry and topography. As part of this monitoring program, the USGS conducted a bathymetric and topographic survey in the Strait of Juan de Fuca on the Elwha River delta, Washington (USGS Field Activity Number 2014-649-FA). Bathymetry data were collected using two personal watercraft (PWCs), each equipped with single-beam echosounders and survey-grade global navigation satellite systems (GNSS). Topography data were collected on foot with GNSS receivers mounted on backpacks. DEM surfaces were produced from all available elevation data using linear interpolation.

This portion of the data release presents sediment grain-size data from samples collected on the Elwha River delta, Washington, in September 2014 (USGS Field Activity 2014-649-FA). Surface sediment was collected from 63 locations using a small ponar, or 'grab', sampler from the R/V Frontier on September 5, 2014 in depths between about 1 and 17 m around the delta. The locations of grab samples were determined with a hand-held global navigation satellite system (GNSS). The grain-size distributions of samples were determined using standard techniques developed by the USGS Pacific Coastal and Marine Science Center sediment lab. The grain-size data are provided in a comma-delimited spreadsheet (.csv).

This part of the data release presents bathymetry data from the Elwha River delta collected in September 2014 using two personal watercraft (PWCs). The PWCs were equipped with single-beam echosounders and survey-grade global navigation satellite system (GNSS) receivers.

This part of the data release presents topography data from the Elwha River delta collected in September 2014. Topography data were collected on foot with global navigation satellite system (GNSS) receivers mounted on backpacks.

This part of the data release presents bathymetry data from the Elwha River delta collected in August 2012 using a personal watercraft (PWC) and the R/V Frontier. Both survey vessels were equipped with single-beam echosounders and survey-grade global navigation satellite system (GNSS) receivers.

This part of the data release presents a digital elevation model (DEM) derived from bathymetry and topography data of the Elwha River delta collected in August 2012. Two dams on the Elwha River, Washington State, USA trapped over 20 million m3 of sediment, reducing downstream sediment fluxes and contributing to erosion of the river's coastal delta. The removal of the Elwha and Glines Canyon dams between 2011 and 2014 induced massive increases in river sediment supply and provided an unprecedented opportunity to examine the response of a delta system to changes in sediment supply. The U.S. Geological Survey developed an integrated research program aimed at understanding the ecosystem responses following dam removal that included regular monitoring of coastal and nearshore bathymetry and topography. As part of this monitoring program, the USGS conducted a bathymetric and topographic survey in the Strait of Juan de Fuca on the Elwha River delta, Washington (USGS Field Activity Number W-05-12-PS). Bathymetry data were collected using two survey vessels, each equipped with single-beam echosounders and survey-grade global navigation satellite system (GNSS) receivers. Topography data were collected on foot with GNSS receivers mounted on backpacks. DEM surfaces were produced from all available elevation data using linear interpolation.

This portion of the data release presents sediment grain-size data from samples collected on the Elwha River delta, Washington, in August 2012 (USGS Field Activity W-05-12-PS). Surface sediment was sampled using a small ponar, or 'grab', sampler between August 28 and August 30, 2012 from the R/V Frontier at a total of 57 locations in water depths between about 1 and 9 m around the delta. The locations of grab samples were determined with a hand-held global navigation satellite system (GNSS). The grain-size distributions of samples were determined using standard techniques developed by the USGS Pacific Coastal and Marine Science Center sediment lab. Grab samples that yielded less than 50 g of sediment were omitted from analysis and are classified as "no sample". The grain-size data are provided in a comma-delimited spreadsheet (.csv).

This part of the data release presents topography data from the Elwha River delta collected in August 2012. Topography data were collected on foot with global navigation satellite system (GNSS) receivers mounted on backpacks.

This part of the data release presents a digital elevation model (DEM) derived from bathymetry and topography data of the Elwha River delta collected in March 2013. Two dams on the Elwha River, Washington State, USA trapped over 20 million m3 of sediment, reducing downstream sediment fluxes and contributing to erosion of the river's coastal delta. The removal of the Elwha and Glines Canyon dams between 2011 and 2014 induced massive increases in river sediment supply and provided an unprecedented opportunity to examine the response of a delta system to changes in sediment supply. The U.S. Geological Survey developed an integrated research program aimed at understanding the ecosystem responses following dam removal that included regular monitoring of coastal and nearshore bathymetry and topography. As part of this monitoring program, the USGS conducted a bathymetric and topographic survey in the Strait of Juan de Fuca on the Elwha River delta, Washington (USGS Field Activity Number W-01-13-PS). Bathymetry data were collected using two personal watercraft (PWCs), each equipped with single-beam echosounders and survey-grade global navigation satellite system (GNSS) receivers. Topography data were collected on foot with GNSS receivers mounted on backpacks. DEM surfaces were produced from all available elevation data using linear interpolation.

This portion of the data release presents sediment grain-size data from samples collected on the Elwha River delta, Washington, in March 2013 (USGS Field Activity W-01-13-PS). Surface sediment was sampled using a small ponar, or 'grab', sampler on March 4, 2013 from the R/V Frontier at a total of 48 locations in water depths between about 1 and 12 m around the delta. An additional 7 sediment samples were collected between March 6 and March 7, 2013 at low tide from intertidal locations on the delta. The locations of grab samples were determined with a hand-held global navigation satellite system (GNSS). The grain-size distributions of samples were determined using standard techniques developed by the USGS Pacific Coastal and Marine Science Center sediment lab. Grab samples that yielded less than 50 g of sediment were omitted from analysis and are classified as "no sample". The grain-size data are provided in a comma-delimited spreadsheet (.csv).

This part of the data release presents bathymetry data from the Elwha River delta collected in March 2013 using two personal watercraft (PWCs). The PWCs were equipped with single-beam echosounders and survey-grade global navigation satellite system (GNSS) receivers.

This part of the data release presents topography data from the Elwha River delta collected in March 2013. Topography data were collected on foot with global navigation satellite system (GNSS) receivers mounted on backpacks.

This part of the data release presents a digital elevation model (DEM) derived from bathymetry and topography data of the Elwha River delta collected in July 2015. Two dams on the Elwha River, Washington State, USA trapped over 20 million m3 of sediment, reducing downstream sediment fluxes and contributing to erosion of the river's coastal delta. The removal of the Elwha and Glines Canyon dams between 2011 and 2014 induced massive increases in river sediment supply and provided an unprecedented opportunity to examine the response of a delta system to changes in sediment supply. The U.S. Geological Survey developed an integrated research program aimed at understanding the ecosystem responses following dam removal that included regular monitoring of coastal and nearshore bathymetry and topography. As part of this monitoring program, the USGS conducted a bathymetric and topographic survey in the Strait of Juan de Fuca on the Elwha River delta, Washington (USGS Field Activity Number 2015-648-FA). Bathymetry data were collected using two personal watercraft (PWCs), each equipped with single-beam echosounders and survey-grade global navigation satellite systems (GNSS). Topography data were collected on foot with GNSS receivers mounted on backpacks. DEM surfaces were produced from all available elevation data using linear interpolation.

This portion of the data release presents sediment grain-size data from samples collected on the Elwha River delta, Washington, between July and August 2015 (USGS Field Activities 2015-648-FA and 2015-652-FA). Surface sediment was collected from 70 locations using a small ponar, or 'grab', sampler from the R/V Frontier on July 28, 2015. An additional 17 sediment samples were collected between July 22 and August 23, 2015 by scuba divers. Forty-eight sediment samples were collected at low tide using a push corer at intertidal locations on the delta. The locations of grab samples and intertidal samples were determined with a hand-held global navigation satellite system (GNSS). Samples obtained by divers were collected adjacent to fixed monuments on the seabed with previously determined coordinates. The grain-size distributions of samples were determined using standard techniques developed by the USGS Pacific Coastal and Marine Science Center sediment lab. The grain-size data are provided in a comma-delimited spreadsheet (.csv).

This part of the data release presents bathymetry data from the Elwha River delta collected in July 2015 using two personal watercraft (PWCs). The PWCs were equipped with single-beam echosounders and survey-grade global navigation satellite systems (GNSS) receivers.

This part of the data release presents topography data from the Elwha River delta collected in July 2015. Topography data were collected on foot with global navigation satellite system (GNSS) receivers mounted on backpacks.

This part of the data release presents a digital elevation model (DEM) derived from bathymetry and topography data of the Elwha River delta collected in September 2013. Two dams on the Elwha River, Washington State, USA trapped over 20 million m3 of sediment, reducing downstream sediment fluxes and contributing to erosion of the river's coastal delta. The removal of the Elwha and Glines Canyon dams between 2011 and 2014 induced massive increases in river sediment supply and provided an unprecedented opportunity to examine the response of a delta system to changes in sediment supply. The U.S. Geological Survey developed an integrated research program aimed at understanding the ecosystem responses following dam removal that included regular monitoring of coastal and nearshore bathymetry and topography. As part of this monitoring program, the USGS conducted a bathymetric and topographic survey in the Strait of Juan de Fuca on the Elwha River delta, Washington (USGS Field Activity Number W-07-13-PS). Bathymetry data were collected using two personal watercraft (PWCs), each equipped with single-beam echosounders and survey-grade global navigation satellite system (GNSS) receivers. Topography data were collected on foot with GNSS receivers mounted on backpacks. DEM surfaces were produced from all available elevation data using linear interpolation.

This portion of the data release presents sediment grain-size data from samples collected on the Elwha River delta, Washington, in September 2013 (USGS Field Activity W-07-13-PS). Surface sediment was collected from 62 locations using a small ponar, or 'grab', sampler from the R/V Frontier on September 19, 2013 in depths between about 1 and 12 m around the delta. An additional 21 sediment samples were collected between September 16 and September 19, 2013 at low tide from intertidal locations on the delta. The locations of grab samples were determined with a hand-held global navigation satellite system (GNSS). The grain-size distributions of samples were determined using standard techniques developed by the USGS Pacific Coastal and Marine Science Center sediment lab. The grain-size data are provided in a comma-delimited spreadsheet (.csv).

This part of the data release presents bathymetry data from the Elwha River delta collected in September 2013 using two personal watercraft (PWCs). The PWCs were equipped with single-beam echosounders and survey-grade global navigation satellite system (GNSS) receivers.

This part of the data release presents topography data from the Elwha River delta collected in September 2013. Topography data were collected on foot with global navigation satellite system (GNSS) receivers mounted on backpacks.

This dataset contains projections of coastal cliff-retreat rates and positions for future scenarios of sea-level rise (SLR). Present-day cliff-edge positions used as the baseline for projections are also included. Projections were made using numerical and statistical models based on field observations such as historical cliff retreat rate, nearshore slope, coastal cliff height, and mean annual wave power, as part of Coastal Storm Modeling System (CoSMoS) v.3.0 Phase 2 in Southern California. Details: Cliff-retreat position projections and associated uncertainties are for scenarios of 0.25, 0.5, 0.75, 1, 1.25, 1.5, 1.75, 2, and 5 meters of SLR. Projections were made at CoSMoS cross-shore transects (CST) spaced 100 m alongshore using a baseline sea-cliff edge from 2010 (included in the dataset). Within each zip file, there are two separate datasets available: one that ignores coastal armoring, such as seawalls and revetments, and allows the cliff to retreat unimpeded (“Do Not Hold the Line”); and another that assumes that current coastal armoring will be maintained and 100% effective at stopping future cliff erosion ("Hold the Line"). Eight numerical models synthesized from literature (Trenhaile, 2000; Walkden and Hall, 2005; Trenhaile, 2009; Trenhaile, 2011; Ruggiero and others, 2011; Hackney and others, 2013) were used to make projections. All models relate breaking-wave height and period to cliff rock or unconsolidated sediment erosion. Models range in complexity from 2-D models in which the entire profile evolves, from below water to the cliff edge, to simple 1-D empirical or statistical models in which only the cliff edge evolves as a function of wave impact intensity and frequency. The projections are a robust average of all models, and the uncertainties are proportional to 1) underlying uncertainties in the model input data, such as historical cliff retreat rates, and 2) the differences between individual model forecasts at each CST so that uncertainty is larger when the models do not agree. As sea level rises, waves break closer to the sea cliff, more wave energy impacts the cliffs, cliff erosion rates accelerate. Model behavior also includes wave run-up (Stockdon and others, 2006), wave set-up that raises the water level during big-wave events, and tidal levels. The more complex 2-D models were run on idealized cliff profiles extending from about 10 m water depth to 1 kilometer inland from the cliff edge. Profiles were extracted by overlaying the cross-shore transects on a high-resolution digital elevation model (DEM) covering the Southern California study area. For all models, the presence of a beach was recorded (yes or no) for all transects using aerial photography, and the cliff toe elevation (or beach/cliff junction) was digitized from the DEM profiles. Using historic cliff edge retreat rates by Hapke and Reid (2007), unknown coefficients within the cliff-profile models were calibrated using a Monte Carlo simulation (in other words, coefficients were tuned until the modeled mean retreat rate equaled the observed mean retreat rate for a given transect). Uncertainty was tallied using a root mean squared error (RMSE) approach. The RMSE represents cumulative uncertainty from multiple sources and assumes that different sources of error will, at times, cancel each other out. It is therefore not a 'worst-case uncertainty' (in other words, a straight sum of errors) but instead an average uncertainty. Total RMSE increased with SLR rate and varied between +/- 2-3 m to a maximum of +/- 50 m for the extreme 5 m SLR scenario. For more information on model details, data sources, and integration with other parts of the CoSMoS framework, see CoSMoS_3.0_Phase_2_Southern_California_Bight:_Summary_of_data_and_methods (available at https://www.sciencebase.gov/catalog/file/get/57f1d4f3e4b0bc0bebfee139?name=CoSMoS_SoCalv3_Phase2_summary_of_methods.pdf).

This dataset contains projections of shoreline positions and uncertainty bands for future scenarios of sea-level rise. Projections were made using CoSMoS-COAST, a numerical model forced with global-to-local nested wave models and assimilated with lidar-derived shoreline vectors. Details: Projections of shoreline position in Southern California are made for scenarios of 0.25, 0.5, 0.75, 1.0, 1.25, 1.5, 1.75, 2.0, and 5.0 meters of sea-level rise by the year 2100. Four datasets are available for different management conditions: shorelines are allowed to retreat unimpeded past urban tructures ("NO Hold the Line") or are limited to this urban boundary ("Hold the Line"), and shorelines are allowed to progress with projected increases in sediment ("Continued Nourishment") or with no projected increases ("No Nourishment"). Projections are made at CoSMoS Monitoring and Observation Points, which represent shore-normal transects spaced 100 m alongshore. The newly developed CoSMoS-COAST model solves a coupled set of partial differential equations that resembles conservation of sediment for the series of transects. The model is synthesized from several shoreline models in the scientific literature: One-line model formulations (Pelnard-Considere, 1956; Larson and others, 1997; Vitousek and Barnard, 2015) account for longshore transport, equilibrium shoreline-model formulations (Yates and others, 2009) account for wave-driven cross-shore transport, and equilibrium beach-profile formulations (Bruun, 1954; Davidson-Arnot, 2005; Anderson and others, 2015) account for long-term beach-profile adjustments due to sea-level rise. The model uses an extended Kalman filter data-assimilation method to improve the fit of the model to lidar-derived observed shoreline positions. As with previous studies (Hapke and others, 2006), the available shoreline data are spatially and temporally sparse. The data-assimilation method automatically adjusts model parameters and estimates the effects of unresolved processes such as natural and anthropogenic sediment supply. The data-assimilation method used in CoSMoS-COAST has been improved over the original method of Long and Plant (2012). The new method ensures that the coefficients of the equilibrium shoreline-change model retain their preferred sign. Without this improvement, the data-assimilation method was subject to instability. Data assimilation is performed only on days of the simulations where shoreline data are observed. For the shoreline projection period (2015–2100), no such data are available and thus no data-assimilation can be performed. Some of the model components are ignored for certain transects and geographic locations. For example, on small pocket beaches longshore transport is assumed negligible and, therefore, is not computed via the model. Generally, projections were not made at transects where the shoreline is armored and sandy beaches are not present. The formulations that comprise the shoreline model are only valid for sandy beaches. Furthermore, they become invalid as the beach becomes fully eroded and possibly undermines coastal infrastructure. Hence, we have specified a maximally eroded shoreline state that represents the interface of sandy beaches and coastal infrastructure (for example, roads, homes, buildings, sea-walls). If the beach erodes to this line, then it is not permitted to erode further. However, we note that the model can be run without specifying this unerodible line. The shoreline model uses a series of global-to-local nested wave models (such as WaveWatch III and SWAN) forced with Global Climate Model (GCM)-derived wind fields. Historical and projected time series of daily maximum wave height and corresponding wave period and direction from 1990 to 2100 force the shoreline model. The modeled wave predictions are a key input to the CoSMoS-COAST shoreline model because the calculation of both the longshore sediment-transport rate (obtained via the "CERC" equation developed by the Army Corp of Engineers; Shore Protection Manual, 1984) and equilibrium shoreline change (Yates and others, 2009) critically depends on the wave conditions. Notably, variations in nearshore wave angle can significantly affect the calculation of longshore transport. Thus, high-resolution modeling efforts to predict nearshore wave conditions are integral components of the shoreline modeling. Sea level vs. time curves are modeled as a quadratic function. Coefficients of the quadratic curves are obtained via three equations: (1) present sea level is assumed to be at zero elevation, (2) the present rate of sea-level rise is assumed to be 3 mm/yr, which is consistent with values observed at local tide gages, (3) future sea-level elevation at 2100 is either 0.93, 1.25, 1.5, 1.75, 2.0 or 5.0 m based on the scenarios considered. We note that sea level only affects the equilibrium-profile changes derived via the Anderson and others (2015) model. The model uses a forward Euler time-stepping method with a daily time step. The longshore sediment-transport term has the option of using a second-order, implicit time-stepping method (Vitousek and Barnard 2015). However, for these modeling efforts, the forward Euler time-stepping method is sufficient and does not violate numerical stability determined by the Courant-Friedrichs-Lewy CFL condition when using a daily time step on 100 m-spaced transects. The model is composed of numerous scripts and functions implemented in Matlab. The main modeling routines have approximately 1,000-plus lines of code. However, many other functions exist that are necessary to initialize and operate the model. Overall the entire shoreline-modeling system is estimated to have approximately 10,000 lines of code. The modeling system is computationally efficient in comparison to traditional coupled hydrodynamic-wave-morphology models like Delft3D. Century-scale simulations for the entire 400 km coast of Southern California take approximately 20–30 minutes of wall-clock time. This limited computational cost allows the possibility of applying ensemble prediction. Significant uncertainty is associated with the process noise of the model and unresolved coastal processes. This makes estimation of uncertainty difficult. The uncertainty bands predicted here represent 95 percent confidence bands associated with the modeled shoreline fluctuations. Unresolved processes are not accounted for in the uncertainty bands and could lead to significantly more uncertainty than reported in these predictions. These results should be considered preliminary. Although some QA/QC has been completed, the results will improve through time as 1) more shoreline data become available to the data-assimilation method, 2) the models are improved, and 3) ensemble wave-forcing is applied to the model. For more information on model details, data sources, and integration with other parts of the CoSMoS framework, see CoSMoS_3.0_Phase_2_Southern_California_Bight:_Summary_of_data_and_methods (available at https://www.sciencebase.gov/catalog/file/get/57f1d4f3e4b0bc0bebfee139?name=CoSMoS_SoCalv3_Phase2_summary_of_methods.pdf).

This part of the data release presents a digital elevation model (DEM) derived from bathymetry and topography data of the Elwha River delta collected in February 2016. Two dams on the Elwha River, Washington State, USA trapped over 20 million m3 of sediment, reducing downstream sediment fluxes and contributing to erosion of the river's coastal delta. The removal of the Elwha and Glines Canyon dams between 2011 and 2014 induced massive increases in river sediment supply and provided an unprecedented opportunity to examine the response of a delta system to changes in sediment supply. The U.S. Geological Survey developed an integrated research program aimed at understanding the ecosystem responses following dam removal that included regular monitoring of coastal and nearshore bathymetry and topography. As part of this monitoring program, the USGS conducted a bathymetric and topographic survey in the Strait of Juan de Fuca on the Elwha River delta, Washington (USGS Field Activity Number 2016-608-FA). Bathymetry data were collected using two personal watercraft (PWCs) and a kayak, each equipped with single beam echosounders and survey-grade global navigation satellite systems (GNSS). Topography data were collected on foot with GNSS receivers mounted on backpacks. DEM surfaces were produced from all available elevation data using linear interpolation.

This portion of the data release presents sediment grain-size data from samples collected on the Elwha River delta, Washington, in February 2016. Surface sediment was collected from 83 locations using a small ponar, or 'grab' sampler from the R/V Frontier in water depths between 17 and 1 m around the delta. An additional 18 samples were collected by hand at low tide. A handheld global satellite navigation system (GNSS) receiver was used to determine the locations of sediment samples. The grain size distributions of suitable samples were determined using standard techniques developed by the USGS Pacific Coastal and Marine Science Center sediment lab. Grab samples that yielded less than 50 g of sediment were omitted from analysis and are classified as "no sample". The grain-size data are provided in a comma-delimited spreadsheet (.csv).

This part of the data release presents topography data from the Elwha River delta collected in February 2016. Topography data were collected on foot with global navigation satellite system (GNSS) receivers mounted on backpacks.

Profiles of salinity, temperature, turbidity, and particle size distribution were collected by the U.S. Geological Survey (USGS) Pacific Coastal and Marine Science Center at two locations in south San Francisco Bay. Data were collected at depth intervals ranging between 0.5 and 2 m (depending on total water depth); sensors remained at each depth for 1 minute. Each profile was collected from surface to bed, and the near-surface region was sampled again at the end of the profile to check steady-state conditions. Profiles were collected for 4 days, for about 7.75 hours each day: Jul 21, 22, 24, and 28, 2020. Data files are grouped by site (channel or shallows) and by instrument (CTD or LISST). Users are advised to assess data quality carefully, and to check metadata for instrument information.

Hydrodynamic and sediment transport time-series data, including water depth, velocity, turbidity, suspended particle size, conductivity, and temperature, were collected by the U.S. Geological Survey (USGS) Pacific Coastal and Marine Science Center at two locations in south San Francisco Bay. Data were collected in the channel (one platform) and in the shallows (three co-located platforms) for 2 weeks in July 2020. Data files are grouped by site (channel or shallows). Each site contained instrumentation to collect the data listed, with slight instrument and setup variations between the two sites due to logistics. Users are advised to assess data quality carefully, and to check metadata for instrument information, as platform deployment times and data-processing methods varied.

This part of DS 781 presents fault data for the geologic and geomorphic map of the Offshore of Point Conception Map Area, California. The vector data file is included in "Faults_OffshorePointConception.zip," which is accessible from https://doi.org/10.5066/F7QN64XQ. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Hartwell, S.R., Golden, N.E., Kvitek, R.G., and Davenport, C.W. (S.Y. Johnson and S.A. Cochran, eds.), 2018, California State Waters Map Series—Offshore of Point Conception, California: U.S. Geological Survey Open-File Report 2018–1024, pamphlet 36 p., 9 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20181024.

This part of DS 781 presents fold data for the geologic and geomorphic map of the Offshore of Point Conception Map Area, California. The vector data file is included in "Folds_OffshorePointConception.zip," which is accessible from https://doi.org/10.5066/F7QN64XQ. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Hartwell, S.R., Golden, N.E., Kvitek, R.G., and Davenport, C.W. (S.Y. Johnson and S.A. Cochran, eds.), 2018, California State Waters Map Series—Offshore of Point Conception, California: U.S. Geological Survey Open-File Report 2018–1024, pamphlet 36 p., 9 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20181024.

This part of DS 781 presents fault data for the geologic and geomorphic map of the Offshore of Gaviota map area, California. The vector data file is included in "Faults_OffshoreGaviota.zip," which is accessible from https://doi.org/10.5066/F7TH8JWJ. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Hartwell, S.R., Golden, N.E., Kvitek, R.G., and Davenport, C.W. (S.Y. Johnson and S.A. Cochran, eds.), 2018, California State Waters Map Series—Offshore of Gaviota, California: U.S. Geological Survey Open-File Report 2018–1023, pamphlet 41 p., 9 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20181023. The southwest-striking south strand of the Santa Ynez fault obliquely cuts the shelf in the western part of the map area. As mapped onshore by Dibblee (1950, 1988a) this fault is unique among Santa Barbara fold belt structures in that it obliquely crosses the Santa Ynez Mountains and the dominant east-west structural grain. The fault was difficult to map in the offshore, even with our dense seismic-reflection data coverage, because the pre-LGM section on the shelf includes massive "reflection free" zones, probably associated with gas or steep dips, and the adjacent slope is mainly underlain by massive to chaotic seismic facies of the Conception Fan. References Cited: Dibblee, T.W., 1988a, Geologic map of the Solvang and Gaviota quadrangles, Santa Barbara County, California, edited by H.E. Ehrenspeck (1988): Dibblee Geological Foundation, Map DF-16, scale 1:24,000. Dibblee, T.W., Jr., 1950, Geology of southwestern Santa Barbara County, California, Point Arguello, Lompoc, Point Conception, Los Olivos, and Gaviota quadrangles: California Division of Mines and Geology Bulletin 150, 95 p., scale 1:62,500.

This part of DS 781 presents fold data for the geologic and geomorphic map of the Offshore of Gaviota map area, California. The vector data file is included in "Folds_OffshoreGaviota.zip," which is accessible from https://doi.org/10.5066/F7TH8JWJ. In the offshore part of the map area, closely-spaced seismic-reflection profiles image many shallow, west-northwest striking folds that have variable geometry, length, amplitude, continuity, and wavelength. The two longest folds, the 17-km-long Molino anticline and the 22-km-long Government Point syncline, are truncated by the south strand of the Santa Ynez fault to the west and east, respectively. These regionally extensive folds and many shorter, west-trending structures are probably rooted in blind thrusts and backthrusts in the hanging wall above the Pitas Point-North Channel fault system.

This portion of the data release contains image mosaics generated using digitized 1:24K natural color photographs collected in June 2000 by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS). These four image mosaics have 1.0 meter-per-pixel resolution, and intermittently cover approximately 53 km (33 mi) of shallow, coastal waters along the west, Kona coast, of the island of Hawai'i, including (from north to south) the Kawaihae, Waikoloa, Kukio, and Kailua-Kona areas. Each digital image mosaic area is downloadable as a separate zip file (area_1m.zip) that contains two versions of the image mosaic--one with and one without a lidar bathymetry shaded-relief image digitally combined with the aerial photography mosaic results. The shaded-relief image was derived using airborne SHOALS (Scanning Hydrographic Operational Lidar Survey) lidar (LIght Detection And Ranging) data collected for the U.S. Geological Survey (USGS) by the U.S. Army Corp of Engineers (USACE) in April 1999. Also included in each zip file is a lower-resolution 'browse' graphic of each image mosaic and associated metadata.

This portion of the data release contains an image mosaic generated using digitized 1:35K natural color photographs collected in September 1993 by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS) of the Napili-Honokowai area along the northwest coast of Maui. The area is downloadable as a zip file (napili_honokowai_1m.zip) and includes a high-resolution (1.0 meter per pixel) digital image mosaic, as well as a lower-resolution 'browse' image and associated metadata.

This portion of the data release contains digital image mosaics along the southeast coast of O'ahu. Digital mosaics at 1-foot (0.3048-meter) resolution, including the areas of Waikiki, Diamond Head, Wai'alae, Maunalua Bay, and Portlock, were generated from 1:10K aerial photography and are presented in one zip file (oahu_1ft.zip) that also contains lower-resolution 'browse' graphics of each image mosaic area, as well as associated metadata. All of the digital image areas (from Waikiki to Portlock) were combined into one large digital mosaic at 1-meter resolution, which is presented in another zip file (oahu_1m.zip) that includes a 'browse' graphic of the image mosaic area and associated metadata. The 1-meter resolution digital image mosaic was also combined with lidar bathymetry data to create a shaded-relief image, which is presented in a third zip file (oahu_1m_shaded.zip), along with a 'browse' graphic of the image mosaic area and associated metadata.

This portion of the data release contains digital image mosaics along the south coast of Moloka'i. Digital mosaics at 1-foot (0.3048-meter) resolution, including the areas of Pala'au, Umipa'a, Kaunakakai, Kamiloloa, Kawela, Kamalo, and Kalaeloa, were generated from 1:10K aerial photography, and are presented in one zip file (molokai_1ft.zip) that also contains lower-resolution 'browse' graphics of each image-mosaic area, as well as associated metadata. Digital mosaics at 1-meter resolution, including the areas of La'au Point, Hale O Lono, Waiakane, Pala'au, Kaunakakai, Kamiloloa, Kawela, Kamalo, and Puko‘o, were generated from 1:35K aerial photography, and are presented in a second zip file (molokai_1m.zip) that also contains 'browse' graphics of each image mosaic area, as well as associated metadata. Several of the 1-meter-resolution images have been merged together and combined with lidar bathymetry data to create three large shaded-relief images along the southwest (Waiakane to Pala'au), southcentral (Pala'au to Kawela), and southeast (Kawela to Puko'o) coasts of Moloka'i. These shaded-relief images are presented in a third zip file (molokai_1m_shaded.zip), along with 'browse' graphics of each image mosaic area and associated metadata.

These data present suspended particle size distributions collected by the U.S. Geological Survey (USGS) Pacific Coastal and Marine Science Center at three locations in the Sacramento-San Joaquin Delta. Data were collected in Lindsey Slough on April 4 and April 18, 2017, and near the mouth of the Mokelumne River and in Middle River on March 14, 2018 by deploying a Sequoia Scientific Laser In-situ Scattering and Transmissometry instrument (LISST 100x) from a small vessel during the deployment of the hydrographic time series data instruments. At each site, data were collected 1 to 2 times, generally near the water surface, at mid depth, and near the sediment bed. These data were collected as part of a study on the effects of invasive aquatic vegetation on sediment transport in the Sacramento-San Joaquin Delta. Users are advised to check metadata and instrument information carefully for applicable time periods of specific data.

Time series data of water surface elevation, wave height, and water column currents and temperature were acquired at seven locations for 86 days off of Waiakane on the south coast of the island of Molokai, Hawaii, in support of a study on the coastal circulation patterns and the transformation of surface waves over the coral reefs.

This dataset includes raw and processed, high-resolution seismic-reflection data collected in 2009 to explore a possible connection between the San Diego Trough Fault and the San Pedro Basin Fault. The survey is in the San Pedro Basin between Santa Catalina Island and San Pedro, California. The data were collected aboard the U.S. Geological Survey R/V Parke Snavely. The seismic-reflection data were acquired using an EdgeTech 512 chirp subbottom profiler. Subbottom acoustic penetration spanned tens to about 50 meters, variable by location.

This dataset includes reprocessed boomer 3D seismic data collected by the Fugro Consultants Inc. in 2012, offshore Point Sal, central California.

This dataset includes raw, and swell-filtered, high-resolution seismic-reflection data, collected by the U.S. Geological Survey (USGS) in 2011, between Point Sur and Morro Bay in central California.

This dataset includes reprocessed boomer 3D seismic data collected by the Fugro Consultants Inc. in 2012, in San Luis Obispo Bay, offshore of Pismo Beach, central California.

This dataset includes raw and processed, high-resolution seismic-reflection data collected in 2008 to collect information on active offshore faults. The survey area is offshore southern California between Huntington Beach and San Diego. The data were collected aboard the R/V Bold. The seismic-reflection data were acquired using a SIG 2mille minisparker. Subbottom acoustic penetration spanned tens to several hundreds of meters, variable by location.

This dataset includes raw and processed, high-resolution seismic-reflection data collected in 2010 to collect information on active offshore faults. The survey area is offshore southern California between Oceanside and La Jolla. The data were collected aboard the U.S. Geological Survey R/V Parke Snavely. The seismic-reflection data were acquired using a SIG 2mille minisparker. Subbottom acoustic penetration spanned tens to several hundreds of meters, variable by location.

This dataset includes reprocessed boomer 3D seismic data collected by the Fugro Consultants Inc. in 2012, in Estero Bay, offshore of Morro Bay, central California.

This dataset includes raw and processed, high-resolution seismic-reflection data collected in 2011 to collect information on active offshore faults. The survey area is offshore southern California between Long Beach and San Diego. The data were collected aboard the U.S. Geological Survey R/V Parke Snavely. The seismic-reflection data were acquired using a SIG 2mille minisparker system. Subbottom acoustic penetration spanned tens to several hundreds of meters, variable by location and equipment type.

This dataset includes raw and processed, high-resolution seismic-reflection data collected in 2010 to collect information on active offshore faults. The survey is area is offshore southern California between Oceanside and La Jolla. The data were collected aboard the U.S. Geological Survey R/V Parke Snavely. The seismic-reflection data were acquired using an EdgeTech 512 chirp subbottom profiler. Subbottom acoustic penetration spanned tens to about 50 meters, variable by location.

This dataset includes raw and processed, high-resolution seismic-reflection data collected in 2011 to collect information on active offshore faults. The survey area is offshore southern California between Long Beach and San Diego. The data were collected aboard the U.S. Geological Survey R/V Parke Snavely. The seismic-reflection data were acquired using an EdgeTech 512 subbottom profiler. Subbottom acoustic penetration spanned tens to about 50 meters, variable by location.

A seamless, three-meter digital elevation model (DEM) was constructed for the entire Southern California coastal zone, extending 473 km from Point Conception to the Mexican border. The goal was to integrate the most recent, high-resolution datasets available (for example, Light Detection and Ranging (Lidar) topography, multibeam and single beam sonar bathymetry, and Interferometric Synthetic Aperture Radar (IfSAR) topography) into a continuous surface from at least the 20-m isobath to the +20-m elevation contour.

A seamless, 2 meter resolution digital elevation model (DEM) was constructed for the open-coast region of the San Francisco Bay Area (outside of the Golden Gate Bridge), extending from Half Moon Bay to Bodega Head along the north-central California coastline. The goal was to integrate the most recent high-resolution bathymetric and topographic datasets available (for example, Light Detection and Ranging (lidar) topography, multibeam and single-beam sonar bathymetry) into a seamless surface model extending offshore at least 3 nautical miles and inland beyond the +20 m elevation contour.

A GIS polygon shapefile outlining the extent of the 14 individual DEM sections that comprise the seamless, 2-meter resolution DEM for the open-coast region of the San Francisco Bay Area (outside of the Golden Gate Bridge), extending from Half Moon Bay to Bodega Head along the north-central California coastline. The goal was to integrate the most recent high-resolution bathymetric and topographic datasets available (for example, Light Detection and Ranging (lidar) topography, multibeam and single-beam sonar bathymetry) into a seamless surface model extending offshore at least 3 nautical miles and inland beyond the +20 meter elevation contour.

A GIS polygon shapefile outlining the extent of small lakes or ponds within the terrain that were assigned a hydo-flattened elevation during lidar post-processing. DEM elevations within these small areas reflect water surface elevations, not bathymetric elevations.

A GIS polygon shapefile outlining the boundaries of the native input datasets used to construct a seamless, 2-meter resolution digital elevation model (DEM) was constructed for the open-coast region of the San Francisco Bay Area (outside of the Golden Gate Bridge), extending from Half Moon Bay to Bodega Head along the North-central California coastline. The goal was to integrate the most recent high-resolution bathymetric and topographic datasets available (for example, Light Detection and Ranging (lidar) topography, multibeam and single-beam sonar bathymetry) into a seamless surface model extending offshore at least 3 nautical miles and inland beyond the +20 m elevation contour.

Bathymetric contours (contour interval 100 m) of the continental margin offshore of Washington, Oregon, and California (cowbat) were compiled from various sources available in the late 1980s and used to construct 1:1,000,000-scale maps (Chase and others, 1992a, 1992b; Grim and others, 1992). The contours range from 200 to 5300 m depth.

Cowbatg.tif is a 1000-m resolution bathymetric grid of the continental margin offshore of Washington, California, and Oregon. The grid was generated from bathymetric contours (cowbathy.shp, also in this data set) mapped by Chase and others (1992a, b) and by Grim and others (1992) from various sources of bottom topography of the continental margin off the states of Washington, Oregon, and California.

Digital vector data for the contours of depth to basement for the deep-sea basins of the Pacific continental margin offshore of Washington, Oregon, and California. The data were interpreted from GLORIA (Paskevich and others, 2011) sidescan data and related seismic-reflection data. The data were published as USGS maps in paper format (Gardner and others, 1992, 1993a, 1993b).

COWBSMG is a 1000-m resolution grid of depth to basement off of Washington, Oregon, and California constructed from depth to basement contour data (cowbsm.shp, also in this data set) from 1:1,000,000-scale maps (Gardner and others, 1992, 1993a, 1993b). The range in depth to basement in this region is -5582 to -985 m with a mean of -3817 m.

Cowthkg.tif is a 1000-m resolution grid of sediment thickness derived from contours (cowiso.shp, also in this data set) from 1:1,000,000-scale Map Showing Sediment Isopachs in the Deep-sea Basins of the Pacific Continental Margin, Strait of Juan de Fuca to Point Loma, California (Gardner and others, 1992, 1993a, 1993b). The maximum sediment thickness in this region is 2342 m with a mean value of 359 m.

Contours of sediment thickness for the deep-sea basins of the Pacific continental margin offshore of Washington, Oregon, and California were were interpreted from GLORIA (Paskevich and others, 2011) sidescan imagery and related seismic-reflection data and were published as maps in paper format (Gardner and others, 1992, 1993a, 1993b).

Multibeam bathymetry data were collected along the Queen Charlotte-Fairweather Fault between Icy Point and Dixon Entrance, offshore southeastern Alaska from 2016-05-17 to 2016-06-12. Data were collected aboard the Alaska Department of Fish and Game R/V Medeia using a Reson SeaBat 7160 multibeam echosounder, Reson 7k Control Center, and HYPACK. This data release contains approximately 4,600 square kilometers of multibeam bathymetry and backscatter data, organized into zip files for each Julian Day of the survey.

Meteorological data, including wind speed, wind direction, air temperature, relative humidity, and air pressure, were collected by the U.S. Geological Survey (USGS) Pacific Coastal and Marine Science Center at a site located in Grizzly Bay, California. A Vaisala WXT530 meteorological station was mounted atop of a dolphin-type mooring structure, from January to June 2020. The data were truncated based on deployment and recovery times of hydrodynamic time-series data, spurious data points from the wind sensor were removed, and the file was written to netCDF. Spurious points were identified based on a recorded wind speed of 0. These points were set to NaN (Not a Number). Users are advised to assess data quality carefully, and to check metadata for additional instrument information.

This data layer (PAC_PRS.txt) is one of five point coverages of known sediment samples, inspections, and probes from the usSEABED data collection for the U.S. Pacific continental margin integrated using the dbSEABED software system. This data layer represents the parsed (PRS) output of the dbSEABED mining software. It contains the numeric results parsed from text-based descriptions held in the data resource files (DRF). Because it relies on descriptions, the PRS data are less precise than the extracted data (PAC_EXT), but may include information on outsized elements and consolidation that are often not in lab-analyzed data. This file contains the same data fields as the extracted (PAC_EXT) and calculated (PAC_CLC) data files, and the three files may be combined.

ArcInfo GRID format data generated from the 2004 multibeam sonar survey of the Northeastern Channel Islands, CA Region. The data include high-resolution bathymetry.

This portion of the data release presents sediment deposition in the estuary as measured using rod surface elevation tables (RSETs) at fifteen locations throughout the Elwha River estuary, Washington, from August 2011 to June 2014 (no associated USGS Field Activities numbers because data were collected predominantly by biologists from the Lower Elwha Klallam Tribe). The locations of the RSETs were determined with a hand-held global positioning system (GPS). We measured sediment deposition from 2011 to 2013 using the RSET table and pins at 36 points around each RSET. Because of extensive sediment deposition in the estuary, we needed to modify our methodology in 2014. We fabricated a new attachment for the RSET base that consisted of a 30 cm horizontal measuring rod and level, which replaced the RSET table. We leveled the rod with respect to the RSET receiver and measured the distance from the end of the rod to the sediment surface at six locations around the center point using a weighted line. The two methods were calibrated so that measurements were comparable. Measurements were taken approximately every two months in 2011 and 2012 and before and after the rainy and freshet (snowmelt) seasons in 2013 and 2014. The sediment deposition data are provided in a comma-delimited spreadsheet (.csv).

This portion of the data release presents sediment grain-size data from samples collected in the Elwha River estuary, Washington, in July 2013 and June 2014 (USGS Field Activities L-15-13-PS and 2014-628-FA). Surface sediment was collected from one location in 2013 and five locations in 2014 using a using a push core. The locations of grab samples were determined with a hand-held global positioning system (GPS). The cores were split into one- to three-centimeter sections. The grain-size distributions of samples were determined using standard techniques developed by the USGS Pacific Coastal and Marine Science Center sediment lab. Size fractions are defined as gravel (greater than 2 mm), sand (63 micron to 2 mm), silt (4 micron to 63 micron), clay (less than 4 micron), and mud (less than 63 micron). The grain-size data are provided in a comma-delimited spreadsheet (.csv).

This portion of the data release presents aquatic invertebrate abundance data from samples collected in the Elwha River estuary, Washington, in 2007 and 2013 (no associated USGS Field Activities numbers because data were collected predominantly by biologists from the Lower Elwha Klallam Tribe). Replicate benthic samples were collected at 18 locations throughout the estuary complex using a petite Ponar grab sampler (appx. 2400 mL sample) and sorted through a 500-micron sieve. Samples were fixed in 10 percent formalin for 3 to 5 days before being transferred to 70 percent ethanol until processing. Individuals were identified to the lowest possible taxonomic resolution, but are grouped according to insect Orders in the data for consistency (unless otherwise noted in the attributes). The locations of samples were determined with a hand-held global positioning system (GPS). Aquatic invertebrate abundance data (including fractions of individuals) are provided in a comma-delimited spreadsheet (.csv).

Time-series data of velocity, pressure, turbidity, conductivity, and temperature were collected near the mouth of the Elwha River, Washington, USA, from December 2010 through October 2014, for the Department of Interior’s Elwha River Restoration project. As part of this project, the U.S. Geological Survey studied the effects of renewed sediment supplies on the coastal ecosystems before, during, and following the removal of two dams, Elwha and Glines Canyon, from the Elwha River. Removal of the dams reintroduced sediment stored in the reservoirs to the river, and the river moved much of this sediment to the coast. Several benthic tripods were instrumented with oceanographic sensors to collect the time-series data. Initial deployment in December 2010 consisted of one tripod about 1 km east of the Elwha River mouth (Tripod A). In March of 2011, an identical tripod (Tripod B) was placed about 1 km west of the river mouth. A mooring was added to the western site in July 2012 to measure turbidity and conductivity near the surface.  A third tripod was placed in deeper water (50 m) directly offshore of the river mouth in an attempt to characterize sediment gravity flows near the seafloor if they occurred (Tripod C). Exceptional sedimentation was observed near the original tripod site A during the winter of 2013-2014. As a result, the tripod was relocated further east in April 2013 and renamed Tripod D. Please check metadata and instrument information carefully for applicable time periods of specific data, as individual instrument deployment times and duration of the time series vary. The naming convention for the NetCDF files included in this release is a 12-character alphanumeric code (ELWYYJKLNNXX.nc) where: ELW is a 3-digit alphabetic-code for this experiment located at the mouth of the Elwha River YY is the 2-digit year at the time of deployment J is the location with respect to the river mouth [A, East (December 2010 to April 2013); B, West; C, Offshore; D, East (April 2013 to March 2014)] K is the deployment number (1-9; beginning and ending dates of each deployment are given below) L is the instrument package type (T, tripod; M, surface mooring) NN indicates the position of instrument on the surface mooring (01, nearest the surface; NN increases with depth) XX denotes the instrument or data type (wh, RDInstruments ADCP current data; wv, RDInstruments ADCP derived wave parameters; nx, Falmouth Scientific NXIC CTD; aq, Aquatec Aqualogger OBS; bl, RBR, Ltd CTD; sc, SeaBird Electonics SBE16+ CT) Some derived parameters are included in these data. Deployment dates: 1. Dec 2010 to Mar 2011 2. Mar 2011 to Sep 2011 3. Sep 2011 to Mar 2012 4. Mar 2012 to Aug 2012 5. Aug 2012 to Jan 2013 6. Jan 2013 to Jun 2013 7. Jun 2013 to Dec 2013 8. Dec 2013 to Mar 2014 9. Mar 2014 to Oct 2014

This part of DS 781 presents data for the acoustic-backscatter map of Drakes Bay and Vicinity, California. Backscatter data are provided as separate grids depending on mapping system or processing method. The raster data file is included in "BackscatterA_8101_DrakesBay.zip", which is accessible from https://pubs.usgs.gov/ds/781/DrakesBay/data_catalog_DrakesBay.html. These data accompany the pamphlet and map sheets of Watt, J.T., Dartnell, P., Golden, N.E., Greene, H.G., Erdey, M.D., Cochrane, G.R., Johnson, S.Y., Hartwell, S.R., Kvitek, R.G., Manson, M.W., Endris, C.A., Dieter, B.E., Sliter, R.W., Krigsman, L.M., Lowe, E.N., and Chin, J.L. (J.T. Watt and S.A. Cochran, eds.), 2015, California State Waters Map Series—Drakes Bay and Vicinity, California: U.S. Geological Survey Open-File Report 2015–1041, pamphlet 36 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20151041. The acoustic-backscatter map of the Drakes Bay and Vicinity map area, California, was generated from backscatter collected by California State University, Monterey Bay (CSUMB), and by Fugro Pelagos. Mapping was completed between 2007 and 2010, using a combination of 200-kHz and 400-kHz Reson 7125, and 244-kHz Reson 8101 multibeam echosounders, as well as 468-kHz SEA SWATHPlus interferometric system. These mapping missions combined to collect backscatter data from about the 10-m isobath to beyond the 3-nautical-mile limit of California's State Waters. Within the acoustic-backscatter imagery, brighter tones indicate higher backscatter intensity, and darker tones indicate lower backscatter intensity. The intensity represents a complex interaction between the acoustic pulse and the seafloor, as well as characteristics within the shallow subsurface, providing a general indication of seafloor texture and composition. Backscatter intensity depends on the acoustic source level; the frequency used to image the seafloor; the grazing angle; the composition and character of the seafloor, including grain size, water content, bulk density, and seafloor roughness; and some biological cover. Harder and rougher bottom types such as rocky outcrops or coarse sediment typically return stronger intensities (high backscatter, lighter tones), whereas softer bottom types such as fine sediment return weaker intensities (low backscatter, darker tones). These data are not intended for navigational purposes.

This part of DS 781 presents data for the acoustic-backscatter map of Drakes Bay and Vicinity, California. Backscatter data are provided as separate grids depending on mapping system or processing method. The raster data file is included in "BackscatterB_Swath_DrakesBay.zip", which is accessible from https://pubs.usgs.gov/ds/781/DrakesBay/data_catalog_DrakesBay.html. These data accompany the pamphlet and map sheets of Watt, J.T., Dartnell, P., Golden, N.E., Greene, H.G., Erdey, M.D., Cochrane, G.R., Johnson, S.Y., Hartwell, S.R., Kvitek, R.G., Manson, M.W., Endris, C.A., Dieter, B.E., Sliter, R.W., Krigsman, L.M., Lowe, E.N., and Chin, J.L. (J.T. Watt and S.A. Cochran, eds.), 2015, California State Waters Map Series—Drakes Bay and Vicinity, California: U.S. Geological Survey Open-File Report 2015–1041, pamphlet 36 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20151041. The acoustic-backscatter map of Drakes Bay and Vicinity map area, California, was generated from backscatter collected by California State University, Monterey Bay (CSUMB), and by Fugro Pelagos. Mapping was completed between 2007 and 2010, using a combination of 200-kHz and 400-kHz Reson 7125, and 244-kHz Reson 8101 multibeam echosounders, as well as 468-kHz SEA SWATHPlus interferometric system. These mapping missions combined to collect backscatter data from about the 10-m isobath to beyond the 3-nautical-mile limit of California's State Waters. Within the acoustic-backscatter imagery, brighter tones indicate higher backscatter intensity, and darker tones indicate lower backscatter intensity. The intensity represents a complex interaction between the acoustic pulse and the seafloor, as well as characteristics within the shallow subsurface, providing a general indication of seafloor texture and composition. Backscatter intensity depends on the acoustic source level; the frequency used to image the seafloor; the grazing angle; the composition and character of the seafloor, including grain size, water content, bulk density, and seafloor roughness; and some biological cover. Harder and rougher bottom types such as rocky outcrops or coarse sediment typically return stronger intensities (high backscatter, lighter tones), whereas softer bottom types such as fine sediment return weaker intensities (low backscatter, darker tones). These data are not intended for navigational purposes.

This part of DS 781 presents data for the acoustic-backscatter map of Drakes bay and Vicinity map area, California. Backscatter data are provided as separate grids depending on mapping system or processing method. The raster data file is included in "BackscatterC_7125_DrakesBay.zip", which is accessible from https://pubs.usgs.gov/ds/781/DrakesBay/data_catalog_DrakesBay.html. The acoustic-backscatter map of Drakes Bay and Vicinity map area, California, was generated from backscatter collected by California State University, Monterey Bay (CSUMB), and by Fugro Pelagos. Mapping was completed between 2007 and 2010, using a combination of 200-kHz and 400-kHz Reson 7125, and 244-kHz Reson 8101 multibeam echosounders, as well as 468-kHz SEA SWATHPlus interferometric system. These mapping missions combined to collect backscatter data from about the 10-m isobath to beyond the 3-nautical-mile limit of California's State Waters. Within the acoustic-backscatter imagery, brighter tones indicate higher backscatter intensity, and darker tones indicate lower backscatter intensity. The intensity represents a complex interaction between the acoustic pulse and the seafloor, as well as characteristics within the shallow subsurface, providing a general indication of seafloor texture and composition. Backscatter intensity depends on the acoustic source level; the frequency used to image the seafloor; the grazing angle; the composition and character of the seafloor, including grain size, water content, bulk density, and seafloor roughness; and some biological cover. Harder and rougher bottom types such as rocky outcrops or coarse sediment typically return stronger intensities (high backscatter, lighter tones), whereas softer bottom types such as fine sediment return weaker intensities (low backscatter, darker tones). These data are not intended for navigational purposes.

This part of DS 781 presents data for the shaded-relief bathymetry map of Drakes Bay and Vicinity, California (raster data file is included in "BathymetryHS_DrakesBay.zip," which is accessible from https://pubs.usgs.gov/ds/781/DrakesBay/data_catalog_DrakesBay.html. These data accompany the pamphlet and map sheets of Watt, J.T., Dartnell, P., Golden, N.E., Greene, H.G., Erdey, M.D., Cochrane, G.R., Johnson, S.Y., Hartwell, S.R., Kvitek, R.G., Manson, M.W., Endris, C.A., Dieter, B.E., Sliter, R.W., Krigsman, L.M., Lowe, E.N., and Chin, J.L. (J.T. Watt and S.A. Cochran, eds.), 2015, California State Waters Map Series—Drakes Bay and Vicinity, California: U.S. Geological Survey Open-File Report 2015–1041, pamphlet 36 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20151041. The shaded-relief bathymetry map of Drakes Bay and Vicinity, California, was generated from bathymetry data collected by California State University, Monterey Bay (CSUMB), and by Fugro Pelagos. Mapping was completed between 2007 and 2010, using a combination of 200-kHz and 400-kHz Reson 7125, and 244-kHz Reson 8101 multibeam echosounders, as well as 468-kHz SEA SWATHPlus interferometric system. These mapping missions combined to collect bathymetry from about the 10-m isobath to beyond the 3-nautical-mile limit of California's State Waters.

This part of DS 781 presents data for the bathymetric contours for several seafloor maps of the Drakes Bay and Vicinity map area, California. The vector data file is included in "Contours_DrakesBay.zip," which is accessible from https://pubs.usgs.gov/ds/781/DrakesBay/data_catalog_DrakesBay.html. These data accompany the pamphlet and map sheets of Watt, J.T., Dartnell, P., Golden, N.E., Greene, H.G., Erdey, M.D., Cochrane, G.R., Johnson, S.Y., Hartwell, S.R., Kvitek, R.G., Manson, M.W., Endris, C.A., Dieter, B.E., Sliter, R.W., Krigsman, L.M., Lowe, E.N., and Chin, J.L. (J.T. Watt and S.A. Cochran, eds.), 2015, California State Waters Map Series—Drakes Bay and Vicinity, California: U.S. Geological Survey Open-File Report 2015–1041, pamphlet 36 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20151041. 10-m interval contours of the Drakes Bay and Vicinity map area, California, were generated from bathymetry data collected by California State University, Monterey Bay (CSUMB) and by Fugro Pelagos. Mapping was completed between 2007 and 2010, using a combination of 200-kHz and 400-kHz Reson 7125, and 244-kHz Reson 8101 multibeam echosounders, as well as 468-kHz SEA SWATHPlus interferometric system. These mapping missions combined to collect bathymetry from about the 10-m isobath to beyond the 3-nautical-mile limit of California's State Waters. Bathymetric contours at 10-m intervals were generated from a bathymetric surface model. The most continuous contour segments were preserved while smaller segments and isolated island polygons were excluded from the final output. Contours were smoothed via a polynomial approximation with exponential kernel (PAEK) algorithm using a tolerance value of 60 m. The contours were then clipped to the boundary of the map area. These data are not intended for navigational purposes.

This part of DS 781 presents data for the geologic and geomorphic map of the Drakes Bay and Vicinity, California. The polygon shapefile is included in "Geology_DrakesBay.zip," which is accessible from https://pubs.usgs.gov/ds/781/DrakesBay/data_catalog_DrakesBay.html. These data accompany the pamphlet and map sheets of Watt, J.T., Dartnell, P., Golden, N.E., Greene, H.G., Erdey, M.D., Cochrane, G.R., Johnson, S.Y., Hartwell, S.R., Kvitek, R.G., Manson, M.W., Endris, C.A., Dieter, B.E., Sliter, R.W., Krigsman, L.M., Lowe, E.N., and Chin, J.L. (J.T. Watt and S.A. Cochran, eds.), 2015, California State Waters Map Series—Drakes Bay and Vicinity, California: U.S. Geological Survey Open-File Report 2015–1041, pamphlet 36 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20151041. Marine geology and geomorphology was mapped in the Drakes Bay and Vicinity map area, California, from approximate Mean High Water (MHW) to the 3-nautical-mile limit of California's State Waters. Offshore geologic units were delineated on the basis of integrated analyses of adjacent onshore geology with multibeam bathymetry and backscatter imagery, seafloor-sediment and rock samples, digital camera and video imagery, and high-resolution seismic-reflection profiles.

This part of DS 781 presents data for part of the acoustic-backscatter map of the Hueneme Canyon and Vicinity map area, California. Backscatter data are provided as separate grids depending on mapping system or processing method. The raster data file is included in "BackscatterA_CSUMB_HuenemeCanyon.zip," which is accessible from https://pubs.usgs.gov/ds/781/HuenemeCanyon/data_catalog_HuenemeCanyon.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Kvitek, R.G., Greene, H.G., Krigsman, L.M., Endris, C.A., Clahan, K.B., Sliter, R.W., Wong, F.L., Yoklavich, M.M., and Normark, W.R. (S.Y. Johnson, ed.), 2012, California State Waters Map Series—-Hueneme Canyon and Vicinity, California: U.S. Geological Survey Scientific Investigations Map 3225, 41 p., 12 sheets, scale 1:24,000, https://pubs.usgs.gov/sim/3225/. The acoustic-backscatter map of Hueneme Canyon and Vicinity map area, California, was generated from backscatter data collected by California State University, Monterey Bay, Seafloor Mapping Lab (CSUMB) and by the U.S. Geological Survey (USGS). This metadata file describes the acoustic-backscatter data collected by CSUMB. See https://pubs.usgs.gov/ds/781/HuenemeCanyon/metadata/BackscatterB_USGS_HuenemeCanyon_metadata.txt for a description of the acoustic-backscatter data collected by the USGS. The majority of the acoustic-backscatter data within the Hueneme Canyon and vicinity, California, map area was collected by CSUMB in the summers of 2006 and 2007, using a 244-kHz Reson 8101 multibeam echosounder. Within the acoustic-backscatter imagery, brighter tones indicate higher backscatter intensity, and darker tones indicate lower backscatter intensity. The intensity represents a complex interaction between the acoustic pulse and the seafloor, as well as characteristics within the shallow subsurface, providing a general indication of seafloor texture and composition. Backscatter intensity depends on the acoustic source level; the frequency used to image the seafloor; the grazing angle; the composition and character of the seafloor, including grain size, water content, bulk density, and seafloor roughness; and some biological cover. Harder and rougher bottom types such as rocky outcrops or coarse sediment typically return stronger intensities (high backscatter, lighter tones), whereas softer bottom types such as fine sediment return weaker intensities (low backscatter, darker tones).

This part of DS 781 presents data for part of the acoustic-backscatter map of the Hueneme Canyon and Vicinity map area, California. Backscatter data are provided as separate grids depending on mapping system or processing method. The raster data file is included in "BackscatterB_USGS_HuenemeCanyon.zip," which is accessible from https://pubs.usgs.gov/ds/781/HuenemeCanyon/data_catalog_HuenemeCanyon.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Kvitek, R.G., Greene, H.G., Krigsman, L.M., Endris, C.A., Clahan, K.B., Sliter, R.W., Wong, F.L., Yoklavich, M.M., and Normark, W.R. (S.Y. Johnson, ed.), 2012, California State Waters Map Series--Hueneme Canyon and Vicinity, California: U.S. Geological Survey Scientific Investigations Map 3225, 41 p., 12 sheets, scale 1:24,000, https://pubs.usgs.gov/sim/3225/. The acoustic-backscatter map of Hueneme Canyon and Vicinity map area, California, was generated from backscatter data collected by California State University, Monterey Bay, Seafloor Mapping Lab (CSUMB) and by the U.S. Geological Survey (USGS). This metadata file describes the acoustic-backscatter data collected by the USGS. See https://pubs.usgs.gov/ds/781/HuenemeCanyon/metadata/BackscatterA_CSUMB_HuenemeCanyon_metadata.txt for a description of the acoustic-backscatter data collected by CSUMB. The far northern part of the Hueneme Canyon and Vicinity, California map area was mapped by the USGS in 2006, using a 117-kHz SEA (AP) Ltd. SWATHplus-M phase-differencing sidescan sonar. This mapping mission collected acoustic-backscatter data from about the 10-m isobath to almost the 3-nautical-mile limit of California's State Waters. Within the acoustic-backscater imagery, brighter tones indicate higher backscatter intensity, and darker tones indicate lower backscatter intensity. The intensity represents a complex interaction between the acoustic pulse and the seafloor, as well as characteristics within the shallow subsurface, providing a general indication of seafloor texture and sediment type. Backscatter intensity depends on the acoustic source level; the frequency used to image the seafloor; the grazing angle; the composition and character of the seafloor, including grain size, water content, bulk density, and seafloor roughness; and some biological cover. Harder and rougher bottom types such as rocky outcrops or coarse sediment typically return stronger intensities (high backscatter, lighter tones), whereas softer bottom types such as fine sediment return weaker intensities (low backscatter, darker tones).

This part of DS 781 present the shaded-relief bathymetry map of the Hueneme Canyon and Vicinity map area, California. The raster data file for the shaded-relief map is included in "BathymetryHS_HuenemeCanyon.zip," which is accessible from https://pubs.usgs.gov/ds/781/HuenemeCanyon/data_catalog_HuenemeCanyon.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Kvitek, R.G., Greene, H.G., Krigsman, L.M., Endris, C.A., Clahan, K.B., Sliter, R.W., Wong, F.L., Yoklavich, M.M., and Normark, W.R. (S.Y. Johnson, ed.), 2012, California State Waters Map Series-—Hueneme Canyon and Vicinity, California: U.S. Geological Survey Scientific Investigations Map 3225, 41 p., 12 sheets, scale 1:24,000, https://pubs.usgs.gov/sim/3225/. The shaded-relief bathymetry map of the Hueneme Canyon and Vicinity map area, California, was generated from bathymetry data collected by California State University, Monterey Bay, Seafloor Mapping Lab (CSUMB), by the U.S. Geological Survey (USGS), and by Fugro Pelagos for the U.S. Army Corps of Engineers (USACE) Joint Lidar Bathymetry Technical Center of Expertise. Most of the offshore area was mapped by CSUMB in the summers of 2006 and 2007, using a 244-kHz Reson 8101 multibeam echosounder. The far northern part of the offshore area was mapped by the USGS in 2006, using a 117-kHz SEA (AP) Ltd. SWATHplus-M phase-differencing sidescan sonar. The nearshore bathymetry and coastal topography were mapped for USACE by Fugro Pelagos in 2009, using the SHOALS-1000T bathymetric-lidar and Leica ALS60 topographic-lidar systems. All these mapping missions combined to collect bathymetry from the 0-m isobath to beyond the 3-nautical-mile limit of California's State Waters.

This part of DS 781 presents data for the bathymetry map of the Hueneme Canyon and Vicinity map area, California. The raster data file for the bathymetry map is included in "Bathymetry_HuenemeCanyon.zip," which is accessible from https://pubs.usgs.gov/ds/781/HuenemeCanyon/data_catalog_HuenemeCanyon.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Kvitek, R.G., Greene, H.G., Krigsman, L.M., Endris, C.A., Clahan, K.B., Sliter, R.W., Wong, F.L., Yoklavich, M.M., and Normark, W.R. (S.Y. Johnson, ed.), 2012, California State Waters Map Series—-Hueneme Canyon and Vicinity, California: U.S. Geological Survey Scientific Investigations Map 3225, 41 p., 12 sheets, scale 1:24,000, https://pubs.usgs.gov/sim/3225/. The bathymetry map of the Hueneme Canyon and Vicinity map area, California, was generated from bathymetry data collected by California State University, Monterey Bay (CSUMB), by the U.S. Geological Survey (USGS), and by Fugro Pelagos for the U.S. Army Corps of Engineers (USACE) Joint Lidar Bathymetry Technical Center of Expertise. Most of the offshore area was mapped by CSUMB in the summers of 2006 and 2007, using a 244-kHz Reson 8101 multibeam echosounder. The far northern part of the offshore area was mapped by the USGS in 2006, using a 117-kHz SEA (AP) Ltd. SWATHplus-M phase-differencing sidescan sonar. The nearshore bathymetry and coastal topography were mapped for USACE by Fugro Pelagos in 2009, using the SHOALS-1000T bathymetric-lidar and Leica ALS60 topographic-lidar systems. These mapping missions combined to collect bathymetry from the 0-m isobath to beyond the 3-nautical-mile limit of California's State Waters.

This part of DS 781 presents data for the bathymetric contours of the Hueneme Canyon and Vicinity map area, California. The vector data file is included in "Contours_HuenemeCanyon.zip," which is accessible from https://pubs.usgs.gov/ds/781/HuenemeCanyon/data_catalog_HuenemeCanyon.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Kvitek, R.G., Greene, H.G., Krigsman, L.M., Endris, C.A., Clahan, K.B., Sliter, R.W., Wong, F.L., Yoklavich, M.M., and Normark, W.R. (S.Y. Johnson, ed.), 2012, California State Waters Map Series—-Hueneme Canyon and Vicinity, California: U.S. Geological Survey Scientific Investigations Map 3225, 41 p., 12 sheets, scale 1:24,000, https://pubs.usgs.gov/sim/3225/. The bathymetry map of Hueneme Canyon and Vicinity map area in southern California was generated from bathymetry data collected by California State University, Monterey Bay (CSUMB), by the U.S. Geological Survey (USGS), and by Fugro Pelagos for the U.S. Army Corps of Engineers (USACE) Joint Lidar Bathymetry Technical Center of Expertise. Most of the offshore area was mapped by CSUMB in the summers of 2006 and 2007, using a 244-kHz Reson 8101 multibeam echosounder. The far-northern part of the offshore area was mapped by the USGS in 2006, using a 117-kHz SEA (AP) Ltd. SWATHplus-M phase-differencing sidescan sonar. The nearshore bathymetry and coastal topography were mapped for USACE by Fugro Pelagos in 2009, using the SHOALS-1000T bathymetric-lidar and Leica ALS60 topographic-lidar systems. All these mapping missions combined to collect bathymetry from the 0-m isobath to beyond the 3-nautical-mile limit of California's State Waters. To generate contours, a smooth arithmetic mean convolution function was applied to the bathymetry. Following smoothing, contour lines were generated at 10-meter intervals from -10 m to -100 m and at 50-meter intervals from -100 m to -400 m.

This part of DS 781 presents data for the curvature map of the Hueneme Canyon and vicinity map area, California. The raster data file is included in "Curvature_HuenemeCanyon.zip," which is accessible from https://pubs.usgs.gov/ds/781/HuenemeCanyon/data_catalog_HuenemeCanyon.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Kvitek, R.G., Greene, H.G., Krigsman, L.M., Endris, C.A., Clahan, K.B., Sliter, R.W., Wong, F.L., Yoklavich, M.M., and Normark, W.R. (S.Y. Johnson, ed.), 2012, California State Waters Map Series-—Hueneme Canyon and Vicinity, California: U.S. Geological Survey Scientific Investigations Map 3225, 41 p., 12 sheets, scale 1:24,000, https://pubs.usgs.gov/sim/3225/. This metadata describes a raster data set of smoothed curvature used as an interpretation aid for mapping geomorphology of Hueneme Canyon. The curvature raster, in conjunction with bathymetry data, amplitude data, and seismic reflection profiles, was used to interpret geology and geomorphology of Hueneme Canyon.

This part of DS 781 presents data for the geologic and geomorphic map of the Hueneme Canyon and Vicinity map area, California. The vector data file is included in "Geology_HuenemeCanyon.zip," which is accessible from http://pubs.usgs.gov/ds/781/HuenemeCanyon/data_catalog_HuenemeCanyon.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Kvitek, R.G., Greene, H.G., Krigsman, L.M., Endris, C.A., Clahan, K.B., Sliter, R.W., Wong, F.L., Yoklavich, M.M., and Normark, W.R. (S.Y. Johnson, ed.), 2012, California State Waters Map Series—-Hueneme Canyon and Vicinity, California: U.S. Geological Survey Scientific Investigations Map 3225, 41 p., 12 sheets, scale 1:24,000, https://pubs.usgs.gov/sim/3225/. Marine geology and geomorphology was mapped in the Hueneme Canyon and Vicinity map area, California, from approximate Mean High Water (MHW) to the 3-nautical-mile limit of California's State Waters, and even farther offshore on the east and west flanks of Hueneme Canyon. Offshore geologic units were delineated on the basis of integrated analyses of adjacent onshore geology with multibeam bathymetry and backscatter imagery, seafloor-sediment and rock samples, digital camera and video imagery, and high-resolution seismic-reflection profiles.

This part of DS 781 presents data for the seafloor-character map of the Hueneme Canyon and Vicinity map area, California. The raster data file is included in "SeafloorCharacter_HuenemeCanyon.zip," which is accessible from http://pubs.usgs.gov/ds/781/HuenemeCanyon/data_catalog_HuenemeCanyon.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Kvitek, R.G., Greene, H.G., Krigsman, L.M., Endris, C.A., Clahan, K.B., Sliter, R.W., Wong, F.L., Yoklavich, M.M., and Normark, W.R. (S.Y. Johnson, ed.), 2012, California State Waters Map Series-—Hueneme Canyon and Vicinity, California: U.S. Geological Survey Scientific Investigations Map 3225, 41 p., 12 sheets, scale 1:24,000, https://pubs.usgs.gov/sim/3225/. This raster-format seafloor-character map shows four substrate classes of the Hueneme Canyon and Vicinity map area. The substrate classes mapped in this area have been further divided into the following California Marine Life Protection Act depth zones and slope classes: Depth Zone 2 (intertidal to 30 m), Depth Zone 3 (30 to 100 m), Depth Zone 4 (100 to 200 m), Depth Zone 5 (greater than 200 m), Slope Class 1 (0 degrees-5 degrees), Slope Class 2 (5 degrees-30 degrees), Slope Class 3 (30 degrees-60 degrees), and Slope Class 4 (60 degrees-90 degrees). Depth Zone 1 (intertidal) is not present in this map area. The map is created using a supervised classification method described by Cochrane (2008). References Cited: California Department of Fish and Game, 2008, California Marine Life Protection Act master plan for marine protected areas; Revised draft: California Department of Fish and Game, accessed April 5 2011, at http://www.dfg.ca.gov/mlpa/masterplan.asp. Cochrane, G.R., 2008, Video-supervised classification of sonar data for mapping seafloor habitat, in Reynolds, J.R., and Greene, H.G., eds., Marine habitat mapping technology for Alaska: Fairbanks, University of Alaska, Alaska Sea Grant College Program, p. 185-194, accessed April 5, 2011, at http://doc.nprb.org/web/research/research%20pubs/615_habitat_mapping_workshop/Individual%20Chapters%20High-Res/Ch13%20Cochrane.pdf. Sappington, J.M., Longshore, K.M., and Thompson, D.B., 2007, Quantifying landscape ruggedness for animal habitat analysis--A case study using bighorn sheep in the Mojave Desert: Journal of Wildlife Management, v. 71, p. 1419-1426.

This part of DS 781 presents data for the curvature map of the Hueneme Canyon and vicinity map area, California. The raster data file is included in "Curvature_HuenemeCanyon.zip," which is accessible from https://pubs.usgs.gov/ds/781/HuenemeCanyon/data_catalog_HuenemeCanyon.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Kvitek, R.G., Greene, H.G., Krigsman, L.M., Endris, C.A., Clahan, K.B., Sliter, R.W., Wong, F.L., Yoklavich, M.M., and Normark, W.R. (S.Y. Johnson, ed.), 2012, California State Waters Map Series—-Hueneme Canyon and Vicinity, California: U.S. Geological Survey Scientific Investigations Map 3225, 41 p., 12 sheets, scale 1:24,000, https://pubs.usgs.gov/sim/3225/. This metadata describes a raster data set of smoothed curvature used as an interpretation aid for mapping geomorphology of Hueneme Canyon. The curvature raster, in conjunction with bathymetry data, amplitude data, and seismic reflection profiles, was used to interpret geology and geomorphology of Hueneme Canyon.

This part of DS 781 presents data for the submarine-landslide scarps for the geologic and geomorphic map of the Hueneme Canyon and Vicinity map area, California. The vector data file is included in "SubmarineLandslideScarps_HuenemeCanyon.zip," which is accessible from http://pubs.usgs.gov/ds/781/HuenemeCanyon/data_catalog_HuenemeCanyon.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Kvitek, R.G., Greene, H.G., Krigsman, L.M., Endris, C.A., Clahan, K.B., Sliter, R.W., Wong, F.L., Yoklavich, M.M., and Normark, W.R. (S.Y. Johnson, ed.), 2012, California State Waters Map Series-—Hueneme Canyon and Vicinity, California: U.S. Geological Survey Scientific Investigations Map 3225, 41 p., 12 sheets, scale 1:24,000, https://pubs.usgs.gov/sim/3225/. Three different landslide units are mapped in Hueneme Canyon based on their morphology and relative age inferred from crosscutting and (or) draping relationships. Landslide units are undifferentiated where these morphology and relative age indicators are not distinct. The landslide units commonly include both steep erosional scarps and paired hummocky landslide deposits, and it is this genetic pairing (scarps with landslides) that distinguishes the scarps within landslide units from the scarps within the canyon-wall units. Lower-relief, sediment-draped, deep-seated slumps are mapped as separate landslide units.

This part of DS 781 presents data for the acoustic-backscatter map of Offshore of Pigeon Point map area, California. Backscatter data are provided as three separate grids depending on mapping system. This metadata file refers to the data included in "BackscatterA_8101_OffshorePigeonPoint.zip," which is accessible from https://doi.org/10.5066/F7513W80. These data accompany the pamphlet and map sheets of Cochrane, G.R., Watt, J.T., Dartnell, P., Greene, H.G., Erdey, M.D., Dieter, B.E., Golden, N.E., Johnson, S.Y., Endris, C.A., Hartwell, S.R., Kvitek, R.G., Davenport, C.W., Krigsman, L.M., Ritchie, A.C., Sliter, R.W., Finlayson, D.P., and Maier, K.L. (G.R. Cochrane and S.A. Cochran, eds.), 2015, California State Waters Map Series—Offshore of Pigeon Point, California: U.S. Geological Survey Open-File Report 2015–1232, pamphlet 40 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20151232. The acoustic-backscatter map of the Offshore of Pigeon Point map area, California, was generated from backscatter data collected by California State University, Monterey Bay (CSUMB), by Fugro Pelagos, and by the U.S. Geological Survey (USGS). Mapping was completed between 2006 and 2009, using a combination of 400-kHz Reson 7125 (CSUMB) and 244-kHz Reson 8101 (FUGRO) multibeam echosounders, as well as a 234-kHz SWATHplus bathymetric sidescan-sonar system (USGS). These mapping missions combined to collect backscatter data from about the 10-m isobath to beyond the 3-nautical-mile limit of California's State Waters. Within the final imagery, brighter tones indicate higher backscatter intensity, and darker tones indicate lower backscatter intensity. The intensity represents a complex interaction between the acoustic pulse and the seafloor, as well as characteristics within the shallow subsurface, providing a general indication of seafloor texture and composition. Backscatter intensity depends on the acoustic source level; the frequency used to image the seafloor; the grazing angle; the composition and character of the seafloor, including grain size, water content, bulk density, and seafloor roughness; and some biological cover. Harder and rougher bottom types such as rocky outcrops or coarse sediment typically return stronger intensities (high backscatter, lighter tones), whereas softer bottom types such as fine sediment return weaker intensities (low backscatter, darker tones).

This part of DS 781 presents data for the acoustic-backscatter map of Offshore of Pigeon Point map area, California. Backscatter data are provided as three separate grids depending on mapping system. This metadata file refers to the data included in "BackscatterB_7125_OffshorePigeonPoint.zip," which is accessible from https://doi.org/10.5066/F7513W80. These data accompany the pamphlet and map sheets of Cochrane, G.R., Watt, J.T., Dartnell, P., Greene, H.G., Erdey, M.D., Dieter, B.E., Golden, N.E., Johnson, S.Y., Endris, C.A., Hartwell, S.R., Kvitek, R.G., Davenport, C.W., Krigsman, L.M., Ritchie, A.C., Sliter, R.W., Finlayson, D.P., and Maier, K.L. (G.R. Cochrane and S.A. Cochran, eds.), 2015, California State Waters Map Series—Offshore of Pigeon Point, California: U.S. Geological Survey Open-File Report 2015–1232, pamphlet 40 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20151232. The acoustic-backscatter map of the Offshore of Pigeon Point, California was generated from backscatter data collected by California State University, Monterey Bay (CSUMB), by Fugro Pelagos, and by the U.S. Geological Survey (USGS). Mapping was completed between 2006 and 2009, using a combination of 400-kHz Reson 7125 and 244-kHz Reson 8101 multibeam echosounders, as well as a 234-kHz SWATHplus bathymetric sidescan-sonar system. Within the final imagery, brighter tones indicate higher backscatter intensity, and darker tones indicate lower backscatter intensity. The intensity represents a complex interaction between the acoustic pulse and the seafloor, as well as characteristics within the shallow subsurface, providing a general indication of seafloor texture and composition. Backscatter intensity depends on the acoustic source level; the frequency used to image the seafloor; the grazing angle; the composition and character of the seafloor, including grain size, water content, bulk density, and seafloor roughness; and some biological cover. Harder and rougher bottom types such as rocky outcrops or coarse sediment typically return stronger intensities (high backscatter, lighter tones), whereas softer bottom types such as fine sediment return weaker intensities (low backscatter, darker tones).

This part of DS 781 presents data for the acoustic-backscatter map of Offshore of Pigeon Point map area, California. Backscatter data are provided as three separate grids depending on mapping system. This metadata file refers to the data included in "BackscatterC_SWATH_OffshorePigeonPoint.zip," which is accessible from https://doi.org/10.5066/F7513W80. These data accompany the pamphlet and map sheets of Cochrane, G.R., Watt, J.T., Dartnell, P., Greene, H.G., Erdey, M.D., Dieter, B.E., Golden, N.E., Johnson, S.Y., Endris, C.A., Hartwell, S.R., Kvitek, R.G., Davenport, C.W., Krigsman, L.M., Ritchie, A.C., Sliter, R.W., Finlayson, D.P., and Maier, K.L. (G.R. Cochrane and S.A. Cochran, eds.), 2015, California State Waters Map Series—Offshore of Pigeon Point, California: U.S. Geological Survey Open-File Report 2015–1232, pamphlet 40 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20151232. The acoustic-backscatter map of the Offshore of Pigeon Point, California was generated from backscatter data collected by California State University, Monterey Bay (CSUMB), by Fugro Pelagos, and by the U.S. Geological Survey (USGS). Mapping was completed between 2006 and 2009, using a combination of 400-kHz Reson 7125 and 244-kHz Reson 8101 multibeam echosounders, as well as a 234-kHz SWATHplus bathymetric sidescan-sonar system. Within the final imagery, brighter tones indicate higher backscatter intensity, and darker tones indicate lower backscatter intensity. The intensity represents a complex interaction between the acoustic pulse and the seafloor, as well as characteristics within the shallow subsurface, providing a general indication of seafloor texture and composition. Backscatter intensity depends on the acoustic source level; the frequency used to image the seafloor; the grazing angle; the composition and character of the seafloor, including grain size, water content, bulk density, and seafloor roughness; and some biological cover. Harder and rougher bottom types such as rocky outcrops or coarse sediment typically return stronger intensities (high backscatter, lighter tones), whereas softer bottom types such as fine sediment return weaker intensities (low backscatter, darker tones).

This part of DS 781 presents data for the shaded-relief bathymetry map of Offshore Pigeon Point, California. The raster data file is included in "BathymetryHS_OffshorePigeonPoint.zip", which is accessible from https://doi.org/10.5066/F7513W80. These data accompany the pamphlet and map sheets of Cochrane, G.R., Watt, J.T., Dartnell, P., Greene, H.G., Erdey, M.D., Dieter, B.E., Golden, N.E., Johnson, S.Y., Endris, C.A., Hartwell, S.R., Kvitek, R.G., Davenport, C.W., Krigsman, L.M., Ritchie, A.C., Sliter, R.W., Finlayson, D.P., and Maier, K.L. (G.R. Cochrane and S.A. Cochran, eds.), 2015, California State Waters Map Series—Offshore of Pigeon Point, California: U.S. Geological Survey Open-File Report 2015–1232, pamphlet 40 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20151232. The shaded-relief bathymetry map of Offshore Pigeon Point, California, was generated from bathymetry data collected by California State University, Monterey Bay (CSUMB), by Fugro Pelagos, and by the U.S. Geological Survey (USGS). Mapping was completed between 2006 and 2009, using a combination of 400-kHz Reson 7125 (CSUMB) and 244-kHz Reson 8101 (Fugros) multibeam echosounders, as well as a 234-kHz SWATHplus bathymetric sidescan-sonar system (USGS). These mapping missions combined to collect bathymetry from about the 10-m isobath to beyond the 3-nautical-mile limit of California's State Waters.

This part of DS 781 presents data for the bathymetry map of Offshore Pigeon Point, California. The raster data file is included in "Bathymetry_OffshorePigeonPoint.zip", which is accessible from https://doi.org/10.5066/F7513W80. These data accompany the pamphlet and map sheets of Cochrane, G.R., Watt, J.T., Dartnell, P., Greene, H.G., Erdey, M.D., Dieter, B.E., Golden, N.E., Johnson, S.Y., Endris, C.A., Hartwell, S.R., Kvitek, R.G., Davenport, C.W., Krigsman, L.M., Ritchie, A.C., Sliter, R.W., Finlayson, D.P., and Maier, K.L. (G.R. Cochrane and S.A. Cochran, eds.), 2015, California State Waters Map Series—Offshore of Pigeon Point, California: U.S. Geological Survey Open-File Report 2015–1232, pamphlet 40 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20151232. The bathymetry map of Offshore Pigeon Point, California, was generated from bathymetry data collected by California State University, Monterey Bay (CSUMB), by Fugro Pelagos, and by the U.S. Geological Survey (USGS). Mapping was completed between 2006 and 2009, using a combination of 400-kHz Reson 7125 (CSUMB) and 244-kHz Reson 8101 (Fugros) multibeam echosounders, as well as a 234-kHz SWATHplus bathymetric sidescan-sonar system (USGS). These mapping missions combined to collect bathymetry from about the 10-m isobath to beyond the 3-nautical-mile limit of California's State Waters. NOTE: The horizontal datum of this bathymetry data (NAD83) differs from the horizontal datum of other layers in this SIM (WGS84). Some bathymetry grids within this map area were projected horizontally from WGS84 to NAD83 using ESRI tools to be more consistent with the vertical reference of the North American Vertical Datum of 1988 (NAVD88). These data are not intended for navigational purposes.

This part of DS 781 presents data for the bathymetric contours for several seafloor maps of the Offshore Pigeon Point map area, California. The vector data file is included in "Contours_OffshorePigeonPoint.zip", which is accessible from https://doi.org/10.5066/F7513W80. These data accompany the pamphlet and map sheets of Cochrane, G.R., Watt, J.T., Dartnell, P., Greene, H.G., Erdey, M.D., Dieter, B.E., Golden, N.E., Johnson, S.Y., Endris, C.A., Hartwell, S.R., Kvitek, R.G., Davenport, C.W., Krigsman, L.M., Ritchie, A.C., Sliter, R.W., Finlayson, D.P., and Maier, K.L. (G.R. Cochrane and S.A. Cochran, eds.), 2015, California State Waters Map Series—Offshore of Pigeon Point, California: U.S. Geological Survey Open-File Report 2015–1232, pamphlet 40 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20151232. 10-m interval contours of the Offshore Pigeon Point map area, California, were generated from bathymetry data collected by the U.S. Geological Survey (USGS) and by California State University, Monterey Bay (CSUMB). Mapping was completed between 2006 and 2009 using a combination of a 244-kHz Reson 8101 multibeam echosounder and a 234-kHz SEA SWATHplus bathymetric sidescan-sonar system. The mapping missions collected bathymetry data from about the 10-m isobath to beyond the 3-nautical-mile limit of California's State Waters. Bathymetric contours at 10-m intervals were generated from a modified 2-m bathymetric surface. The original surface was smoothed using the Focal Mean tool in ArcGIS and a circular neighborhood with a radius of 20 to 30 meters (depending on the area). The contours were generated from this smoothed surface using the ArcGIS Spatial Analyst Contour tool. The most continuous contour segments were preserved while smaller segments and isolated island polygons were excluded from the final output. The contours were then clipped to the boundary of the map area. These data are not intended for navigational purposes.

This part of DS 781 presents data for the folds for the geologic and geomorphic map of the Offshore Pigeon Point map area, California. The vector data file is included in "Folds_OffshorePigeonPoint.zip," which is accessible from https://doi.org/10.5066/F7513W80. These data accompany the pamphlet and map sheets of Cochrane, G.R., Watt, J.T., Dartnell, P., Greene, H.G., Erdey, M.D., Dieter, B.E., Golden, N.E., Johnson, S.Y., Endris, C.A., Hartwell, S.R., Kvitek, R.G., Davenport, C.W., Krigsman, L.M., Ritchie, A.C., Sliter, R.W., Finlayson, D.P., and Maier, K.L. (G.R. Cochrane and S.A. Cochran, eds.), 2015, California State Waters Map Series—Offshore of Pigeon Point, California: U.S. Geological Survey Open-File Report 2015–1232, pamphlet 40 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20151232.

This part of DS 781 presents the seafloor-character map Offshore of Pigeon Point, California. The raster data file is included in "SeafloorCharacter_OffshorePigeonPoint.zip," which is accessible from https://doi.org/10.5066/F7513W80. These data accompany the pamphlet and map sheets of Cochrane, G.R., Watt, J.T., Dartnell, P., Greene, H.G., Erdey, M.D., Dieter, B.E., Golden, N.E., Johnson, S.Y., Endris, C.A., Hartwell, S.R., Kvitek, R.G., Davenport, C.W., Krigsman, L.M., Ritchie, A.C., Sliter, R.W., Finlayson, D.P., and Maier, K.L. (G.R. Cochrane and S.A. Cochran, eds.), 2015, California State Waters Map Series—Offshore of Pigeon Point, California: U.S. Geological Survey Open-File Report 2015–1232, pamphlet 40 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20151232. This raster-format seafloor character map shows four substrate classes Offshore of Pigeon Point, California. The substrate classes mapped in this area have been further divided into the following California Marine Life Protection Act depth zones and slope classes: Depth Zone 2 (intertidal to 30 m), Depth Zone 3 (30 to 100 m), Slope Class 1 (0 degrees - 5 degrees), and Slope Class 2 (5 degrees - 30 degrees). Depth Zone 1 (intertidal), Depth Zones 4-5 (greater than 100 m), and Slopes Classes 3-4 (greater than 30 degrees) are not present in the region covered by this block. The map is created using a supervised classification method described by Cochrane (2008). Reference Cited: Cochrane, G.R., 2008, Video-supervised classification of sonar data for mapping seafloor habitat, in Reynolds, J.R., and Greene, H.G., eds., Marine habitat mapping technology for Alaska: Fairbanks, University of Alaska, Alaska Sea Grant College Program, p. 185-194, accessed April 5, 2011, at http://doc.nprb.org/web/research/research%20pubs/615_habitat_mapping_workshop/Individual%20Chapters%20High-Res/Ch13%20Cochrane.pdf.

This dataset includes raw and processed, high-resolution seismic-reflection data collected in 2009 to explore a possible connection between the San Diego Trough Fault and the San Pedro Basin Fault. The survey is in the San Pedro Basin between Santa Catalina Island and San Pedro, California. The data were collected aboard the U.S. Geological Survey R/V Parke Snavely. The seismic-reflection data were acquired using a SIG 2mille minisparker. Subbottom acoustic penetration spanned tens to several hundreds of meters, variable by location.

This part of DS 781 presents data for the acoustic-backscatter map of Offshore of Scott Creek map area, California. Backscatter data are provided as three separate grids depending on mapping system. The raster data files are included in "BackscatterA_8101_OffshoreScottCreek.zip," which is accessible from https://doi.org/10.5066/F7CJ8BJW. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Johnson, S.Y., Greene, H.G., Erdey, M.D., Dieter, B.E., Golden, N.E., Endris, C.A., Hartwell, S.R., Kvitek, R.G., Davenport, C.W., Watt, J.T., Krigsman, L.M., Ritchie, A.C., Sliter, R.W., Finlayson, D.P., and Maier, K.L. (G.R. Cochrane and S.A. Cochran, eds.), 2015, California State Waters Map Series--Offshore of Scott Creek, California: U.S. Geological Survey Open-File Report 2015-1191, pamphlet 40 p., 10 sheets, scale 1:24,000, http://doi.org/10.3133/ofr20151191. The acoustic-backscatter map of the Offshore of Pigeon Point map area, California, was generated from backscatter data collected by California State University, Monterey Bay (CSUMB), by Fugro Pelagos, and by the U.S. Geological Survey (USGS). Mapping was completed between 2006 and 2009, using a combination of 400-kHz Reson 7125 (CSUMB) and 244-kHz Reson 8101 (FUGRO) multibeam echosounders, as well as a 234-kHz SWATHplus bathymetric sidescan-sonar system (USGS). These mapping missions combined to collect backscatter data from about the 10-m isobath to beyond the 3-nautical-mile limit of California's State Waters. Within the final imagery, brighter tones indicate higher backscatter intensity, and darker tones indicate lower backscatter intensity. The intensity represents a complex interaction between the acoustic pulse and the seafloor, as well as characteristics within the shallow subsurface, providing a general indication of seafloor texture and composition. Backscatter intensity depends on the acoustic source level; the frequency used to image the seafloor; the grazing angle; the composition and character of the seafloor, including grain size, water content, bulk density, and seafloor roughness; and some biological cover. Harder and rougher bottom types such as rocky outcrops or coarse sediment typically return stronger intensities (high backscatter, lighter tones), whereas softer bottom types such as fine sediment return weaker intensities (low backscatter, darker tones).

This part of DS 781 presents data for the acoustic-backscatter map of Offshore of Scott Creek map area, California. Backscatter data are provided as three separate grids depending on mapping system. The raster data files are included in "BackscatterB_7125_OffshoreScottCreek.zip," which is accessible from https://doi.org/10.5066/F7CJ8BJW. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Johnson, S.Y., Greene, H.G., Erdey, M.D., Dieter, B.E., Golden, N.E., Endris, C.A., Hartwell, S.R., Kvitek, R.G., Davenport, C.W., Watt, J.T., Krigsman, L.M., Ritchie, A.C., Sliter, R.W., Finlayson, D.P., and Maier, K.L. (G.R. Cochrane and S.A. Cochran, eds.), 2015, California State Waters Map Series--Offshore of Scott Creek, California: U.S. Geological Survey Open-File Report 2015-1191, pamphlet 40 p., 10 sheets, scale 1:24,000, http://doi.org/10.3133/ofr20151191. The acoustic-backscatter map of the Offshore of Scott Creek map area, California, was generated from backscatter data collected by California State University, Monterey Bay (CSUMB), by Fugro Pelagos, and by the U.S. Geological Survey (USGS). Mapping was completed between 2006 and 2009, using a combination of 400-kHz Reson 7125 (CSUMB) and 244-kHz Reson 8101 (FUGRO) multibeam echosounders, as well as a 234-kHz SWATHplus bathymetric sidescan-sonar system (USGS). These mapping missions combined to collect backscatter data from about the 10-m isobath to beyond the 3-nautical-mile limit of California's State Waters. Within the final imagery, brighter tones indicate higher backscatter intensity, and darker tones indicate lower backscatter intensity. The intensity represents a complex interaction between the acoustic pulse and the seafloor, as well as characteristics within the shallow subsurface, providing a general indication of seafloor texture and composition. Backscatter intensity depends on the acoustic source level; the frequency used to image the seafloor; the grazing angle; the composition and character of the seafloor, including grain size, water content, bulk density, and seafloor roughness; and some biological cover. Harder and rougher bottom types such as rocky outcrops or coarse sediment typically return stronger intensities (high backscatter, lighter tones), whereas softer bottom types such as fine sediment return weaker intensities (low backscatter, darker tones).

This part of DS 781 presents data for the acoustic-backscatter map of Offshore of Scott Creek map area, California. Backscatter data are provided as three separate grids depending on mapping system. The raster data files are included in "BackscatterC_SWATH_OffshoreScottCreek.zip," which is accessible from https://doi.org/10.5066/F7CJ8BJW. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Johnson, S.Y., Greene, H.G., Erdey, M.D., Dieter, B.E., Golden, N.E., Endris, C.A., Hartwell, S.R., Kvitek, R.G., Davenport, C.W., Watt, J.T., Krigsman, L.M., Ritchie, A.C., Sliter, R.W., Finlayson, D.P., and Maier, K.L. (G.R. Cochrane and S.A. Cochran, eds.), 2015, California State Waters Map Series--Offshore of Scott Creek, California: U.S. Geological Survey Open-File Report 2015-1191, pamphlet 40 p., 10 sheets, scale 1:24,000, http://doi.org/10.3133/ofr20151191. The acoustic-backscatter map of the Offshore of Scott Creek map area, California, was generated from backscatter data collected by California State University, Monterey Bay (CSUMB), by Fugro Pelagos, and by the U.S. Geological Survey (USGS). Mapping was completed between 2006 and 2009, using a combination of 400-kHz Reson 7125 (CSUMB) and 244-kHz Reson 8101 (FUGRO) multibeam echosounders, as well as a 234-kHz SWATHplus bathymetric sidescan-sonar system (USGS). These mapping missions combined to collect backscatter data from about the 10-m isobath to beyond the 3-nautical-mile limit of California's State Waters. Within the final imagery, brighter tones indicate higher backscatter intensity, and darker tones indicate lower backscatter intensity. The intensity represents a complex interaction between the acoustic pulse and the seafloor, as well as characteristics within the shallow subsurface, providing a general indication of seafloor texture and composition. Backscatter intensity depends on the acoustic source level; the frequency used to image the seafloor; the grazing angle; the composition and character of the seafloor, including grain size, water content, bulk density, and seafloor roughness; and some biological cover. Harder and rougher bottom types such as rocky outcrops or coarse sediment typically return stronger intensities (high backscatter, lighter tones), whereas softer bottom types such as fine sediment return weaker intensities (low backscatter, darker tones).

This part of DS 781 presents data for the shaded-relief bathymetry map of Offshore Scott Creek, California. The raster data file is included in "BathymetryHS_OffshoreScottCreek.zip", which is accessible from https://doi.org/10.5066/F7CJ8BJW. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Johnson, S.Y., Greene, H.G., Erdey, M.D., Dieter, B.E., Golden, N.E., Endris, C.A., Hartwell, S.R., Kvitek, R.G., Davenport, C.W., Watt, J.T., Krigsman, L.M., Ritchie, A.C., Sliter, R.W., Finlayson, D.P., and Maier, K.L. (G.R. Cochrane and S.A. Cochran, eds.), 2015, California State Waters Map Series--Offshore of Scott Creek, California: U.S. Geological Survey Open-File Report 2015-1191, pamphlet 40 p., 10 sheets, scale 1:24,000, http://doi.org/10.3133/ofr20151191. The bathymetry and shaded-relief maps of Offshore Scott Creek, California, were generated from bathymetry data collected by California State University, Monterey Bay (CSUMB), by Fugro Pelagos, and by the U.S. Geological Survey (USGS). Mapping was completed between 2006 and 2009, using a combination of 400-kHz Reson 7125 and 244-kHz Reson 8101 multibeam echosounders, as well as a 234-kHz SWATHplus bathymetric sidescan-sonar system. These mapping missions combined to collect bathymetry from about the 10-m isobath to beyond the 3-nautical-mile limit of California's State Waters.

This part of DS 781 presents data for the bathymetry map of Offshore Scott Creek, California. The raster data file is included in "Bathymetry_OffshoreScottCreek.zip", which is accessible from https://doi.org/10.5066/F7CJ8BJW. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Johnson, S.Y., Greene, H.G., Erdey, M.D., Dieter, B.E., Golden, N.E., Endris, C.A., Hartwell, S.R., Kvitek, R.G., Davenport, C.W., Watt, J.T., Krigsman, L.M., Ritchie, A.C., Sliter, R.W., Finlayson, D.P., and Maier, K.L. (G.R. Cochrane and S.A. Cochran, eds.), 2015, California State Waters Map Series--Offshore of Scott Creek, California: U.S. Geological Survey Open-File Report 2015-1191, pamphlet 40 p., 10 sheets, scale 1:24,000, http://doi.org/10.3133/ofr20151191. The bathymetry and shaded-relief maps of the Offshore Scott Creek map area, California, were generated from bathymetry data collected by California State University, Monterey Bay (CSUMB), by Fugro Pelagos, and by the U.S. Geological Survey (USGS). Mapping was completed between 2006 and 2009, using a combination of 400-kHz Reson 7125 and 244-kHz Reson 8101 multibeam echosounders, as well as a 234-kHz SWATHplus bathymetric sidescan-sonar system. These mapping missions combined to collect bathymetry from about the 10-m isobath to beyond the 3-nautical-mile limit of California's State Waters. NOTE: The horizontal datum of this bathymetry data (NAD83) differs from the horizontal datum of other layers in this data release (WGS84). Some bathymetry grids within this map area were projected horizontally from WGS84 to NAD83 using ESRI tools to be more consistent with the vertical reference of the North American Vertical Datum of 1988 (NAVD88).

This part of DS 781 presents data for the bathymetric contours for several seafloor maps of the Offshore Scott Creek map area, California. The vector data file is included in "Contours_OffshoreScottCreek.zip", which is accessible from https://doi.org/10.5066/F7CJ8BJW. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Johnson, S.Y., Greene, H.G., Erdey, M.D., Dieter, B.E., Golden, N.E., Endris, C.A., Hartwell, S.R., Kvitek, R.G., Davenport, C.W., Watt, J.T., Krigsman, L.M., Ritchie, A.C., Sliter, R.W., Finlayson, D.P., and Maier, K.L. (G.R. Cochrane and S.A. Cochran, eds.), 2015, California State Waters Map Series--Offshore of Scott Creek, California: U.S. Geological Survey Open-File Report 2015-1191, pamphlet 40 p., 10 sheets, scale 1:24,000, http://doi.org/10.3133/ofr20151191. 10-m interval contours of the Offshore Scott Creek map area, California, were generated from bathymetry data collected by California State University, Monterey Bay (CSUMB), by Fugro Pelagos, and by the U.S. Geological Survey (USGS). Mapping was completed between 2006 and 2009, using a combination of 400-kHz Reson 7125 and 244-kHz Reson 8101 multibeam echosounders, as well as a 234-kHz SWATHplus bathymetric sidescan-sonar system. These mapping missions combined to collect bathymetry from about the 10-m isobath to beyond the 3-nautical-mile limit of California's State Waters. Bathymetric contours at 10-m intervals were generated from a modified 2-m bathymetric surface. The original surface was smoothed using the Focal Mean tool in ArcGIS and a circular neighborhood with a radius of 20 to 30 meters (depending on the area). The contours were generated from this smoothed surface using the ArcGIS Spatial Analyst Contour tool. The most continuous contour segments were preserved while smaller segments and isolated island polygons were excluded from the final output. The contours were then clipped to the boundary of the map area.

This part of DS 781 presents data for the faults for the geologic and geomorphic map of the Offshore of Scott Creek map area, California. The vector data file is included in "Faults_OffshoreScottCreek.zip," which is accessible from https://doi.org/10.5066/F7CJ8BJW. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Johnson, S.Y., Greene, H.G., Erdey, M.D., Dieter, B.E., Golden, N.E., Endris, C.A., Hartwell, S.R., Kvitek, R.G., Davenport, C.W., Watt, J.T., Krigsman, L.M., Ritchie, A.C., Sliter, R.W., Finlayson, D.P., and Maier, K.L. (G.R. Cochrane and S.A. Cochran, eds.), 2015, California State Waters Map Series--Offshore of Scott Creek, California: U.S. Geological Survey Open-File Report 2015-1191, pamphlet 40 p., 10 sheets, scale 1:24,000, http://doi.org/10.3133/ofr20151191.

This part of DS 781 presents data for the folds for the geologic and geomorphic map of the Offshore of Scott Creek map area, California. The vector data file is included in "Folds_OffshoreScottCreek.zip," which is accessible from https://doi.org/10.5066/F7CJ8BJW. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Johnson, S.Y., Greene, H.G., Erdey, M.D., Dieter, B.E., Golden, N.E., Endris, C.A., Hartwell, S.R., Kvitek, R.G., Davenport, C.W., Watt, J.T., Krigsman, L.M., Ritchie, A.C., Sliter, R.W., Finlayson, D.P., and Maier, K.L. (G.R. Cochrane and S.A. Cochran, eds.), 2015, California State Waters Map Series--Offshore of Scott Creek, California: U.S. Geological Survey Open-File Report 2015-1191, pamphlet 40 p., 10 sheets, scale 1:24,000, http://doi.org/10.3133/ofr20151191.

This part of DS 781 presents the seafloor-character map of the Offshore of Scott Creek map area, California. The raster data file is included in "SeafloorCharacter_OffshoreScottCreek.zip," which is accessible from https://doi.org/10.5066/F7CJ8BJW. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Johnson, S.Y., Greene, H.G., Erdey, M.D., Dieter, B.E., Golden, N.E., Endris, C.A., Hartwell, S.R., Kvitek, R.G., Davenport, C.W., Watt, J.T., Krigsman, L.M., Ritchie, A.C., Sliter, R.W., Finlayson, D.P., and Maier, K.L. (G.R. Cochrane and S.A. Cochran, eds.), 2015, California State Waters Map Series--Offshore of Scott Creek, California: U.S. Geological Survey Open-File Report 2015-1191, pamphlet 40 p., 10 sheets, scale 1:24,000, http://doi.org/10.3133/ofr20151191. This raster-format seafloor character map shows four substrate classes offshore of Scott Creek, California. The substrate classes mapped in this area have been further divided into the following California Marine Life Protection Act depth zones and slope classes: Depth Zone 2 (intertidal to 30 m), Depth Zone 3 (30 to 100 m), Slope Class 1 (0 degrees - 5 degrees), and Slope Class 2 (5 degrees - 30 degrees). Depth Zone 1 (intertidal), Depth Zones 4-5 (greater than 100 m), and Slopes Classes 3-4 (greater than 30 degrees) are not present in the region covered by this block. The map is created using a supervised classification method described by Cochrane (2008). Reference Cited: Cochrane, G.R., 2008, Video-supervised classification of sonar data for mapping seafloor habitat, in Reynolds, J.R., and Greene, H.G., eds., Marine habitat mapping technology for Alaska: Fairbanks, University of Alaska, Alaska Sea Grant College Program, p. 185-194, accessed April 5, 2011, at http://doc.nprb.org/web/research/research%20pubs/615_habitat_mapping_workshop/Individual%20Chapters%20High-Res/Ch13%20Cochrane.pdf.

This portion of the USGS data release presents bathymetry data collected during surveys performed in the Columbia River littoral cell, Washington and Oregon, in 2020 (USGS Field Activity Number 2020-622-FA). Bathymetry data were collected using four personal watercraft (PWCs) equipped with single-beam sonar systems and global navigation satellite system (GNSS) receivers. The sonar systems consisted of an Odom Echotrac CV-100 single-beam echosounder and 200 kHz transducer with a 9-degree beam angle. Raw acoustic backscatter returns were digitized by the echosounder with a vertical resolution of 1.25 cm. Depths from the echosounders were computed using sound velocity profiles measured using a YSI CastAway CTD during the survey. Positioning of the survey vessels was determined at 5 to 10 Hz using Trimble R7 GNSS receivers. Output from the GNSS receivers and sonar systems were combined in real time on the PWC by a computer running HYPACK hydrographic survey software. Navigation information was displayed on a video monitor, allowing PWC operators to navigate along survey lines at speeds of 2 to 3 m/s. Survey-grade positions of the PWCs were achieved with a single-base station and differential post-processing. Positioning data from the GNSS receivers were post-processed using Waypoint Grafnav to apply differential corrections from a GNSS base station with known horizontal and vertical coordinates relative to the North American Datum of 1983. Orthometric elevations relative to the NAVD88 vertical datum were computed using National Geodetic Survey Geoid12a offsets. Bathymetric data were merged with post-processed positioning data and spurious soundings were removed using a custom Graphical User Interface (GUI) programmed with the computer program MATLAB. The average estimated vertical uncertainty of the bathymetric measurements is 10 cm. The final point data from the PWCs are provided in a comma-separated text file and are projected in cartesian coordinates using the Washington State Plane South, meters coordinate system. Due to equipment and staffing issues associated with the global pandemic, bathymetric surveys performed at the southern portion of the Clatsop Plains sub-cell (survey lines 71 to 101) and North Beach sub-cell were performed several weeks after the corresponding topographic surveys. The CTD was not available for bathymetric surveys at these locations and an assumed speed of sound of 1,500 and 1,490 m/s was applied to soundings collected in the North Beach sub-cell and southern portion of the Clatsop sub-cell, respectively.

This portion of the USGS data release presents topography data collected during surveys performed in the Columbia River littoral cell, Washington and Oregon, in 2020 (USGS Field Activity Number 2020-622-FA). Topographic profiles were collected by walking along survey lines with global navigation satellite system (GNSS) receivers mounted on backpacks. Prior to data collection, vertical distances between the GNSS antennas and the ground were measured using a tape measure. Hand-held data collectors were used to log raw data and display navigational information allowing surveyors to navigate survey lines spaced at 100- to 1000-m intervals along the beach. Profiles were surveyed from the landward edge of the study area (either the base of a bluff, engineering structure, or just landward of the primary dune) over the beach foreshore, to wading depth on the same series of transects as nearshore bathymetric surveys that were conducted during the same time period. Additional topographic data were collected between survey lines in some areas with an all-terrain vehicle (ATV) equipped with a GNSS receiver to constrain the elevations and alongshore extent of major morphological features. Positioning data from the survey platforms were referenced to a GNSS base station with known horizontal and vertical coordinates relative to the North American Datum of 1983. Differential corrections from the GNSS base stations to the survey platforms were either applied in real-time with a VHF radio link, or post-processed using Trimble Business Center software. Orthometric elevations relative to the NAVD88 vertical datum were computed using National Geodetic Survey Geoid12a offsets. The average estimated vertical uncertainty of the topographic measurements is 4 cm. The final point data are provided in comma-separated text format and are projected in Cartesian coordinates using the Washington State Plane South, meters coordinate system. Due to equipment and staffing issues associated with the global pandemic, topographic surveys performed at the southern portion of the Clatsop Plains sub-cell (lines 71 to 101) and North Beach sub-cell took place several weeks prior the corresponding bathymetric surveys.

This portion of the USGS data release presents bathymetry data collected during surveys performed in the Columbia River littoral cell, Washington and Oregon, in 2021 (USGS Field Activity Number 2021-632-FA). Bathymetry data were collected using four personal watercraft (PWCs) equipped with single-beam sonar systems and global navigation satellite system (GNSS) receivers. The sonar systems consisted of an Odom Echotrac CV-100 single-beam echosounder and 200 kHz transducer with a 9-degree beam angle. Raw acoustic backscatter returns were digitized by the echosounder with a vertical resolution of 1.25 cm. Depths from the echosounders were computed using sound velocity profiles measured using a YSI CastAway CTD during the survey. Positioning of the survey vessels was determined at 5 to 10 Hz using Trimble R7 GNSS receivers. Output from the GNSS receivers and sonar systems were combined in real time on the PWC by a computer running HYPACK hydrographic survey software. Navigation information was displayed on a video monitor, allowing PWC operators to navigate along survey lines at speeds of 2 to 3 m/s. Survey-grade positions of the PWCs were achieved with a single-base station and differential post-processing. Positioning data from the GNSS receivers were post-processed using Waypoint Grafnav to apply differential corrections from a GNSS base station with known horizontal and vertical coordinates relative to the North American Datum of 1983. Orthometric elevations relative to the NAVD88 vertical datum were computed using National Geodetic Survey Geoid12a offsets. Bathymetric data were merged with post-processed positioning data and spurious soundings were removed using a custom Graphical User Interface (GUI) programmed with the computer program MATLAB. The average estimated vertical uncertainty of the bathymetric measurements is 10 cm. The final point data from the PWCs are provided in a comma-separated text file and are projected in cartesian coordinates using the Washington State Plane South, meters coordinate system.

This portion of the USGS data release presents topography data collected during surveys performed in the Columbia River littoral cell, Washington and Oregon, in 2021 (USGS Field Activity Number 2021-632-FA). Topographic profiles were collected by walking along survey lines with global navigation satellite system (GNSS) receivers mounted on backpacks. Prior to data collection, vertical distances between the GNSS antennas and the ground were measured using a tape measure. Hand-held data collectors were used to log raw data and display navigational information allowing surveyors to navigate survey lines spaced at 100- to 1000-m intervals along the beach. Profiles were surveyed from the landward edge of the study area (either the base of a bluff, engineering structure, or just landward of the primary dune) over the beach foreshore, to wading depth on the same series of transects as nearshore bathymetric surveys that were conducted during the same time period. Additional topographic data were collected between survey lines in some areas with an all-terrain vehicle (ATV) equipped with a GNSS receiver to constrain the elevations and alongshore extent of major morphological features. Positioning data from the survey platforms were referenced to a GNSS base station with known horizontal and vertical coordinates relative to the North American Datum of 1983. Differential corrections from the GNSS base stations to the survey platforms were either applied in real-time with a VHF radio link, or post-processed using Trimble Business Center software. Orthometric elevations relative to the NAVD88 vertical datum were computed using National Geodetic Survey Geoid12a offsets. The average estimated vertical uncertainty of the topographic measurements is 4 cm. The final point data are provided in comma-separated text format and are projected in Cartesian coordinates using the Washington State Plane South, meters coordinate system.

This part of DS 781 presents data for the geologic and geomorphic map of the Offshore Pigeon Point map area, California. The vector data file is included in "Geology_OffshorePigeonPoint.zip," which is accessible from https://doi.org/10.5066/F7513W80. Marine geology and geomorphology were mapped in the Offshore Pigeon Point map area, California, from approximate Mean High Water (MHW) to the 3-nautical-mile limit of California'€™s State Waters. Offshore geologic units were delineated on the basis of integrated analyses of adjacent onshore geology with multibeam bathymetry and backscatter imagery, seafloor-sediment and rock samples, digital camera and video imagery, and high-resolution seismic-reflection profiles. These data accompany the pamphlet and map sheets of Cochrane, G.R., Watt, J.T., Dartnell, P., Greene, H.G., Erdey, M.D., Dieter, B.E., Golden, N.E., Johnson, S.Y., Endris, C.A., Hartwell, S.R., Kvitek, R.G., Davenport, C.W., Krigsman, L.M., Ritchie, A.C., Sliter, R.W., Finlayson, D.P., and Maier, K.L. (G.R. Cochrane and S.A. Cochran, eds.), 2015, California State Waters Map Series—Offshore of Pigeon Point, California: U.S. Geological Survey Open-File Report 2015–1232, pamphlet 40 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20151232.

This part of DS 781 presents data for the acoustic-backscatter map of Offshore of Aptos map area, California. Backscatter data are provided as two separate grids depending on mapping system and processing method. This metadata file refers to the data included in "BackscatterA_SWATH_OffshoreAptos.zip," which is accessible from https://doi.org/10.5066/F7K35RQB. These data accompany the pamphlet and map sheets of Cochrane, G.R., Johnson, S.Y., Dartnell, P., Greene, H.G., Erdey, M.D, Dieter, B.E., Golden, N.E., Hartwell, S.R., Ritchie, A.C., Kvitek, r.G., Maier, K.L., Endris, C.A., Davenport, C.W., Watt, J.T., Sliter, R.W., Finlayson, D.P., and Krigsman, L.M., (G.R. Cochrane and S.A. Cochran, eds.), 2016, California State Waters Map Series—Offshore of Aptos, California: U.S. Geological Survey Open-File Report 2016-1025, 43 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20161025. The acoustic-backscatter map of Offshore of Aptos, California, was generated from backscatter data collected by the U.S. Geological Survey (USGS) and by Monterey Bay Aquarium Research Institute (MBARI). Mapping was completed between 1998 and 2009, using a combination of a 234-kHz SWATHplus bathymetric sidescan-sonar system and a 30-kHz Simrad EM-300 multibeam echosounder. Within the final imagery, brighter tones indicate higher backscatter intensity, and darker tones indicate lower backscatter intensity. The intensity represents a complex interaction between the acoustic pulse and the seafloor, as well as characteristics within the shallow subsurface, providing a general indication of seafloor texture and composition. Backscatter intensity depends on the acoustic source level; the frequency used to image the seafloor; the grazing angle; the composition and character of the seafloor, including grain size, water content, bulk density, and seafloor roughness; and some biological cover. Harder and rougher bottom types such as rocky outcrops or coarse sediment typically return stronger intensities (high backscatter, lighter tones), whereas softer bottom types such as fine sediment return weaker intensities (low backscatter, darker tones).

This part of DS 781 presents data for the faults for the geologic and geomorphic map of the Offshore Pigeon Point map area, California. The vector data file is included in "Faults_OffshorePigeonPoint.zip," which is accessible from https://doi.org/10.5066/F7513W80. These data accompany the pamphlet and map sheets of Cochrane, G.R., Watt, J.T., Dartnell, P., Greene, H.G., Erdey, M.D., Dieter, B.E., Golden, N.E., Johnson, S.Y., Endris, C.A., Hartwell, S.R., Kvitek, R.G., Davenport, C.W., Krigsman, L.M., Ritchie, A.C., Sliter, R.W., Finlayson, D.P., and Maier, K.L. (G.R. Cochrane and S.A. Cochran, eds.), 2015, California State Waters Map Series—Offshore of Pigeon Point, California: U.S. Geological Survey Open-File Report 2015–1232, pamphlet 40 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20151232.

This part of DS 781 presents data for the acoustic-backscatter map of Offshore of Santa Cruz map area, California. Backscatter data are provided as a raster file included in "Backscatter_Swath_OffshoreSantaCruz.zip," which is accessible from https://doi.org/10.5066/F7TM785G. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Johnson, S.Y., Erdey, M.D., Golden, N.E., Greene, H.G., Dieter, B.E., Hartwell, S.R., Ritchie, A.C., Finlayson, D.P., Endris, C.A., Watt, J.T., Davenport, C.W., Sliter, R.W., Maier, K.L., and Krigsman, L.M. (G.R. Cochrane and S.A. Cochran, eds.), 2016, California State Waters Map Series—Offshore of Santa Cruz, California: U.S. Geological Survey Open-File Report 2016-1024, pamphlet 40 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20161024. The acoustic-backscatter map of the Offshore of Santa Cruz, California was generated from backscatter data collected by the U.S. Geological Survey (USGS). Mapping was completed in 2009, using a 234-kHz SWATHplus bathymetric sidescan-sonar system. Within the final imagery, brighter tones indicate higher backscatter intensity, and darker tones indicate lower backscatter intensity. The intensity represents a complex interaction between the acoustic pulse and the seafloor, as well as characteristics within the shallow subsurface, providing a general indication of seafloor texture and composition. Backscatter intensity depends on the acoustic source level; the frequency used to image the seafloor; the grazing angle; the composition and character of the seafloor, including grain size, water content, bulk density, and seafloor roughness; and some biological cover. Harder and rougher bottom types such as rocky outcrops or coarse sediment typically return stronger intensities (high backscatter, lighter tones), whereas softer bottom types such as fine sediment return weaker

This part of DS 781 presents data for the shaded-relief bathymetry map of Offshore Santa Cruz, California. The raster data file is included in "BathymetryHS_OffshoreSantaCruz.zip", which is accessible from https://doi.org/10.5066/F7TM785G. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Johnson, S.Y., Erdey, M.D., Golden, N.E., Greene, H.G., Dieter, B.E., Hartwell, S.R., Ritchie, A.C., Finlayson, D.P., Endris, C.A., Watt, J.T., Davenport, C.W., Sliter, R.W., Maier, K.L., and Krigsman, L.M. (G.R. Cochrane and S.A. Cochran, eds.), 2016, California State Waters Map Series—Offshore of Santa Cruz, California: U.S. Geological Survey Open-File Report 2016-1024, pamphlet 40 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20161024. The shaded-relief bathymetry map of Offshore Santa Cruz, California, was generated from bathymetry data collected by the U.S. Geological Survey (USGS). Mapping was completed in 2009 using a 234-kHz SWATHplus bathymetric sidescan-sonar system. The mapping mission collected bathymetry data from about the 10-m isobath to beyond the 3-nautical-mile limit of California's State Waters. NOTE: The horizontal datum of this bathymetry data (NAD83) differs from the horizontal datum of other layers in this data release (WGS84).

This part of DS 781 presents data for the bathymetry map of Offshore Santa Cruz, California. The raster data file is included in "Bathymetry_OffshoreSantaCruz.zip", which is accessible from https://doi.org/10.5066/F7TM785G. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Johnson, S.Y., Erdey, M.D., Golden, N.E., Greene, H.G., Dieter, B.E., Hartwell, S.R., Ritchie, A.C., Finlayson, D.P., Endris, C.A., Watt, J.T., Davenport, C.W., Sliter, R.W., Maier, K.L., and Krigsman, L.M. (G.R. Cochrane and S.A. Cochran, eds.), 2016, California State Waters Map Series—Offshore of Santa Cruz, California: U.S. Geological Survey Open-File Report 2016-1024, pamphlet 40 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20161024. The bathymetry map of Offshore Santa Cruz, California, was generated from bathymetry data collected by the U.S. Geological Survey (USGS). Mapping was completed in 2009 using a 234-kHz SWATHplus bathymetric sidescan-sonar system. The mapping mission collected bathymetry data from about the 10-m isobath to beyond the 3-nautical-mile limit of California's State Waters. NOTE: The horizontal datum of this bathymetry data (NAD83) differs from the horizontal datum of other layers in this data release (WGS84).

This part of DS 781 presents data for the bathymetric contours for several seafloor maps of the Offshore Santa Cruz map area, California. The vector data file is included in "Contours_OffshoreSantaCruz.zip", which is accessible from https://doi.org/10.5066/F7TM785G. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Johnson, S.Y., Erdey, M.D., Golden, N.E., Greene, H.G., Dieter, B.E., Hartwell, S.R., Ritchie, A.C., Finlayson, D.P., Endris, C.A., Watt, J.T., Davenport, C.W., Sliter, R.W., Maier, K.L., and Krigsman, L.M. (G.R. Cochrane and S.A. Cochran, eds.), 2016, California State Waters Map Series—Offshore of Santa Cruz, California: U.S. Geological Survey Open-File Report 2016-1024, pamphlet 40 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20161024. 10-m interval contours of the Offshore Santa Cruz map area, California, were generated from bathymetry data collected by the U.S. Geological Survey (USGS). Mapping was completed in 2009 using a 234-kHz SWATHplus bathymetric sidescan-sonar system. The mapping mission collected bathymetry data from about the 10-m isobath to beyond the 3-nautical-mile limit of California's State Waters.

This part of DS 781 presents the seafloor-character map Offshore of Santa Cruz, California. The raster data file is included in "SeafloorCharacter_OffshoreSantaCruz.zip," which is accessible from https://doi.org/10.5066/F7TM785G. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Johnson, S.Y., Erdey, M.D., Golden, N.E., Greene, H.G., Dieter, B.E., Hartwell, S.R., Ritchie, A.C., Finlayson, D.P., Endris, C.A., Watt, J.T., Davenport, C.W., Sliter, R.W., Maier, K.L., and Krigsman, L.M. (G.R. Cochrane and S.A. Cochran, eds.), 2016, California State Waters Map Series—Offshore of Santa Cruz, California: U.S. Geological Survey Open-File Report 2016-1024, pamphlet 40 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20161024. This raster-format seafloor character map shows five substrate classes Offshore of Santa Cruz, California. The substrate classes mapped in this area have been further divided into the following California Marine Life Protection Act depth zones and slope classes: Depth Zone 2 (intertidal to 30 m), Depth Zone 3 (30 to 100 m), Slope Class 1 (0 degrees - 5 degrees), and Slope Class 2 (5 degrees - 30 degrees). Depth Zone 1 (intertidal), Depth Zones 4-5 (greater than 100 m), and Slopes Classes 3-4 (greater than 30 degrees) are not present in the region covered by this block. The map is created using a supervised classification method described by Cochrane (2008). Reference Cited: Cochrane, G.R., 2008, Video-supervised classification of sonar data for mapping seafloor habitat, in Reynolds, J.R., and Greene, H.G., eds., Marine habitat mapping technology for Alaska: Fairbanks, University of Alaska, Alaska Sea Grant College Program, p. 185-194, accessed April 5, 2011, at http://doc.nprb.org/web/research/research%20pubs/615_habitat_mapping_workshop/Individual%20Chapters%20High-Res/Ch13%20Cochrane.pdf. Sappington, J.M., Longshore, K.M., and Thompson, D.B., 2007, Quantifying landscape ruggedness for animal habitat analysis--A case study using bighorn sheep in the Mojave Desert: Journal of Wildlife Management, v. 71, p. 1419-1426.

This part of DS 781 presents data for the bathymetry map of Drakes Bay and Vicinity map area, California. The raster data file for the bathymetry map is included in "Bathymetry_DrakesBay.zip," which is accessible from https://pubs.usgs.gov/ds/781/DrakesBay/data_catalog_DrakesBay.html. These data accompany the pamphlet and map sheets of Watt, J.T., Dartnell, P., Golden, N.E., Greene, H.G., Erdey, M.D., Cochrane, G.R., Johnson, S.Y., Hartwell, S.R., Kvitek, R.G., Manson, M.W., Endris, C.A., Dieter, B.E., Sliter, R.W., Krigsman, L.M., Lowe, E.N., and Chin, J.L. (J.T. Watt and S.A. Cochran, eds.), 2015, California State Waters Map Series—Drakes Bay and Vicinity, California: U.S. Geological Survey Open-File Report 2015–1041, pamphlet 36 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20151041. The bathymetry map of Drakes Bay and Vicinity map area, California, was generated from bathymetry data collected by California State University, Monterey Bay (CSUMB), and by Fugro Pelagos. Mapping was completed between 2007 and 2010, using a combination of 200-kHz and 400-kHz Reson 7125, and 244-kHz Reson 8101 multibeam echosounders, as well as 468-kHz SEA SWATHPlus interferometric system. These mapping missions combined to collect bathymetry from about the 10-m isobath to beyond the 3-nautical-mile limit of California's State Waters. NOTE: the horizontal datum of the bathymetry data (NAD83) differs from the horizontal datum of other layers in this data series (WGS84). Some bathymetry grids within this map were projected horizontally from WGS84 to NAD83 using Esri tools to be more consistent with the vertical reference of the North American Vertical Datum of 1988 (NAVD88). These data are not intended for navigational purposes.

This part of DS 781 presents data for the acoustic-backscatter map of Monterey Canyon and Vicinity map area, California. Backscatter data are provided as separate grids depending on mapping system and processing method. These metadata describe acoustic-backscatter data collected and processed by the U.S. Geological Survey. The raster data files are included in "BackscatterA_USGS_SWATH_MontereyCanyon.zip," which is accessible from https://doi.org/10.3133/ds781. These data accompany the pamphlet and map sheets of Dartnell, P., Maier, K.L., Erdey, M.D., Dieter, B.E., Golden, N.E., Johnson, S.Y., Hartwell, S.R., Cochrane, G.R., Ritchie, A.C., Finlayson, D.P., Kvitek, R.G., Sliter, R.W., Greene, H.G., Davenport, C.W., Endris, C.A., and Krigsman, L.M. (P. Dartnell and S.A. Cochran, eds.), 2016, California State Waters Map Series—Monterey Canyon and Vicinity, California: U.S. Geological Survey Open-File Report 2016–1072, 48 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20161072. The acoustic-backscatter map of Monterey Canyon and Vicinity, California, was generated from acoustic-backscatter data collected by the U.S. Geological Survey (USGS), by Monterey Bay Aquarium Research Institute (MBARI), and by California State University, Monterey Bay (CSUMB). Mapping for the entire map area was completed between 1998 and 2014 using a combination of 30-kHz Simrad EM-300 and 200-kHz/400-kHz Reson 7125 multibeam echosounders, as well as 234-kHz and 468-kHz SEA SWATHplus bathymetric sidescan-sonar systems. The USGS mapping was completed in 2009 and 2014. Within the final imagery, brighter tones indicate higher backscatter intensity, and darker tones indicate lower backscatter intensity. The intensity represents a complex interaction between the acoustic pulse and the seafloor, as well as characteristics within the shallow subsurface, providing a general indication of seafloor texture and composition. Backscatter intensity depends on the acoustic source level; the frequency used to image the seafloor; the grazing angle; the composition and character of the seafloor, including grain size, water content, bulk density, and seafloor roughness; and some biological cover. Harder and rougher bottom types such as rocky outcrops or coarse sediment typically return stronger intensities (high backscatter, lighter tones), whereas softer bottom types such as fine sediment return weaker intensities (low backscatter, darker tones).

This part of DS 781 presents data for the acoustic-backscatter map of Monterey Canyon and Vicinity map area, California. Backscatter data are provided as separate grids depending on mapping system and processing method. These metadata describe acoustic-backscatter data collected by Monterey Bay Aquarium Research Institute (MBARI) and processed by the U.S. Geological Survey. The raster data files are included in "BackscatterB_EM300_MontereyCanyon.zip," which is accessible from https://doi.org/10.3133/ds781. These data accompany the pamphlet and map sheets of Dartnell, P., Maier, K.L., Erdey, M.D., Dieter, B.E., Golden, N.E., Johnson, S.Y., Hartwell, S.R., Cochrane, G.R., Ritchie, A.C., Finlayson, D.P., Kvitek, R.G., Sliter, R.W., Greene, H.G., Davenport, C.W., Endris, C.A., and Krigsman, L.M. (P. Dartnell and S.A. Cochran, eds.), 2016, California State Waters Map Series—Monterey Canyon and Vicinity, California: U.S. Geological Survey Open-File Report 2016–1072, 48 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20161072. The acoustic-backscatter map of Monterey Canyon and Vicinity, California, were generated from acoustic-backscatter data collected by the U.S. Geological Survey (USGS), by Monterey Bay Aquarium Research Institute (MBARI), and by California State University, Monterey Bay (CSUMB). Mapping for the entire map area was completed between 1998 and 2014 using a combination of 30-kHz Simrad EM-300 and 200-kHz/400-kHz Reson 7125 multibeam echosounders, as well as 234-kHz and 468-kHz SEA SWATHplus bathymetric sidescan-sonar systems. The MBARI mapping was completed in 1998, the data were downloaded and reprocessed by the USGS in 2014. Within the final imagery, brighter tones indicate higher backscatter intensity, and darker tones indicate lower backscatter intensity. The intensity represents a complex interaction between the acoustic pulse and the seafloor, as well as characteristics within the shallow subsurface, providing a general indication of seafloor texture and composition. Backscatter intensity depends on the acoustic source level; the frequency used to image the seafloor; the grazing angle; the composition and character of the seafloor, including grain size, water content, bulk density, and seafloor roughness; and some biological cover. Harder and rougher bottom types such as rocky outcrops or coarse sediment typically return stronger intensities (high backscatter, lighter tones), whereas softer bottom types such as fine sediment return weaker intensities (low backscatter, darker tones).

This part of DS 781 presents data for the acoustic-backscatter map of Monterey Canyon and Vicinity map area, California. Backscatter data are provided as separate grids depending on mapping system and processing method. These metadata describe acoustic-backscatter data collected by California State University, Monterey Bay and processed by the U.S. Geological Survey. The raster data files are included in "BackscatterC_7125_MontereyCanyon.zip," which is accessible from https://doi.org/10.5066/F7XD0ZQ4. These data accompany the pamphlet and map sheets of Dartnell, P., Maier, K.L., Erdey, M.D., Dieter, B.E., Golden, N.E., Johnson, S.Y., Hartwell, S.R., Cochrane, G.R., Ritchie, A.C., Finlayson, D.P., Kvitek, R.G., Sliter, R.W., Greene, H.G., Davenport, C.W., Endris, C.A., and Krigsman, L.M. (P. Dartnell and S.A. Cochran, eds.), 2016, California State Waters Map Series—Monterey Canyon and Vicinity, California: U.S. Geological Survey Open-File Report 2016–1072, 48 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20161072. The acoustic-backscatter map of Monterey Canyon and Vicinity, California, were generated from acoustic-backscatter data collected by the U.S. Geological Survey (USGS), by Monterey Bay Aquarium Research Institute (MBARI), and by California State University, Monterey Bay (CSUMB). Mapping for the entire map area was completed between 1998 and 2014 using a combination of 30-kHz Simrad EM-300 and 200-kHz/400-kHz Reson 7125 multibeam echosounders, as well as 234-kHz and 468-kHz SEA SWATHplus bathymetric sidescan-sonar systems. The CSUMB mapping missions were completed in 2008 and 2009. Within the final imagery, brighter tones indicate higher backscatter intensity, and darker tones indicate lower backscatter intensity. The intensity represents a complex interaction between the acoustic pulse and the seafloor, as well as characteristics within the shallow subsurface, providing a general indication of seafloor texture and composition. Backscatter intensity depends on the acoustic source level; the frequency used to image the seafloor; the grazing angle; the composition and character of the seafloor, including grain size, water content, bulk density, and seafloor roughness; and some biological cover. Harder and rougher bottom types such as rocky outcrops or coarse sediment typically return stronger intensities (high backscatter, lighter tones), whereas softer bottom types such as fine sediment return weaker intensities (low backscatter, darker tones).

This part of DS 781 presents data for the acoustic-backscatter map of Monterey Canyon and Vicinity map area, California. Backscatter data are provided as separate grids depending on mapping system and processing method. These metadata describe acoustic-backscatter data collected by California State University, Monterey Bay and processed by the U.S. Geological Survey. The raster data files are included in "BackscatterD_CSUMB_SWATH_MontereyCanyon.zip," which is accessible from https://doi.org/10.5066/F7XD0ZQ4. These data accompany the pamphlet and map sheets of Dartnell, P., Maier, K.L., Erdey, M.D., Dieter, B.E., Golden, N.E., Johnson, S.Y., Hartwell, S.R., Cochrane, G.R., Ritchie, A.C., Finlayson, D.P., Kvitek, R.G., Sliter, R.W., Greene, H.G., Davenport, C.W., Endris, C.A., and Krigsman, L.M. (P. Dartnell and S.A. Cochran, eds.), 2016, California State Waters Map Series—Monterey Canyon and Vicinity, California: U.S. Geological Survey Open-File Report 2016–1072, 48 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20161072. The acoustic-backscatter map of Monterey Canyon and Vicinity, California, were generated from acoustic-backscatter data collected by the U.S. Geological Survey (USGS), by Monterey Bay Aquarium Research Institute (MBARI), and by California State University, Monterey Bay (CSUMB). Mapping for the entire map area was completed between 1998 and 2014 using a combination of 30-kHz Simrad EM-300 and 200-kHz/400-kHz Reson 7125 multibeam echosounders, as well as 234-kHz and 468-kHz SEA SWATHplus bathymetric sidescan-sonar systems. The CSUMB mapping missions were completed in 2008 and 2009. Within the final imagery, brighter tones indicate higher backscatter intensity, and darker tones indicate lower backscatter intensity. The intensity represents a complex interaction between the acoustic pulse and the seafloor, as well as characteristics within the shallow subsurface, providing a general indication of seafloor texture and composition. Backscatter intensity depends on the acoustic source level; the frequency used to image the seafloor; the grazing angle; the composition and character of the seafloor, including grain size, water content, bulk density, and seafloor roughness; and some biological cover. Harder and rougher bottom types such as rocky outcrops or coarse sediment typically return stronger intensities (high backscatter, lighter tones), whereas softer bottom types such as fine sediment return weaker intensities (low backscatter, darker tones).

This part of DS 781 presents data for 2-m and 5-m bathymetry and shaded-relief maps of Monterey Canyon and Vicinity, California. Bathymetry data are provided as separate grids depending on the mapping resolution. Data collected at shallower depths by the U.S. Geological Survey (USGS) and California State University, Monterey Bay (CSUMB) have a spatial resolution of 2 m per pixel, whereas data collected at deeper depths by the Monterey Bay Aquarium Research Institute (MBARI) have a spatial resolution of 5-m per pixel. This metadata file describes the shaded-relief 2-m data collected by the USGS and CSUMB, and processed by the USGS. The raster data file is included in "BathymetryAHS_2m_MontereyCanyon.zip," which is accessible from https://doi.org/10.5066/F7XD0ZQ4. These data accompany the pamphlet and map sheets of Dartnell, P., Maier, K.L., Erdey, M.D., Dieter, B.E., Golden, N.E., Johnson, S.Y., Hartwell, S.R., Cochrane, G.R., Ritchie, A.C., Finlayson, D.P., Kvitek, R.G., Sliter, R.W., Greene, H.G., Davenport, C.W., Endris, C.A., and Krigsman, L.M. (P. Dartnell and S.A. Cochran, eds.), 2016, California State Waters Map Series—Monterey Canyon and Vicinity, California: U.S. Geological Survey Open-File Report 2016–1072, 48 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20161072. The 2-m and 5-m bathymetry and shaded-relief maps of Monterey Canyon and Vicinity, California, were generated from data collected between 1998 and 2014 using a combination of 30-kHz Simrad EM-300 and 200-kHz/400-kHz Reson 7125 multibeam echosounders, as well as 234-kHz and 468-kHz SEA SWATHplus bathymetric sidescan-sonar systems. The mapping missions collected bathymetry data from about the 10-m isobath to beyond the 3-nautical-mile limit of California's State Waters. NOTE: The horizontal datum of this bathymetry data (NAD83) differs from the horizontal datum of other layers in this data release (WGS84).

This part of DS 781 presents data for 2-m and 5-m bathymetry and shaded-relief maps of Monterey Canyon and Vicinity, California. Bathymetry data are provided as separate grids depending on the mapping resolution. Data collected at shallower depths by the U.S. Geological Survey (USGS) and California State University, Monterey Bay (CSUMB) have a spatial resolution of 2 m per pixel, whereas data collected at deeper depths by the Monterey Bay Aquarium Research Institute (MBARI) have a spatial resolution of 5-m per pixel. This metadata file describes the 2-m data collected by the USGS and CSUMB, and processed by the USGS. The raster data file is included in "BathymetryA_2m_MontereyCanyon.zip," which is accessible from https://doi.org/10.5066/F7XD0ZQ4. These data accompany the pamphlet and map sheets of Dartnell, P., Maier, K.L., Erdey, M.D., Dieter, B.E., Golden, N.E., Johnson, S.Y., Hartwell, S.R., Cochrane, G.R., Ritchie, A.C., Finlayson, D.P., Kvitek, R.G., Sliter, R.W., Greene, H.G., Davenport, C.W., Endris, C.A., and Krigsman, L.M. (P. Dartnell and S.A. Cochran, eds.), 2016, California State Waters Map Series—Monterey Canyon and Vicinity, California: U.S. Geological Survey Open-File Report 2016–1072, 48 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20161072. The 2-m and 5-m bathymetry and shaded-relief maps of Monterey Canyon and Vicinity, California, were generated from data collected between 1998 and 2014 using a combination of 30-kHz Simrad EM-300 and 200-kHz/400-kHz Reson 7125 multibeam echosounders, as well as 234-kHz and 468-kHz SEA SWATHplus bathymetric sidescan-sonar systems. The mapping missions collected bathymetry data from about the 10-m isobath to beyond the 3-nautical-mile limit of California's State Waters. NOTE: The horizontal datum of this bathymetry data (NAD83) differs from the horizontal datum of other layers in this data release (WGS84).

This part of DS 781 presents data for 2-m and 5-m bathymetry and shaded-relief maps of Monterey Canyon and Vicinity, California. Bathymetry data are provided as separate grids depending on the mapping resolution. Data collected at shallower depths by the U.S. Geological Survey (USGS) and California State University, Monterey Bay (CSUMB) have a spatial resolution of 2 m per pixel, whereas data collected at deeper depths by the Monterey Bay Aquarium Research Institute (MBARI) have a spatial resolution of 5-m per pixel. This metadata file describes the shaded-relief 5-m data collected by MBARI and processed by the USGS. The raster data file is included in "BathymetryBHS_5m_MontereyCanyon.zip," which is accessible from https://doi.org/10.5066/F7XD0ZQ4. These data accompany the pamphlet and map sheets of Dartnell, P., Maier, K.L., Erdey, M.D., Dieter, B.E., Golden, N.E., Johnson, S.Y., Hartwell, S.R., Cochrane, G.R., Ritchie, A.C., Finlayson, D.P., Kvitek, R.G., Sliter, R.W., Greene, H.G., Davenport, C.W., Endris, C.A., and Krigsman, L.M. (P. Dartnell and S.A. Cochran, eds.), 2016, California State Waters Map Series—Monterey Canyon and Vicinity, California: U.S. Geological Survey Open-File Report 2016–1072, 48 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20161072. The 2-m and 5-m bathymetry and shaded-relief maps of Monterey Canyon and Vicinity, California, were generated from data collected between 1998 and 2014 using a combination of 30-kHz Simrad EM-300 and 200-kHz/400-kHz Reson 7125 multibeam echosounders, as well as 234-kHz and 468-kHz SEA SWATHplus bathymetric sidescan-sonar systems. The mapping missions collected bathymetry data from about the 10-m isobath to beyond the 3-nautical-mile limit of California's State Waters. NOTE: The horizontal datum of this bathymetry data (NAD83) differs from the horizontal datum of other layers in this data release (WGS84).

This part of DS 781 presents data for 2-m and 5-m bathymetry and shaded-relief maps of Monterey Canyon and Vicinity, California. Bathymetry data are provided as separate grids depending on the mapping resolution. Data collected at shallower depths by the U.S. Geological Survey (USGS) and California State University, Monterey Bay (CSUMB) have a spatial resolution of 2 m per pixel, whereas data collected at deeper depths by the Monterey Bay Aquarium Research Institute (MBARI) have a spatial resolution of 5-m per pixel. This metadata file describes the 5-m data collected by MBARI and processed by the USGS. The raster data file is included in "BathymetryB_5m_MontereyCanyon.zip," which is accessible from https://doi.org/10.5066/F7XD0ZQ4. These data accompany the pamphlet and map sheets of Dartnell, P., Maier, K.L., Erdey, M.D., Dieter, B.E., Golden, N.E., Johnson, S.Y., Hartwell, S.R., Cochrane, G.R., Ritchie, A.C., Finlayson, D.P., Kvitek, R.G., Sliter, R.W., Greene, H.G., Davenport, C.W., Endris, C.A., and Krigsman, L.M. (P. Dartnell and S.A. Cochran, eds.), 2016, California State Waters Map Series—Monterey Canyon and Vicinity, California: U.S. Geological Survey Open-File Report 2016–1072, 48 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20161072. The 2-m and 5-m bathymetry and shaded-relief maps of Monterey Canyon and Vicinity, California, were generated from data collected between 1998 and 2014 using a combination of 30-kHz Simrad EM-300 and 200-kHz/400-kHz Reson 7125 multibeam echosounders, as well as 234-kHz and 468-kHz SEA SWATHplus bathymetric sidescan-sonar systems. The mapping missions collected bathymetry data from about the 10-m isobath to beyond the 3-nautical-mile limit of California's State Waters. NOTE: The horizontal datum of this bathymetry data (NAD83) differs from the horizontal datum of other layers in this data release (WGS84).

This part of DS 781 presents bathymetric contours for several seafloor maps of the Monterey Canyon and Vicinity map area, California. The shapefile is included in "Contours_MontereyCanyon.zip," which is accessible from https://doi.org/10.3133/ofr20161072. These data accompany the pamphlet and map sheets of Dartnell, P., Maier, K.L., Erdey, M.D., Dieter, B.E., Golden, N.E., Johnson, S.Y., Hartwell, S.R., Cochrane, G.R., Ritchie, A.C., Finlayson, D.P., Kvitek, R.G., Sliter, R.W., Greene, H.G., Davenport, C.W., Endris, C.A., and Krigsman, L.M. (P. Dartnell and S.A. Cochran, eds.), 2016, California State Waters Map Series—Monterey Canyon and Vicinity, California: U.S. Geological Survey Open-File Report 2016–1072, 48 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20161072. Bathymetric contours of the Monterey Canyon and Vicinity map area, California, were generated from bathymetry data collected by the U.S. Geological Survey (USGS), by Monterey Bay Aquarium Research Institute (MBARI), and by California State University, Monterey Bay (CSUMB). Mapping was completed between 1998 and 2014 using a combination of 30-kHz Simrad EM-300 and 200-kHz/400-kHz Reson 7125 multibeam echosounders, as well as 234-kHz and 468-kHz SEA SWATHplus bathymetric sidescan-sonar systems. The mapping missions collected bathymetry data from about the 10-m isobath to beyond the 3-nautical-mile limit of California's State Waters. Bathymetric contours were generated separately from the modified 2-m and 5-m bathymetric surface then merged to one final contour dataset. 10-m intervals were generated in water depths shallower than 100 m, at 50-m intervals from 100 to 200 m, and at 200-m intervals in water depths deeper than 200 m. The original surface was smoothed using the Focal Mean tool in ArcGIS and a circular neighborhood with a radius of 20 to 30 m (depending on the area). The contours were generated from this smoothed surface using the ArcGIS Spatial Analyst Contour tool. The most continuous contour segments were preserved; smaller segments and isolated island polygons were excluded from the final output.

This part of DS 781 presents data for the geologic and geomorphic map of Monterey Canyon and Vicinity, California. The vector data file is included in "Geology_MontereyCanyon.zip," which is accessible from http://pubs.usgs.gov/ds/781/MontereyCanyon/data_catalog_MontereyCanyon.html. These data accompany the pamphlet and map sheets of Dartnell, P., Maier, K.L., Erdey, M.D., Dieter, B.E., Golden, N.E., Johnson, S.Y., Hartwell, S.R., Cochrane, G.R., Ritchie, A.C., Finlayson, D.P., Kvitek, R.G., Sliter, R.W., Greene, H.G., Davenport, C.W., Endris, C.A., and Krigsman, L.M. (P. Dartnell and S.A. Cochran, eds.), 2016, California State Waters Map Series—Monterey Canyon and Vicinity, California: U.S. Geological Survey Open-File Report 2016–1072, 48 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20161072. Marine geology and geomorphology were mapped in the Monterey Canyon and Vicinity map area from approximate Mean High Water (MHW) across the continental shelf, as well as in Monterey Canyon to a water depth of about 1,750 m. This map area includes much of central Monterey Bay, extending just beyond the limit of California’s State Waters (note that the California’s State Waters limit, which generally is 3 nautical miles [5.6 km] from shore, extends farther offshore (as much as 12 nautical miles) between Santa Cruz and Monterey, so that it encompasses all of Monterey Bay. Offshore geologic units were delineated on the basis of integrated analyses of adjacent onshore geology with multibeam bathymetry and backscatter imagery, seafloor-sediment and rock samples, digital camera and video imagery, and high-resolution seismic reflection profiles. Aerial photographs taken in multiple years were used to map the nearshore area (0 to 10 m water depth) and to link the offshore and onshore geology.

This part of DS 781 presents data for the habitat map of the seafloor of the Monterey Canyon and Vicinity map area, California. The vector data file is included in "Habitat_MontereyCanyon.zip," which is accessible from https://doi.org/10.5066/F7XD0ZQ4. These data accompany the pamphlet and map sheets of Dartnell, P., Maier, K.L., Erdey, M.D., Dieter, B.E., Golden, N.E., Johnson, S.Y., Hartwell, S.R., Cochrane, G.R., Ritchie, A.C., Finlayson, D.P., Kvitek, R.G., Sliter, R.W., Greene, H.G., Davenport, C.W., Endris, C.A., and Krigsman, L.M. (P. Dartnell and S.A. Cochran, eds.), 2016, California State Waters Map Series—Monterey Canyon and Vicinity, California: U.S. Geological Survey Open-File Report 2016–1072, 48 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20161072. Using multibeam echosounder (MBES) bathymetry and backscatter data collected and processed between 1998 and 2014, potential marine benthic habitat maps were constructed. The habitats were based on substrate types and documented or "ground truthed" using underwater video images and seafloor samples obtained by the USGS. These maps display various habitat types that range from flat, soft, unconsolidated sediment-covered seafloor to hard, deformed (folded), or highly rugose and differentially eroded bedrock exposures. Rugged, high-relief, rocky outcrops that have been eroded to form ledges and small caves are ideal habitat for rockfish (Sebastes spp.) and other bottom fish such as lingcod (Ophiodon elongatus). Habitat map is presented in a map format generated in a GIS (ArcMap), and both digital and hard-copy versions will be produced. Please refer to Greene and others (2007) for more information regarding the Benthic Marine Potential Habitat Classification Scheme and the codes used to represent various seafloor features. References Cited: Greene, H.G., Bizzarro, J.J., O'Connell, V.M., and Brylinsky, C.K., 2007, Construction of digital potential marine benthic habitat maps using a coded classification scheme and its application, in Todd, B.J., and Greene, H.G., eds., Mapping the seafloor for habitat characterization: Geological Association of Canada Special Paper 47, p. 141-155.

This part of DS 781 presents data for the paleoshorelines for the geologic and geomorphic map of Monterey Canyon and Vicinity, California. The vector data file is included in "Paleoshorelines_MontereyCanyon.zip," which is accessible from https://doi.org/10.3133/ofr20161072. These data accompany the pamphlet and map sheets of Dartnell, P., Maier, K.L., Erdey, M.D., Dieter, B.E., Golden, N.E., Johnson, S.Y., Hartwell, S.R., Cochrane, G.R., Ritchie, A.C., Finlayson, D.P., Kvitek, R.G., Sliter, R.W., Greene, H.G., Davenport, C.W., Endris, C.A., and Krigsman, L.M. (P. Dartnell and S.A. Cochran, eds.), 2016, California State Waters Map Series—Monterey Canyon and Vicinity, California: U.S. Geological Survey Open-File Report 2016–1072, 48 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20161072.

This part of DS 781 presents the seafloor-character map of Monterey Canyon and Vicinity, California. The raster data file is included in "SeafloorCharacter_2m_MontereyCanyon.zip," which is accessible from https://doi.org/10.3133/ds781. These data accompany the pamphlet and map sheets of Dartnell, P., Maier, K.L., Erdey, M.D., Dieter, B.E., Golden, N.E., Johnson, S.Y., Hartwell, S.R., Cochrane, G.R., Ritchie, A.C., Finlayson, D.P., Kvitek, R.G., Sliter, R.W., Greene, H.G., Davenport, C.W., Endris, C.A., and Krigsman, L.M. (P. Dartnell and S.A. Cochran, eds.), 2016, California State Waters Map Series—Monterey Canyon and Vicinity, California: U.S. Geological Survey Open-File Report 2016–1072, 48 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20161072. This raster-format seafloor character map shows five substrate classes in Monterey Canyon and Vicinity, California. The substrate classes mapped in this area have been further divided into the following California Marine Life Protection Act depth zones and slope classes: Depth Zone 2 (intertidal to 30 m), Depth Zone 3 (30 to 100 m), Depth Zone 4 (100 to 200 m), Slope Class 1 (0 degrees - 5 degrees), and Slope Class 2 (5 degrees - 30 degrees). Depth Zone 1 (intertidal), Depth Zone 5 (greater than 200 m), and Slopes Classes 3-4 (greater than 30 degrees) are not present in the region covered by this block. The map is created using a supervised classification method described by Cochrane (2008), with multibeam echosounder (MBES) bathymetry and backscatter data collected and processed between 1998 and 2014, along with ground-truth verification from underwater video and sediment samples. Reference Cited: Cochrane, G.R., 2008, Video-supervised classification of sonar data for mapping seafloor habitat, in Reynolds, J.R., and Greene, H.G., eds., Marine habitat mapping technology for Alaska: Fairbanks, University of Alaska, Alaska Sea Grant College Program, p. 185-194, accessed April 5, 2011, at http://doc.nprb.org/web/research/research%20pubs/615_habitat_mapping_workshop/Individual%20Chapters%20High-Res/Ch13%20Cochrane.pdf.

This part of DS 781 presents the seafloor-character map of Monterey Canyon and Vicinity, California. The raster data file is included in "SeafloorCharacter_5m_MontereyCanyon.zip," which is accessible from https://doi.org/10.3133/ds781. These data accompany the pamphlet and map sheets of Dartnell, P., Maier, K.L., Erdey, M.D., Dieter, B.E., Golden, N.E., Johnson, S.Y., Hartwell, S.R., Cochrane, G.R., Ritchie, A.C., Finlayson, D.P., Kvitek, R.G., Sliter, R.W., Greene, H.G., Davenport, C.W., Endris, C.A., and Krigsman, L.M. (P. Dartnell and S.A. Cochran, eds.), 2016, California State Waters Map Series—Monterey Canyon and Vicinity, California: U.S. Geological Survey Open-File Report 2016–1072, 48 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20161072. This raster-format seafloor character map shows five substrate classes in Monterey Canyon and Vicinity, California. The substrate classes mapped in this area have been further divided into the following California Marine Life Protection Act depth zones and slope classes: Depth Zone 2 (intertidal to 30 m), Depth Zone 3 (30 to 100 m), Depth Zone 4 (100 to 200 m), Slope Class 1 (0 degrees - 5 degrees), and Slope Class 2 (5 degrees - 30 degrees). Depth Zone 1 (intertidal), Depth Zone 5 (greater than 200 m), and Slopes Classes 3-4 (greater than 30 degrees) are not present in the region covered by this block. The map is created using a supervised classification method described by Cochrane (2008), with multibeam echosounder (MBES) bathymetry and backscatter data collected and processed between 1998 and 2014, along with ground-truth verification from underwater video and sediment samples. Reference Cited: Cochrane, G.R., 2008, Video-supervised classification of sonar data for mapping seafloor habitat, in Reynolds, J.R., and Greene, H.G., eds., Marine habitat mapping technology for Alaska: Fairbanks, University of Alaska, Alaska Sea Grant College Program, p. 185-194, accessed April 5, 2011, at http://doc.nprb.org/web/research/research%20pubs/615_habitat_mapping_workshop/Individual%20Chapters%20High-Res/Ch13%20Cochrane.pdf.

This part of DS 781 presents data for the acoustic-backscatter map of the Offshore of Monterey map area, California. Backscatter data are provided as separate grids depending on resolution. This metadata file refers to the data included in "Backscatter_5m_OffshoreMonterey.zip," which is accessible from https://doi.org/10.5066/F70Z71C8. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Hartwell, S.R., Cochrane, G.R., Golden, N.E., Watt, J.T., Davenport, C.W., Kvitek, R.G., Erdey, M.D., Krigsman, L.M., Sliter, R.W., and Maier, K.L. (S.Y. Johnson and S.A. Cochran, eds.), 2016, California State Waters Map Series—Offshore of Monterey, California: U.S. Geological Survey Open-File Report 2016–1110, pamphlet 44 p., 10 sheets, scale 1:24,000, http://dx.doi.org/10.3133/ofr20161110. The acoustic-backscatter map of the Offshore of Monterey map area in central California was generated from backscatter data collected by California State University, Monterey Bay (CSUMB) and by Monterey Bay Aquarium Research Institute (MBARI). Mapping was completed between 1998 and 2012 using a combination of multibeam echosounders including 200-kHz/400-kHz Reson 7125, 100-kHz Reson 7111, 240 kHz Reson 8101, and 30-kHz Simrad EM-300 as well as 234-kHz and 468-kHz SWATHplus bathymetric sidescan-sonar system. Within the final imagery, brighter tones indicate higher backscatter intensity, and darker tones indicate lower backscatter intensity. The intensity represents a complex interaction between the acoustic pulse and the seafloor, as well as characteristics within the shallow subsurface, providing a general indication of seafloor texture and composition. Backscatter intensity depends on the acoustic source level; the frequency used to image the seafloor; the grazing angle; the composition and character of the seafloor, including grain size, water content, bulk density, and seafloor roughness; and some biological cover. Harder and rougher bottom types such as rocky outcrops or coarse sediment typically return stronger intensities (high backscatter, lighter tones), whereas softer bottom types such as fine sediment return weaker intensities (low backscatter, darker tones).

This part of DS 781 presents data for the acoustic-backscatter map of the Offshore of Monterey map area, California. Backscatter data are provided as separate grids depending on resolution. This metadata file refers to the data included in "Backscatter_7125_OffshoreMonterey.zip," which is accessible from https://doi.org/10.5066/F70Z71C8. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Hartwell, S.R., Cochrane, G.R., Golden, N.E., Watt, J.T., Davenport, C.W., Kvitek, R.G., Erdey, M.D., Krigsman, L.M., Sliter, R.W., and Maier, K.L. (S.Y. Johnson and S.A. Cochran, eds.), 2016, California State Waters Map Series—Offshore of Monterey, California: U.S. Geological Survey Open-File Report 2016–1110, pamphlet 44 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20161110. The acoustic-backscatter map of the Offshore of Monterey map area in central California was generated from backscatter data collected by California State University, Monterey Bay (CSUMB) and by Monterey Bay Aquarium Research Institute (MBARI). Mapping was completed between 1998 and 2012 using a combination of multibeam echosounders including 200-kHz/400-kHz Reson 7125, 100-kHz Reson 7111, 240 kHz Reson 8101, and 30-kHz Simrad EM-300 as well as 234-kHz and 468-kHz SWATHplus bathymetric sidescan-sonar system. Within the final imagery, brighter tones indicate higher backscatter intensity, and darker tones indicate lower backscatter intensity. The intensity represents a complex interaction between the acoustic pulse and the seafloor, as well as characteristics within the shallow subsurface, providing a general indication of seafloor texture and composition. Backscatter intensity depends on the acoustic source level; the frequency used to image the seafloor; the grazing angle; the composition and character of the seafloor, including grain size, water content, bulk density, and seafloor roughness; and some biological cover. Harder and rougher bottom types such as rocky outcrops or coarse sediment typically return stronger intensities (high backscatter, lighter tones), whereas softer bottom types such as fine sediment return weaker intensities (low backscatter, darker tones).

This part of DS 781 presents data for the acoustic-backscatter map of the Offshore of Monterey map area, California. Backscatter data are provided as separate grids depending on resolution. This metadata file refers to the data included in "Backscatter_8101_OffshoreMonterey.zip," which is accessible from https://doi.org/10.5066/F70Z71C8. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Hartwell, S.R., Cochrane, G.R., Golden, N.E., Watt, J.T., Davenport, C.W., Kvitek, R.G., Erdey, M.D., Krigsman, L.M., Sliter, R.W., and Maier, K.L. (S.Y. Johnson and S.A. Cochran, eds.), 2016, California State Waters Map Series—Offshore of Monterey, California: U.S. Geological Survey Open-File Report 2016–1110, pamphlet 44 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20161110. The acoustic-backscatter map of the Offshore of Monterey map area in central California was generated from backscatter data collected by California State University, Monterey Bay (CSUMB) and by Monterey Bay Aquarium Research Institute (MBARI). Mapping was completed between 1998 and 2012 using a combination of multibeam echosounders including 200-kHz/400-kHz Reson 7125, 100-kHz Reson 7111, 240 kHz Reson 8101, and 30-kHz Simrad EM-300 as well as 234-kHz and 468-kHz SWATHplus bathymetric sidescan-sonar system. Within the final imagery, brighter tones indicate higher backscatter intensity, and darker tones indicate lower backscatter intensity. The intensity represents a complex interaction between the acoustic pulse and the seafloor, as well as characteristics within the shallow subsurface, providing a general indication of seafloor texture and composition. Backscatter intensity depends on the acoustic source level; the frequency used to image the seafloor; the grazing angle; the composition and character of the seafloor, including grain size, water content, bulk density, and seafloor roughness; and some biological cover. Harder and rougher bottom types such as rocky outcrops or coarse sediment typically return stronger intensities (high backscatter, lighter tones), whereas softer bottom types such as fine sediment return weaker intensities (low backscatter, darker tones).

This part of DS 781 presents data for the acoustic-backscatter map of the Offshore of Monterey map area, California. Backscatter data are provided as separate grids depending on resolution. This metadata file refers to the data included in "Backscatter_Swath_OffshoreMonterey.zip," which is accessible from https://doi.org/10.5066/F70Z71C8. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Hartwell, S.R., Cochrane, G.R., Golden, N.E., Watt, J.T., Davenport, C.W., Kvitek, R.G., Erdey, M.D., Krigsman, L.M., Sliter, R.W., and Maier, K.L. (S.Y. Johnson and S.A. Cochran, eds.), 2016, California State Waters Map Series—Offshore of Monterey, California: U.S. Geological Survey Open-File Report 2016–1110, pamphlet 44 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20161110. The acoustic-backscatter map of the Offshore of Monterey map area in central California was generated from backscatter data collected by California State University, Monterey Bay (CSUMB) and by Monterey Bay Aquarium Research Institute (MBARI). Mapping was completed between 1998 and 2012 using a combination of multibeam echosounders including 200-kHz/400-kHz Reson 7125, 100-kHz Reson 7111, 240 kHz Reson 8101, and 30-kHz Simrad EM-300 as well as 234-kHz and 468-kHz SWATHplus bathymetric sidescan-sonar system. Within the final imagery, brighter tones indicate higher backscatter intensity, and darker tones indicate lower backscatter intensity. The intensity represents a complex interaction between the acoustic pulse and the seafloor, as well as characteristics within the shallow subsurface, providing a general indication of seafloor texture and composition. Backscatter intensity depends on the acoustic source level; the frequency used to image the seafloor; the grazing angle; the composition and character of the seafloor, including grain size, water content, bulk density, and seafloor roughness; and some biological cover. Harder and rougher bottom types such as rocky outcrops or coarse sediment typically return stronger intensities (high backscatter, lighter tones), whereas softer bottom types such as fine sediment return weaker intensities (low backscatter, darker tones).

This part of DS 781 presents data for the bathymetry map of the Offshore of Monterey map area, California. Bathymetry data are provided as separate grids depending on resolution. This metadata file refers to the data included in "BathymetryHS_2m_OffshoreMonterey.zip," which is accessible from https://doi.org/10.5066/F70Z71C8. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Hartwell, S.R., Cochrane, G.R., Golden, N.E., Watt, J.T., Davenport, C.W., Kvitek, R.G., Erdey, M.D., Krigsman, L.M., Sliter, R.W., and Maier, K.L. (S.Y. Johnson and S.A. Cochran, eds.), 2016, California State Waters Map Series—Offshore of Monterey, California: U.S. Geological Survey Open-File Report 2016–1110, pamphlet 44 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20161110. The 2-m and 5-m bathymetry and shaded-relief bathymetry maps of the Offshore of Monterey map area, California, were generated from acoustic bathymetry data collected by California State University, Monterey Bay (CSUMB) and by Monterey Bay Aquarium Research Institute (MBARI), as well as from bathymetric lidar data collected by the U.S. Army Corps of Engineers, Joint Airborne Lidar Bathymetry Center of Expertise (JALBTCX). Acoustic mapping was completed between 1998 and 2012 using a combination of 200-kHz/400-kHz Reson 7125, 100-kHz Reson 7111, 240-kHz Reson 8101, and 30-kHz Simrad EM-300 multibeam echosounders, as well as 234-kHz and 468-kHz SWATHplus bathymetric sidescan-sonar systems. Bathymetric lidar mapping was completed between 2009 and 2010 for the California Coastal Mapping Project (CCMP). These mapping missions combined to collect bathymetry data from the shoreline to beyond the limit of California’s State Waters. NOTE: The horizontal datum of this bathymetry data (NAD83) differs from the horizontal datum of other layers in this data release (WGS84).

This part of DS 781 presents data for the bathymetry map of the Offshore of Monterey map area, California. Bathymetry data are provided as separate grids depending on resolution. This metadata file refers to the data included in "BathymetryHS_5m_OffshoreMonterey.zip," which is accessible from https://doi.org/10.5066/F70Z71C8. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Hartwell, S.R., Cochrane, G.R., Golden, N.E., Watt, J.T., Davenport, C.W., Kvitek, R.G., Erdey, M.D., Krigsman, L.M., Sliter, R.W., and Maier, K.L. (S.Y. Johnson and S.A. Cochran, eds.), 2016, California State Waters Map Series—Offshore of Monterey, California: U.S. Geological Survey Open-File Report 2016–1110, pamphlet 44 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20161110. The 2-m and 5-m bathymetry and shaded-relief bathymetry maps of the Offshore of Monterey map area, California, were generated from acoustic bathymetry data collected by California State University, Monterey Bay (CSUMB) and by Monterey Bay Aquarium Research Institute (MBARI), as well as from bathymetric lidar data collected by the U.S. Army Corps of Engineers, Joint Airborne Lidar Bathymetry Center of Expertise (JALBTCX). Acoustic mapping was completed between 1998 and 2012 using a combination of 200-kHz/400-kHz Reson 7125, 100-kHz Reson 7111, 240-kHz Reson 8101, and 30-kHz Simrad EM-300 multibeam echosounders, as well as 234-kHz and 468-kHz SWATHplus bathymetric sidescan-sonar systems. Bathymetric lidar mapping was completed between 2009 and 2010 for the California Coastal Mapping Project (CCMP). These mapping missions combined to collect bathymetry data from the shoreline to beyond the limit of California’s State Waters. NOTE: The horizontal datum of this bathymetry data (NAD83) differs from the horizontal datum of other layers in this data release (WGS84).

This part of DS 781 presents data for the bathymetry map of the Offshore of Monterey map area, California. Bathymetry data are provided as separate grids depending on resolution. This metadata file refers to the data included in "Bathymetry_2m_OffshoreMonterey.zip," which is accessible from https://doi.org/10.5066/F70Z71C8. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Hartwell, S.R., Cochrane, G.R., Golden, N.E., Watt, J.T., Davenport, C.W., Kvitek, R.G., Erdey, M.D., Krigsman, L.M., Sliter, R.W., and Maier, K.L. (S.Y. Johnson and S.A. Cochran, eds.), 2016, California State Waters Map Series—Offshore of Monterey, California: U.S. Geological Survey Open-File Report 2016–1110, pamphlet 44 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20161110. The 2-m and 5-m bathymetry and shaded-relief bathymetry maps of the Offshore of Monterey map area, California, were generated from acoustic bathymetry data collected by California State University, Monterey Bay (CSUMB) and by Monterey Bay Aquarium Research Institute (MBARI), as well as from bathymetric lidar data collected by the U.S. Army Corps of Engineers, Joint Airborne Lidar Bathymetry Center of Expertise (JALBTCX). Acoustic mapping was completed between 1998 and 2012 using a combination of 200-kHz/400-kHz Reson 7125, 100-kHz Reson 7111, 240-kHz Reson 8101, and 30-kHz Simrad EM-300 multibeam echosounders, as well as 234-kHz and 468-kHz SWATHplus bathymetric sidescan-sonar systems. Bathymetric lidar mapping was completed between 2009 and 2010 for the California Coastal Mapping Project (CCMP). These mapping missions combined to collect bathymetry data from the shoreline to beyond the limit of California’s State Waters. NOTE: The horizontal datum of this bathymetry data (NAD83) differs from the horizontal datum of other layers in this data release (WGS84).

This part of DS 781 presents data for the bathymetry map of the Offshore of Monterey map area, California. Bathymetry data are provided as separate grids depending on resolution. This metadata file refers to the data included in "Bathymetry_5m_OffshoreMonterey.zip," which is accessible from https://doi.org/10.5066/F70Z71C8. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Hartwell, S.R., Cochrane, G.R., Golden, N.E., Watt, J.T., Davenport, C.W., Kvitek, R.G., Erdey, M.D., Krigsman, L.M., Sliter, R.W., and Maier, K.L. (S.Y. Johnson and S.A. Cochran, eds.), 2016, California State Waters Map Series—Offshore of Monterey, California: U.S. Geological Survey Open-File Report 2016–1110, pamphlet 44 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20161110. The 2-m and 5-m bathymetry and shaded-relief bathymetry maps of the Offshore of Monterey map area, California, were generated from acoustic bathymetry data collected by California State University, Monterey Bay (CSUMB) and by Monterey Bay Aquarium Research Institute (MBARI), as well as from bathymetric lidar data collected by the U.S. Army Corps of Engineers, Joint Airborne Lidar Bathymetry Center of Expertise (JALBTCX). Acoustic mapping was completed between 1998 and 2012 using a combination of 200-kHz/400-kHz Reson 7125, 100-kHz Reson 7111, 240-kHz Reson 8101, and 30-kHz Simrad EM-300 multibeam echosounders, as well as 234-kHz and 468-kHz SWATHplus bathymetric sidescan-sonar systems. Bathymetric lidar mapping was completed between 2009 and 2010 for the California Coastal Mapping Project (CCMP). These mapping missions combined to collect bathymetry data from the shoreline to beyond the limit of California’s State Waters. NOTE: The horizontal datum of this bathymetry data (NAD83) differs from the horizontal datum of other layers in this data release (WGS84).

This part of DS 781 presents bathymetric contours for several seafloor maps of the Offshore of Monterey map area, California. This metadata file refers to the data included in "Contours_OffshoreMonterey.zip," which is accessible from https://doi.org/10.5066/F70Z71C8. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Hartwell, S.R., Cochrane, G.R., Golden, N.E., Watt, J.T., Davenport, C.W., Kvitek, R.G., Erdey, M.D., Krigsman, L.M., Sliter, R.W., and Maier, K.L. (S.Y. Johnson and S.A. Cochran, eds.), 2016, California State Waters Map Series—Offshore of Monterey, California: U.S. Geological Survey Open-File Report 2016–1110, pamphlet 44 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20161110. Bathymetric contours of the Offshore of Monterey map area, California, were generated from bathymetry data collected by California State University, Monterey Bay (CSUMB) and by Monterey Bay Aquarium Research Institute (MBARI), as well as from bathymetric lidar data collected by the U.S. Army Corps of Engineers, Joint Airborne Lidar Bathymetry Center of Expertise (JALBTCX). Mapping was completed between 1998 and 2012 using a combination of 30-kHz Simrad EM-300 and 200-kHz/400-kHz Reson 7125 multibeam echosounders, as well as 234-kHz and 468-kHz SEA SWATHplus bathymetric sidescan-sonar systems. Bathymetric lidar mapping was completed between 2009 and 2010 for the California Coastal Mapping Project (CCMP). The mapping missions collected bathymetry data from about the 10-m isobath to beyond the 3-nautical-mile limit of California's State Waters. Bathymetric contours were generated separately from the modified 2-m and 5-m bathymetric surfaces then merged to one final contour dataset. 10-m intervals were generated in water depths shallower than 100 m, at 50-m intervals from 100 to 200 m, and at 200-m intervals in water depths deeper than 200 m. The original surface was smoothed using the Focal Mean tool in ArcGIS and a circular neighborhood with a radius of 20 to 30 m (depending on the area). The contours were generated from this smoothed surface using the ArcGIS Spatial Analyst Contour tool. The most continuous contour segments were preserved; smaller segments and isolated island polygons were excluded from the final output.

This part of DS 781 presents fault data for the geologic and geomorphic map of the Offshore of Monterey map area, California. The vector data file is included in "Faults_OffshoreMonterey.zip," which is accessible from https://doi.org/10.5066/F70Z71C8. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Hartwell, S.R., Cochrane, G.R., Golden, N.E., Watt, J.T., Davenport, C.W., Kvitek, R.G., Erdey, M.D., Krigsman, L.M., Sliter, R.W., and Maier, K.L. (S.Y. Johnson and S.A. Cochran, eds.), 2016, California State Waters Map Series—Offshore of Monterey, California: U.S. Geological Survey Open-File Report 2016–1110, pamphlet 44 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20161110. Faults in the Offshore of Monterey map area are identified on seismic-reflection data based on abrupt truncation or warping of reflections and (or) juxtaposition of reflection panels with different seismic parameters such as reflection presence, amplitude, frequency, geometry, continuity, and vertical sequence. Faults were primarily mapped by interpretation of seismic reflection profile data from USGS field activity S–6–11–MB collected in 2011.

This part of DS 781 presents fold data for the geologic and geomorphic map of the Offshore of Monterey map area, California. The vector data file is included in "Folds_OffshoreMonterey.zip," which is accessible from https://doi.org/10.5066/F70Z71C8. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Hartwell, S.R., Cochrane, G.R., Golden, N.E., Watt, J.T., Davenport, C.W., Kvitek, R.G., Erdey, M.D., Krigsman, L.M., Sliter, R.W., and Maier, K.L. (S.Y. Johnson and S.A. Cochran, eds.), 2016, California State Waters Map Series—Offshore of Monterey, California: U.S. Geological Survey Open-File Report 2016–1110, pamphlet 44 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20161110. Folds in the Offshore of Monterey map area are identified on seismic-reflection data based on abrupt truncation or warping of reflections and (or) juxtaposition of reflection panels with different seismic parameters such as reflection presence, amplitude, frequency, geometry, continuity, and vertical sequence. Faults were primarily mapped by interpretation of seismic reflection profile data from USGS field activity S–6–11–MB collected in 2011.

This part of DS 781 presents data for the geologic and geomorphic map of the Offshore of Monterey map area, California. The vector data file is included in "Geology_OffshoreMonterey.zip," which is accessible from https://doi.org/10.5066/F70Z71C8. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Hartwell, S.R., Cochrane, G.R., Golden, N.E., Watt, J.T., Davenport, C.W., Kvitek, R.G., Erdey, M.D., Krigsman, L.M., Sliter, R.W., and Maier, K.L. (S.Y. Johnson and S.A. Cochran, eds.), 2016, California State Waters Map Series—Offshore of Monterey, California: U.S. Geological Survey Open-File Report 2016–1110, pamphlet 44 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20161110. Marine geology and geomorphology were mapped in the Offshore of Monterey map area, California, from approximate Mean High Water (MHW) to the 3-nautical-mile limit of California''s State Waters. Offshore geologic units were delineated on the basis of integrated analyses of adjacent onshore geology with multibeam bathymetry and backscatter imagery, seafloor-sediment and rock samples, digital camera and video imagery, and high-resolution seismic-reflection profiles.

This part of DS 781 presents data for the habitat map of the seafloor of the Offshore of Monterey map area, California. The vector data file is included in "Habitat_OffshoreMonterey.zip," which is accessible from https://doi.org/10.5066/F70Z71C8. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Hartwell, S.R., Cochrane, G.R., Golden, N.E., Watt, J.T., Davenport, C.W., Kvitek, R.G., Erdey, M.D., Krigsman, L.M., Sliter, R.W., and Maier, K.L. (S.Y. Johnson and S.A. Cochran, eds.), 2016, California State Waters Map Series—Offshore of Monterey, California: U.S. Geological Survey Open-File Report 2016–1110, pamphlet 44 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20161110. This map shows physical marine benthic habitats in the Offshore of Monterey map area. Marine benthic habitats represent a particular type of water quality, substrate, geomorphology, seafloor process, or any other attribute that may provide a habitat for a specific species or an assemblage of organisms. Marine benthic habitats are classified using the Coastal and Marine Ecological Classification Standard (CMECS), developed by representatives from a consortium of federal agencies. CMECS is the U.S. government standard for marine habitat characterization. The standard provides an ecologically-relevant structure for biologic, geologic, chemical, and physical habitat attributes. This map illustrates the geoform and substrate components of the standard. This map was derived from seafloor geology map (sheet 10) units by translation of the unit description into the best-fit values of CMECS classes. The CMECS classes are documented at https://www.fgdc.gov/standards/projects/FGDC-standards-projects/cmecs-folder/CMECS_Version_06-2012_FINAL.pdf. Please refer to Greene and others (2007) for more information regarding the Benthic Marine Potential Habitat Classification Scheme and the codes used to represent various seafloor features. Reference Cited: Greene, H.G., Bizzarro, J.J., O'Connell, V.M., and Brylinsky, C.K., 2007, Construction of digital potential marine benthic habitat maps using a coded classification scheme and its application, in Todd, B.J., and Greene, H.G., eds., Mapping the seafloor for habitat characterization: Geological Association of Canada Special Paper 47, p. 141-155.

This part of DS 781 presents data for the paleoshorelines for the geologic and geomorphic map of the Offshore of Monterey map area, California. The vector data file is included in "Paleoshorelines_OffshoreMonterey.zip," which is accessible from https://doi.org/10.5066/F70Z71C8. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Hartwell, S.R., Cochrane, G.R., Golden, N.E., Watt, J.T., Davenport, C.W., Kvitek, R.G., Erdey, M.D., Krigsman, L.M., Sliter, R.W., and Maier, K.L. (S.Y. Johnson and S.A. Cochran, eds.), 2016, California State Waters Map Series—Offshore of Monterey, California: U.S. Geological Survey Open-File Report 2016–1110, pamphlet 44 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20161110.

This part of DS 781 presents data for the seafloor-character map of the Offshore of Monterey map area, California. Seafloor-character data are provided as two separate grids depending on resolution of the mapping system and processing method. The raster data file is included in "SeafloorCharacter_2m_OffshoreMonterey.zip," which is accessible from https://doi.org/10.5066/F70Z71C8. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Hartwell, S.R., Cochrane, G.R., Golden, N.E., Watt, J.T., Davenport, C.W., Kvitek, R.G., Erdey, M.D., Krigsman, L.M., Sliter, R.W., and Maier, K.L. (S.Y. Johnson and S.A. Cochran, eds.), 2016, California State Waters Map Series—Offshore of Monterey, California: U.S. Geological Survey Open-File Report 2016–1110, pamphlet 44 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20161110. This raster-format seafloor-character map shows four substrate classes in the Offshore of Monterey map area, California. The substrate classes mapped in this area have been colored to indicate which of the following California Marine Life Protection Act depth zones and slope classes they belong: Depth Zone 2 (intertidal to 30 m), Depth Zone 3 (30 to 100 m), Depth Zone 4 (100 to 200 m), Depth Zone 5 (deeper than 200 m), Slope Class 1 (0 degrees - 5 degrees; flat), and Slope Class 2 (5 degrees - 30 degrees; sloping). Depth Zone 1 (intertidal), and Slopes Classes 3 and 4 (greater than 30 degrees) are not present in this map area. The map is created using a supervised classification method described by Cochrane (2008), using multibeam echosounder (MBES) bathymetry and backscatter data collected and processed between 1998 and 2014. Bathymetry data were collected at two different resolutions: at 2-m resolution, down to approximately 90-m water depth (1998-2012 CSUMB and MBARI data); and at 5-m resolution, in the deeper areas (1998-2012 MBARI data). The final resolution of the seafloor-character map is determined by the resolution of both the backscatter and bathymetry datasets; therefore, separate seafloor-character maps were generated to retain the maximum resolution of the source data. Reference Cited: Cochrane, G.R., 2008, Video-supervised classification of sonar data for mapping seafloor habitat, in Reynolds, J.R., and Greene, H.G., eds., Marine habitat mapping technology for Alaska: Fairbanks, University of Alaska, Alaska Sea Grant College Program, p. 185-194, accessed April 5, 2011, at http://doc.nprb.org/web/research/research%20pubs/615_habitat_mapping_workshop/Individual%20Chapters%20High-Res/Ch13%20Cochrane.pdf.

This part of DS 781 presents data for the seafloor-character map of the Offshore of Monterey map area, California. Seafloor-character data are provided as two separate grids depending on resolution of the mapping system and processing method. The raster data file is included in "SeafloorCharacter_5m_OffshoreMonterey.zip," which is accessible from https://doi.org/10.5066/F70Z71C8. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Hartwell, S.R., Cochrane, G.R., Golden, N.E., Watt, J.T., Davenport, C.W., Kvitek, R.G., Erdey, M.D., Krigsman, L.M., Sliter, R.W., and Maier, K.L. (S.Y. Johnson and S.A. Cochran, eds.), 2016, California State Waters Map Series—Offshore of Monterey, California: U.S. Geological Survey Open-File Report 2016–1110, pamphlet 44 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20161110. This raster-format seafloor-character map shows four substrate classes in the Offshore of Monterey map area, California. The substrate classes mapped in this area have been colored to indicate which of the following California Marine Life Protection Act depth zones and slope classes they belong: Depth Zone 2 (intertidal to 30 m), Depth Zone 3 (30 to 100 m), Depth Zone 4 (100 to 200 m), Depth Zone 5 (deeper than 200 m), Slope Class 1 (0 degrees - 5 degrees; flat), and Slope Class 2 (5 degrees - 30 degrees; sloping). Depth Zone 1 (intertidal), and Slopes Classes 3 and 4 (greater than 30 degrees) are not present in this map area. The map is created using a supervised classification method described by Cochrane (2008), using multibeam echosounder (MBES) bathymetry and backscatter data collected and processed between 1998 and 2014. Bathymetry data were collected at two different resolutions: at 2-m resolution, down to approximately 90-m water depth (1998-2012 CSUMB and MBARI data); and at 5-m resolution, in the deeper areas (1998-2012 MBARI data). The final resolution of the seafloor-character map is determined by the resolution of both the backscatter and bathymetry datasets; therefore, separate seafloor-character maps were generated to retain the maximum resolution of the source data. Reference Cited: Cochrane, G.R., 2008, Video-supervised classification of sonar data for mapping seafloor habitat, in Reynolds, J.R., and Greene, H.G., eds., Marine habitat mapping technology for Alaska: Fairbanks, University of Alaska, Alaska Sea Grant College Program, p. 185-194, accessed April 5, 2011, at http://doc.nprb.org/web/research/research%20pubs/615_habitat_mapping_workshop/Individual%20Chapters%20High-Res/Ch13%20Cochrane.pdf.

Vegetation type and density data were collected by the U.S. Geological Survey (USGS) Pacific Coastal and Marine Science Center at three locations in the Sacramento-San Joaquin Delta. Data were collected in Lindsey Slough in April 2017, and Middle River and the Mokelumne River in March 2018. Vegetation samples were collected by divers, and used to determine dry biomass density. These data were collected as part of a cooperative project, with the USGS California Water Science Center and the California Department of Fish and Wildlife, on the effects of invasive aquatic vegetation on sediment transport in the Sacramento-San Joaquin Delta.

Multibeam acoustic-backscatter data were collected offshore of Morro Bay, California, from 2016 to 2019. The data were collected during five separate multi-agency surveys for the U.S. Geological Survey (USGS)/Bureau of Ocean Energy Management (BOEM) California Deepwater Investigations and Groundtruthing I (Cal DIG I) project, under a collaboration with the National Oceanic and Atmospheric Administration (NOAA), using Simrad 700 series hull-mounted multibeam echosounders. Data in 2017 and 2018 were acquired by the NOAA Hydrographic Vessel Rainier (surveys H1309, H13151, and H13152). The 2018 data acquired by the Ranier were collected during USGS field activity 2018-641-FA. Additional data were collected in 2019 by the NOAA Hydrographic Survey Vessel Fairweather (survey W00479). Data from the Scripps Institution of Oceanography R/V Sally Ride collected in 2016 (survey SR1604) were used to fill in a small gap in the NOAA data. The acoustic-backscatter data from the five surveys were combined into a single raster and are provided as a 10-meter resolution GeoTIFF.

Multibeam acoustic-bathymetry data were collected offshore of Morro Bay, California, from 2016 to 2019. The data were collected during five separate multi-agency surveys for the U.S. Geological Survey (USGS)/Bureau of Ocean Energy Management (BOEM) California Deepwater Investigations and Groundtruthing I (Cal DIG I) project, under a collaboration with the National Oceanic and Atmospheric Administration (NOAA), using Simrad 700 series hull-mounted multibeam echosounders. Data in 2017 and 2018 were acquired by the NOAA Hydrographic Vessel Rainier (surveys H1309, H13151, and H13152). The 2018 data acquired by the Ranier were collected during USGS field activity 2018-641-FA. Additional data were collected in 2019 by the NOAA Hydrographic Survey Vessel Fairweather (survey W00479). Data from the Scripps Institution of Oceanography R/V Sally Ride collected in 2016 (survey SR1604) were used to fill in a small gap in the NOAA data. The acoustic-backscatter data from the five surveys were combined into a single raster and are provided as a 10-meter resolution GeoTIFF.

Seafloor induration (surface hardness) was derived from multibeam echosounder (MBES) and annotated underwater video data collected offshore of Morro Bay, California, from 2016 to 2020. MBES and underwater video data were collected in support of the U.S. Geological Survey (USGS)/Bureau of Ocean Energy Management (BOEM) California Deepwater Investigations and Groundtruthing I (Cal DIG I) project, under a collaboration with the National Oceanic and Atmospheric Administration (NOAA). Substrate observations from the underwater video were translated into Coastal and Marine Ecological Classification Standard (CMECS; Federal Geographic Data Committee, 2012) induration classes to use as training for a supervised classification of the MBES data. The induration raster is provided as a 10-meter resolution GeoTIFF.

This part of DS 781 presents data for the acoustic-backscatter map of the Offshore of Bodega Head map area, California. Backscatter data are provided as separate grids depending on mapping system or processing method. The raster data file is included in "BackscatterA_8101_OffshoreBodegaHead.zip", which is accessible from https://pubs.usgs.gov/ds/781/OffshoreBodegaHead/data_catalog_OffshoreBodegaHead.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Golden, N.E., Hartwell, S.R., Erdey, M.D., Greene, H.G., Cochrane, G.R., Kvitek, R.G., Manson, M.W., Endris, C.A., Dieter, B.E., Watt, J.T., Krigsman, L.M., Sliter, R.W., Lowe, E.N., and Chin, J.L. (S.Y. Johnson and S.A. Cochran, eds.), 2015, California State Waters Map Series—Offshore of Bodega Head, California: U.S. Geological Survey Open-File Report 2015–1140, pamphlet 39 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20151140. The acoustic-backscatter map of the Offshore of Bodega Head map area, California, was generated from backscatter data collected by California State University, Monterey Bay (CSUMB), and by Fugro Pelagos. Mapping was completed between 2007 and 2010, using a combination of 200-kHz and 400-kHz Reson 7125, and 244-kHz Reson 8101 multibeam echosounders, as well as 468-kHz SEA SWATHPlus interferometric system. These mapping missions combined to collect backscatter data (sheet 3) from about the 10-m isobath to beyond the 3-nautical-mile limit of California State Waters. Within the acoustic-backscatter imagery, brighter tones indicate higher backscatter intensity, and darker tones indicate lower backscatter intensity. The intensity represents a complex interaction between the acoustic pulse and the seafloor, as well as characteristics within the shallow subsurface, providing a general indication of seafloor texture and composition. Backscatter intensity depends on the acoustic source level; the frequency used to image the seafloor; the grazing angle; the composition and character of the seafloor, including grain size, water content, bulk density, and seafloor roughness; and some biological cover. Harder and rougher bottom types such as rocky outcrops or coarse sediment typically return stronger intensities (high backscatter, lighter tones), whereas softer bottom types such as fine sediment return weaker intensities (low backscatter, darker tones). These data are not intended for navigational purposes.

This part of DS 781 presents data for the acoustic-backscatter map of the Offshore of Bodega Head map area, California. Backscatter data are provided as separate grids depending on mapping system or processing method. The raster data file is included in "BackscatterB_7125_OffshoreBodegaHead.zip", which is accessible from https://pubs.usgs.gov/ds/781/OffshoreBodegaHead/data_catalog_OffshoreBodegaHead.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Golden, N.E., Hartwell, S.R., Erdey, M.D., Greene, H.G., Cochrane, G.R., Kvitek, R.G., Manson, M.W., Endris, C.A., Dieter, B.E., Watt, J.T., Krigsman, L.M., Sliter, R.W., Lowe, E.N., and Chin, J.L. (S.Y. Johnson and S.A. Cochran, eds.), 2015, California State Waters Map Series—Offshore of Bodega Head, California: U.S. Geological Survey Open-File Report 2015–1140, pamphlet 39 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20151140. The acoustic-backscatter map of the Offshore of Bodega Head map area, California, was generated from backscatter data collected by California State University, Monterey Bay (CSUMB), and by Fugro Pelagos. Mapping was completed between 2007 and 2010, using a combination of 200-kHz and 400-kHz Reson 7125, and 244-kHz Reson 8101 multibeam echosounders, as well as 468-kHz SEA SWATHPlus interferometric system. These mapping missions combined to collect backscatter data (sheet 3) from about the 10-m isobath to beyond the 3-nautical-mile limit of California State Waters. Within the acoustic-backscatter imagery, brighter tones indicate higher backscatter intensity, and darker tones indicate lower backscatter intensity. The intensity represents a complex interaction between the acoustic pulse and the seafloor, as well as characteristics within the shallow subsurface, providing a general indication of seafloor texture and composition. Backscatter intensity depends on the acoustic source level; the frequency used to image the seafloor; the grazing angle; the composition and character of the seafloor, including grain size, water content, bulk density, and seafloor roughness; and some biological cover. Harder and rougher bottom types such as rocky outcrops or coarse sediment typically return stronger intensities (high backscatter, lighter tones), whereas softer bottom types such as fine sediment return weaker intensities (low backscatter, darker tones). These data are not intended for navigational purposes.

This part of DS 781 presents data for the acoustic-backscatter map of the Offshore of Bodega Head map area, California. Backscatter data are provided as separate grids depending on mapping system or processing method. The raster data file is included in "BackscatterC_Swath_OffshoreBodegaHead.zip", which is accessible from https://pubs.usgs.gov/ds/781/OffshoreBodegaHead/data_catalog_OffshoreBodegaHead.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Golden, N.E., Hartwell, S.R., Erdey, M.D., Greene, H.G., Cochrane, G.R., Kvitek, R.G., Manson, M.W., Endris, C.A., Dieter, B.E., Watt, J.T., Krigsman, L.M., Sliter, R.W., Lowe, E.N., and Chin, J.L. (S.Y. Johnson and S.A. Cochran, eds.), 2015, California State Waters Map Series—Offshore of Bodega Head, California: U.S. Geological Survey Open-File Report 2015–1140, pamphlet 39 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20151140. The acoustic-backscatter map of the Offshore of Bodega Head map area, California, was generated from backscatter data collected by California State University, Monterey Bay (CSUMB), and by Fugro Pelagos. Mapping was completed between 2007 and 2010, using a combination of 200-kHz and 400-kHz Reson 7125, and 244-kHz Reson 8101 multibeam echosounders, as well as 468-kHz SEA SWATHPlus interferometric system. These mapping missions combined to collect backscatter data (sheet 3) from about the 10-m isobath to beyond the 3-nautical-mile limit of California State Waters. Within the acoustic-backscatter imagery, brighter tones indicate higher backscatter intensity, and darker tones indicate lower backscatter intensity. The intensity represents a complex interaction between the acoustic pulse and the seafloor, as well as characteristics within the shallow subsurface, providing a general indication of seafloor texture and composition. Backscatter intensity depends on the acoustic source level; the frequency used to image the seafloor; the grazing angle; the composition and character of the seafloor, including grain size, water content, bulk density, and seafloor roughness; and some biological cover. Harder and rougher bottom types such as rocky outcrops or coarse sediment typically return stronger intensities (high backscatter, lighter tones), whereas softer bottom types such as fine sediment return weaker intensities (low backscatter, darker tones). These data are not intended for navigational purposes.

This part of DS 781 presents data for the bathymetry and shaded-relief maps of the Offshore of Bodega Head map area, California. Raster data file is included in "BathymetryHS_OffshoreBodegaHead.zip," which is accessible from http://pubs.usgs.gov/ds/781/OffshoreBodegaHead/data_catalog_OffshoreBodegaHead.html. The bathymetry and shaded-relief maps of the Offshore of Bodega Head map area, California, were generated from bathymetry data collected by California State University, Monterey Bay (CSUMB), and by Fugro Pelagos. Mapping was completed between 2007 and 2010, using a combination of 200-kHz and 400-kHz Reson 7125, and 244-kHz Reson 8101 multibeam echosounders, as well as 468-kHz SEA SWATHPlus interferometric system. These mapping missions combined to collect bathymetry (sheets 1, 2) from about the 10-m isobath to beyond the 3-nautical-mile limit of California State Waters.

This part of DS 781 presents data for the bathymetry and shaded-relief maps of the Offshore of Bodega Head map area, California. Raster data file is included in "Bathymetry_OffshoreBodegaHead.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreBodegaHead/data_catalog_OffshoreBodegaHead.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Golden, N.E., Hartwell, S.R., Erdey, M.D., Greene, H.G., Cochrane, G.R., Kvitek, R.G., Manson, M.W., Endris, C.A., Dieter, B.E., Watt, J.T., Krigsman, L.M., Sliter, R.W., Lowe, E.N., and Chin, J.L. (S.Y. Johnson and S.A. Cochran, eds.), 2015, California State Waters Map Series—Offshore of Bodega Head, California: U.S. Geological Survey Open-File Report 2015–1140, pamphlet 39 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20151140. The bathymetry and shaded-relief maps of the Offshore of Bodega Head map area, California, were generated from bathymetry data collected by California State University, Monterey Bay (CSUMB), and by Fugro Pelagos. Mapping was completed between 2007 and 2010, using a combination of 200-kHz and 400-kHz Reson 7125, and 244-kHz Reson 8101 multibeam echosounders, as well as 468-kHz SEA SWATHPlus interferometric system. These mapping missions combined to collect bathymetry (sheets 1, 2) from about the 10-m isobath to beyond the 3-nautical-mile limit of California State Waters. The horizontal datum of the bathymetry data (NAD83) differs from the horizontal datum of other layers in this data series (WGS84). Some bathymetry grids within this map were projected horizontally from WGS84 to NAD83 using ESRI tools to be more consistent with the vertical reference of the North American Vertical Datum of 1988 (NAVD88). These data are not intended for navigational purposes.

This part of DS 781 presents data for the bathymetric contours for several seafloor maps of the Offshore of Bodega Head map area, California. The vector data file is included in "Contours_OffshoreBodegaHead.zip," which is accessible https://pubs.usgs.gov/ds/781/OffshoreBodegaHead/data_catalog_OffshoreBodegaHead.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Golden, N.E., Hartwell, S.R., Erdey, M.D., Greene, H.G., Cochrane, G.R., Kvitek, R.G., Manson, M.W., Endris, C.A., Dieter, B.E., Watt, J.T., Krigsman, L.M., Sliter, R.W., Lowe, E.N., and Chin, J.L. (S.Y. Johnson and S.A. Cochran, eds.), 2015, California State Waters Map Series—Offshore of Bodega Head, California: U.S. Geological Survey Open-File Report 2015–1140, pamphlet 39 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20151140. 10-m interval contours of the Offshore of Bodega head map area, California, were generated from bathymetry data collected by California State University, Monterey Bay (CSUMB) and by Fugro Pelagos. Mapping was completed between 2007 and 2010, using a combination of 200-kHz and 400-kHz Reson 7125, and 244-kHz Reson 8101 multibeam echosounders, as well as 468-kHz SEA SWATHPlus interferometric system. These mapping missions combined to collect bathymetry from about the 10-m isobath to beyond the 3-nautical-mile limit of California State Waters. Bathymetric contours at 10-m intervals were generated from a bathymetric surface model. The most continuous contour segments were preserved while smaller segments and isolated island polygons were excluded from the final output. Contours were smoothed via a polynomial approximation with exponential kernel (PAEK) algorithm using a tolerance value of 60 m. The contours were then clipped to the boundary of the map area. These data are not intended for navigational purposes.

This part of DS 781 presents the seafloor-character map Offshore of Bodega Head, California (raster data file is included in "SeafloorCharacter_BodegaHead.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreBodegaHead/data_catalog_OffshoreBodegaHead.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Golden, N.E., Hartwell, S.R., Erdey, M.D., Greene, H.G., Cochrane, G.R., Kvitek, R.G., Manson, M.W., Endris, C.A., Dieter, B.E., Watt, J.T., Krigsman, L.M., Sliter, R.W., Lowe, E.N., and Chin, J.L. (S.Y. Johnson and S.A. Cochran, eds.), 2015, California State Waters Map Series—Offshore of Bodega Head, California: U.S. Geological Survey Open-File Report 2015–1140, pamphlet 39 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20151140. This raster-format seafloor-character map shows four substrate classes offshore of Bodega Head, California. The substrate classes mapped in this area have been further divided into the following California Marine Life Protection Act depth zones and slope classes: Depth Zone 2 (intertidal to 30 m), Depth Zone 3 (30 to 100 m), Slope Class 1 (0 degrees - 5 degrees), and Slope Class 2 (5 degrees - 30 degrees). Depth Zone 1 (intertidal), Depth Zone 4 (100 to 200 m), Depth Zone 5 (greater than 200 m), and Slopes Classes 3-4 (greater than 30 degrees) are not present in the region covered by this block. The map is created using a supervised classification method described by Cochrane (2008). References Cited: California Department of Fish and Game, 2008, California Marine Life Protection Act master plan for marine protected areas; Revised draft: California Department of Fish and Game, accessed April 5 2011, at http://www.dfg.ca.gov/mlpa/masterplan.asp. Cochrane, G.R., 2008, Video-supervised classification of sonar data for mapping seafloor habitat, in Reynolds, J.R., and Greene, H.G., eds., Marine habitat mapping technology for Alaska: Fairbanks, University of Alaska, Alaska Sea Grant College Program, p. 185-194, accessed April 5, 2011, at http://doc.nprb.org/web/research/research%20pubs/615_habitat_mapping_workshop/Individual%20Chapters%20High-Res/Ch13%20Cochrane.pdf. Sappington, J.M., Longshore, K.M., and Thompson, D.B., 2007, Quantifying landscape ruggedness for animal habitat analysis--A case study using bighorn sheep in the Mojave Desert: Journal of Wildlife Management, v. 71, p. 1419-1426.

These metadata describe bathymetry collected during a 2015 multibeam echosounder survey near Cross Sound, southeast Alaska. Data were collected by the U.S. Geological Survey (USGS) and the Alaska Department of Fish and Game (ADFG) aboard the ADFG R/V Solstice during USGS field activity 2015-629-FA. The bathymetry data are published here as a 32-bit GeoTIFF image.

These metadata describe navigation tracklines from a 2015 multibeam echosounder survey near Cross Sound, southeast Alaska. Data were collected by the U.S. Geological Survey (USGS) and the Alaska Department of Fish and Game (ADFG) aboard the ADFG R/V Solstice during USGS field activity 2015-629-FA. The trackline data are provided as a GIS shapefile.

These metadata describe acoustic-backscatter data collected during 2017 and 2018 multibeam echosounder surveys of Noyes Submarine Canyon and vicinity, southeast Alaska. Data were collected by the National Oceanic and Atmospheric Administration (NOAA) aboard the NOAA survey vessel Fairweather and the data were post-processed by the U.S. Geological Survey (USGS), Pacific Coastal and Marine Science Center (PCMSC) for PCMSC research projects. The acoustic-backscatter data are provided as a GeoTIFF image.

These metadata describe bathymetry data collected during 2017 and 2018 multibeam echosounder surveys of Noyes Submarine Canyon and vicinity, southeast Alaska. Data were collected by the National Oceanic and Atmospheric Administration (NOAA) aboard the NOAA survey vessel Fairweather and the data were post-processed by the U.S. Geological Survey (USGS), Pacific Coastal and Marine Science Center (PCMSC) for PCMSC research projects.

These metadata describe ship navigation tracklines from a 2017 multibeam echosounder survey near Noyo Submarine Canyon and Dixon Entrance, southeast Alaska. Data were collected by the National Oceanic and Atmospheric Administration (NOAA) aboard the NOAA survey vessel Fairweather and the data were post-processed by the U.S. Geological Survey (USGS), Pacific Coastal and Marine Science Center (PCMSC) for PCMSC research projects. The tracklines are provided as a GIS shapefile.

These metadata describe ship navigation tracklines from a 2018 multibeam echosounder survey near Noyo Submarine Canyon and vicinity, southeast Alaska. Data were collected by the National Oceanic and Atmospheric Administration (NOAA) aboard the NOAA survey vessel Fairweather and the data were post-processed by the U.S. Geological Survey (USGS), Pacific Coastal and Marine Science Center (PCMSC) for PCMSC research projects. The tracklines are provided as a GIS shapefile.

Cross-shore transects (CSTs) developed for Coastal Storm Model (CoSMoS) work in Northern California 3.2 are presented. 3,528 CSTs are numbered consecutively from 8067 at Golden Gate Bridge to 11,594 at the California/Oregon state border. Each of the profiles extend from the approximate -15 m isobath to at least 10 m above NAVD88 (truncated in cases where a lagoon or other waterway exists on the landward end of the profile), and are spaced approximately 100-250 m apart.

Nearshore proxies for total water level (TWL) developed for Coastal Storm Model (CoSMoS) work in Northern California 3.2 are presented. Deterministic dynamical modeling of future climate conditions and associated hazards, such as flooding, can be computationally-expensive if century-long time-series of waves, sea level variations, and overland flow patterns are simulated. To focus such modeling on storm events of interest, local impacts over long time periods and large geographical areas are estimated. Nearshore proxies for total water level (TWL) are generated via a computationally simple approach, assuming a linear superposition of the important processes contributing to overall total water level. A time series of TWL proxies is used as the basis for 1) identifying coastal segments that respond similarly to region-wide coastal storms, 2) selecting storm events for detailed hydrodynamic modeling within CoSMoS, and 3) to drive long-term shoreline change and bluff retreat models.

This part of USGS Data Series 935 (Cochrane, 2014) presents bathymetry and topography data for the Offshore of Burien, California, map area, a part of the Southern Salish Sea Habitat Map Series. The data for this map area are a combination of topography extracted from a pre-existing Digital Elevation Model (DEM) merged with bathymetry data that were collected by the National Oceanic and Atmospheric Administration (NOAA) using multibeam sonar systems. The merged data are available for download in a single zip file (BathyTopo_OffshoreBurien.zip).

This part of USGS Data Series 935 (Cochrane, 2014) presents substrate, geomorphic, and biotope data in the Offshore of Burien, Washington, map area, a part of the Southern Salish Sea Habitat Map Series. Given the variable bathymetric resolution, the complex geologic history of the region, and the lack of acoustic backscatter data, automated and semi-automated classification schemes of classifying seafloor substrate and geoform were deemed to have very low accuracy. Instead, classification of these properties was performed manually following the Coastal and Marine Ecological Classification Standard (CMECS; Madden and others, 2009) using observations from underwater video footage. The best overall predictors of biotic assemblage were used to generate the CMECS biotopes. However, the nature of the biological data gathered makes it difficult to define clear biotopes. It was difficult to see or identify many organisms in the underwater video, and with an average of only 3-4 taxa identified per sampling unit, it is hard to characterize biotic assemblages. Some biological clusters of taxa were identified statistically for multiple map areas, and within each area, some of these groupings were found at consistent depths and/or with predictable substrates. The maps are not fine-grained enough to capture the physical variation seen within one-minute video units. Depth zones in the biotope map are based on Dethier (1992).

This part of USGS Data Series 935 (Cochrane, 2014) presents bathymetry and topography data for the Offshore of Seattle, California, map area, a part of the Southern Salish Sea Habitat Map Series. The data for this map area are a combination of topography extracted from a pre-existing Digital Elevation Model (DEM) merged with bathymetry data that were collected by the National Oceanic and Atmospheric Administration (NOAA) using multibeam sonar systems. The merged data are available for download in a single zip file (BathyTopo_OffshoreSeattle.zip).

This part of USGS Data Series 935 (Cochrane, 2014) presents substrate, geomorphic, and biotope data in the Offshore of Seattle, California, map area, a part of the Southern Salish Sea Habitat Map Series. Given the variable bathymetric resolution, the complex geologic history of the region, and the lack of acoustic backscatter data, automated and semi-automated classification schemes of classifying seafloor substrate and geoform were deemed to have very low accuracy. Instead, classification of these properties was performed manually following the Coastal and Marine Ecological Classification Standard (CMECS; Madden and others, 2009) using observations from underwater video footage. The best overall predictors of biotic assemblage were used to generate the CMECS biotopes. However, the nature of the biological data gathered makes it difficult to define clear biotopes. It was difficult to see or identify many organisms in the underwater video, and with an average of only 3-4 taxa identified per sampling unit, it is hard to characterize biotic assemblages. Some biological clusters of taxa were identified statistically for multiple map areas, and within each area, some of these groupings were found at consistent depths and/or with predictable substrates. The maps are not fine-grained enough to capture the physical variation seen within one-minute video units. Depth zones in the biotope map are based on Dethier (1992).

This part of USGS Data Series 935 (Cochrane, 2014) presents observations from underwater video collected in the Offshore of Seattle, California, map area, a part of the Southern Salish Sea Habitat Map Series. To validate the interpretations of multibeam sonar data and turn it into geologically and biologically useful information, the U.S. Geological Survey (USGS) towed a camera sled over specific locations throughout the Seattle map area to collect video and photographic data that would “ground truth” the seafloor. The ground-truth survey conducted in the Offshore of Seattle map area occurred in 2011 on the R/V Karluk (USGS field activity K0111PS) and on the Washington State Department of Fish and Game R/V Molluscan (USGS field activity M0111PS). The underwater camera sled was towed 1 to 2 m above the seafloor at speeds of between 1 and 2 nautical miles/hour. The surveys for this map area include approximately 6 hours (9.1 trackline km) of video.

Derived contours at 10-m intervals are from data collected by the USGS with a multibeam (Simrad EM1000) sidescan sonar system in the southern Monterey Bay between Moss Landing and Monterey, California in 1995 (USGS Field Activity P1-95-MB). This is one of a collection of digital files of a geographic information system of spatially referenced data related to the USGS Coastal and Marine Geology Program Monterey Bay National Marine Sanctuary Project (see this and other older Monterey Bay USGS works archived at https://archive.usgs.gov/archive/sites/walrus.wr.usgs.gov/monterey/index.html.

This dataset contains projections of coastal cliff retreat and associated uncertainty across Northern California for future scenarios of sea-level rise (SLR) to include 25, 50, 75, 100, 125, 150, 175, 200, 250, 300, and 500 centimeters (cm) of SLR by the year 2100 and cover coastline from the Golden Gate Bridge to the California-Oregon state border. Present-day cliff-edge positions used as the baseline for projections are also included. Projections were made using numerical models and field observations such as historical cliff retreat rate, nearshore slope, coastal cliff height, and mean annual wave power, as part of Coastal Storm Modeling System (CoSMoS). See cited references and methods for more detail.

This portion of the USGS data release presents acoustic-backscatter data collected during surveys performed in Floras Lake, Oregon in June 2018 (USGS Field Activity Number 2018-636-FA). Lake bed backscatter data were collected using a personal watercraft (PWC) equipped with a sidescan sonar system and global navigation satellite system (GNSS) receivers. The sonar system consisted of a Tritech Starfish 990F with a 1-MHz transducer and a 0.3-degree horizontal beam width. Output from the GNSS receivers and sonar system were combined in real time on the PWC by a computer running HYPACK hydrographic survey software. Navigation information was displayed on a video monitor, allowing PWC operators to navigate along survey lines at speeds of 2 to 3 m/s. Survey-grade positions of the PWCs were achieved with a single-base station and differential post-processing. Positioning data from the GNSS receivers were post-processed using Waypoint Grafnav to apply differential corrections from a GNSS base station with known horizontal and vertical coordinates relative to the North American Datum of 1983.

This portion of the USGS data release presents bathymetry data collected during surveys performed in Floras Lake, Oregon in June 2018 (USGS Field Activity Number 2018-636-FA). Floras Lake is a coastal lake in southern Oregon that is separated from the Pacific Ocean by sand dunes. It is not influenced by tides, although water levels fluctuate seasonally. Lake bed bathymetry data were collected using two personal watercraft (PWCs) equipped with single-beam sonar systems and global navigation satellite system (GNSS) receivers. The sonar systems consisted of an Odom Echotrac CV-100 single-beam echosounder and 200 kHz transducer with a 9-degree beam angle. Depths from the lakebed to the echosounder were calculated using the digitized acoustic backscatter and sound velocity profiles, measured using a YSI CastAway CTD. Positioning of the survey vessels was determined at 10 Hz using Trimble R7 GNSS receivers. Output from the GNSS receivers and sonar systems were combined in real time on the PWC by a computer running HYPACK hydrographic survey software. Navigation information was displayed on a video monitor, allowing PWC operators to navigate along survey lines at speeds of 2 to 3 m/s. Survey-grade positions of the PWCs were achieved with a single-base station and differential post-processing. Positioning data from the GNSS receivers were post-processed using Waypoint Grafnav to apply differential corrections from a GNSS base station with known horizontal and vertical coordinates relative to the North American Datum of 1983. Orthometric elevations relative to the NAVD88 vertical datum were computed using National Geodetic Survey Geoid12a offsets. Bathymetric data were merged with post-processed positioning data, raw data were examined and soundings adjusted in areas with aquatic vegetation, and spurious soundings were removed using a custom Graphical User Interface (GUI) programmed with the computer program MATLAB. The average estimated vertical uncertainty of the bathymetric measurements is 5 cm based on manufacturer-reported accuracies of the survey equipment. However, the effect of aquatic vegetation on the vertical accuracy of the bathymetric measurements is unknown. The final point data from the PWCs are provided in a comma-separated text file and are projected in cartesian coordinates using the Universal Transverse Mercator (UTM), Zone 10 North, meters coordinate system.

This part of DS 781 presents data for the acoustic-backscatter map of the Offshore of Bolinas map area, California. Backscatter data are provided as separate grids depending on mapping system or processing method. The raster data file is included in "BackscatterA_8101_2004_OffshoreBolinas.zip", which is accessible from https://pubs.usgs.gov/ds/781/OffshoreBolinas/data_catalog_OffshoreBolinas.html. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Johnson, S.Y., Greene, H.G., Erdey, M.D., Golden, N.E., Hartwell, S.R., Manson, M.W., Sliter, R.W., Endris, C.A., Watt, J.T., Ross, S.L., Kvitek, R.G., Phillips, E.L., Bruns, T.R., and Chin, J.L. (G.R. Cochrane and S.A. Cochran, eds.), 2015, California State Waters Map Series — Offshore of Bolinas, California: U.S. Geological Survey Open-File Report 2015–1135, pamphlet 36 p., 10 sheets, https://doi.org/10.3133/ofr20151135. The acoustic-backscatter map of the Offshore of Bolinas map area, California, was generated from backscatter collected by California State University, Monterey Bay (CSUMB), by Fugro Pelagos, and by Moss Landing Marine Laboratory (MLML). Mapping was completed between 2004 and 2010, using a combination of 200-kHz and 400-kHz Reson 7125, and 244-kHz Reson 8101 multibeam echosounders, as well as 468-kHz SEA SWATHPlus and 250-kHz GeoSwath interferometric systems. Moss Landing Marine Laboratory mapped the nearshore region north of Bolinas in 2004 prior to the California Seafloor Mapping Program (CSMP). The nearshore region from south of Bolinas Lagoon to Stinson Beach was mapped by Fugro Pelagos in 2009 for a project outside of the CSMP and only bathymetry data were collected. Therefore, note that the shaded relief map coverage (see Bathymetry Hillshade--Offshore of Bolinas, California, DS 781) does not match the acoustic-backscatter map coverage (see Backscatter A-E--Offshore of Bolinas, California, DS 781). Within the acoustic-backscatter imagery, brighter tones indicate higher backscatter intensity, and darker tones indicate lower backscatter intensity. The intensity represents a complex interaction between the acoustic pulse and the seafloor, as well as characteristics within the shallow subsurface, providing a general indication of seafloor texture and sediment type. Backscatter intensity depends on the acoustic source level; the frequency used to image the seafloor; the grazing angle; the composition and character of the seafloor, including grain size, water content, bulk density, and seafloor roughness; and some biological cover. Harder and rougher bottom types such as rocky outcrops or coarse sediment typically return stronger intensities (high backscatter, lighter tones), whereas softer bottom types such as fine sediment return weaker intensities (low backscatter, darker tones). These data are not intended for navigational purposes.

This part of DS 781 presents data for the acoustic-backscatter map of the Offshore of Bolinas map area, California. Backscatter data are provided as separate grids depending on mapping system or processing method. The raster data file is included in "BackscatterB_8101_2007_OffshoreBolinas.zip", which are accessible from https://pubs.usgs.gov/ds/781/OffshoreBolinas/data_catalog_OffshoreBolinas.html. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Johnson, S.Y., Greene, H.G., Erdey, M.D., Golden, N.E., Hartwell, S.R., Manson, M.W., Sliter, R.W., Endris, C.A., Watt, J.T., Ross, S.L., Kvitek, R.G., Phillips, E.L., Bruns, T.R., and Chin, J.L. (G.R. Cochrane and S.A. Cochran, eds.), 2015, California State Waters Map Series — Offshore of Bolinas, California: U.S. Geological Survey Open-File Report 2015–1135, pamphlet 36 p., 10 sheets, https://doi.org/10.3133/ofr20151135. The acoustic-backscatter map of the Offshore of Bolinas map area, California, was generated from backscatter collected by California State University, Monterey Bay (CSUMB), by Fugro Pelagos, and by Moss Landing Marine Laboratory (MLML). Mapping was completed between 2004 and 2010, using a combination of 200-kHz and 400-kHz Reson 7125, and 244-kHz Reson 8101 multibeam echosounders, as well as 468-kHz SEA SWATHPlus and 250-kHz GeoSwath interferometric systems. Moss Landing Marine Laboratory mapped the nearshore region north of Bolinas in 2004 prior to the California Seafloor Mapping Program (CSMP). The nearshore region from south of Bolinas Lagoon to Stinson Beach was mapped by Fugro Pelagos in 2009 for a project outside of the CSMP and only bathymetry data were collected. Therefore, note that the shaded relief map coverage (see Bathymetry Hillshade--Offshore of Bolinas, California, DS 781) does not match the acoustic-backscatter map coverage (see Backscatter A-E--Offshore of Bolinas, California, DS 781). Within the acoustic-backscatter imagery, brighter tones indicate higher backscatter intensity, and darker tones indicate lower backscatter intensity. The intensity represents a complex interaction between the acoustic pulse and the seafloor, as well as characteristics within the shallow subsurface, providing a general indication of seafloor texture and sediment type. Backscatter intensity depends on the acoustic source level; the frequency used to image the seafloor; the grazing angle; the composition and character of the seafloor, including grain size, water content, bulk density, and seafloor roughness; and some biological cover. Harder and rougher bottom types such as rocky outcrops or coarse sediment typically return stronger intensities (high backscatter, lighter tones), whereas softer bottom types such as fine sediment return weaker intensities (low backscatter, darker tones). These data are not intended for navigational purposes.

This part of DS 781 presents data for the acoustic-backscatter map of the Offshore of Bolinas map area, California. Backscatter data are provided as separate grids depending on mapping system or processing method. The raster data files is included in "BackscatterC_7125_OffshoreBolinas.zip", which are accessible from https://pubs.usgs.gov/ds/781/OffshoreBolinas/data_catalog_OffshoreBolinas.html. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Johnson, S.Y., Greene, H.G., Erdey, M.D., Golden, N.E., Hartwell, S.R., Manson, M.W., Sliter, R.W., Endris, C.A., Watt, J.T., Ross, S.L., Kvitek, R.G., Phillips, E.L., Bruns, T.R., and Chin, J.L. (G.R. Cochrane and S.A. Cochran, eds.), 2015, California State Waters Map Series — Offshore of Bolinas, California: U.S. Geological Survey Open-File Report 2015–1135, pamphlet 36 p., 10 sheets, https://doi.org/10.3133/ofr20151135. The acoustic-backscatter map of the Offshore of Bolinas map area, California, was generated from backscatter collected by California State University, Monterey Bay (CSUMB), by Fugro Pelagos, and by Moss Landing Marine Laboratory (MLML). Mapping was completed between 2004 and 2010, using a combination of 200-kHz and 400-kHz Reson 7125, and 244-kHz Reson 8101 multibeam echosounders, as well as 468-kHz SEA SWATHPlus and 250-kHz GeoSwath interferometric systems. Moss Landing Marine Laboratory mapped the nearshore region north of Bolinas in 2004 prior to the California Seafloor Mapping Program (CSMP). The nearshore region from south of Bolinas Lagoon to Stinson Beach was mapped by Fugro Pelagos in 2009 for a project outside of the CSMP and only bathymetry data were collected. Therefore, note that the shaded relief map coverage (see Bathymetry Hillshade--Offshore of Bolinas, California, DS 781) does not match the acoustic-backscatter map coverage (see Backscatter A-E--Offshore of Bolinas, California, DS 781). Within the acoustic-backscatter imagery, brighter tones indicate higher backscatter intensity, and darker tones indicate lower backscatter intensity. The intensity represents a complex interaction between the acoustic pulse and the seafloor, as well as characteristics within the shallow subsurface, providing a general indication of seafloor texture and sediment type. Backscatter intensity depends on the acoustic source level; the frequency used to image the seafloor; the grazing angle; the composition and character of the seafloor, including grain size, water content, bulk density, and seafloor roughness; and some biological cover. Harder and rougher bottom types such as rocky outcrops or coarse sediment typically return stronger intensities (high backscatter, lighter tones), whereas softer bottom types such as fine sediment return weaker intensities (low backscatter, darker tones). These data are not intended for navigational purposes.

This part of DS 781 presents data for the acoustic-backscatter map of the Offshore of Bolinas map area, California. Backscatter data are provided as separate grids depending on mapping system or processing method. The raster data files is included in "BackscatterD_Snippets_OffshoreBolinas.zip", which are accessible from https://pubs.usgs.gov/ds/781/OffshoreBolinas/data_catalog_OffshoreBolinas.html. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Johnson, S.Y., Greene, H.G., Erdey, M.D., Golden, N.E., Hartwell, S.R., Manson, M.W., Sliter, R.W., Endris, C.A., Watt, J.T., Ross, S.L., Kvitek, R.G., Phillips, E.L., Bruns, T.R., and Chin, J.L. (G.R. Cochrane and S.A. Cochran, eds.), 2015, California State Waters Map Series — Offshore of Bolinas, California: U.S. Geological Survey Open-File Report 2015–1135, pamphlet 36 p., 10 sheets, https://doi.org/10.3133/ofr20151135. The acoustic-backscatter map of the Offshore of Bolinas map area, California, was generated from backscatter collected by California State University, Monterey Bay (CSUMB), by Fugro Pelagos, and by Moss Landing Marine Laboratory (MLML). Mapping was completed between 2004 and 2010, using a combination of 200-kHz and 400-kHz Reson 7125, and 244-kHz Reson 8101 multibeam echosounders, as well as 468-kHz SEA SWATHPlus and 250-kHz GeoSwath interferometric systems. Moss Landing Marine Laboratory mapped the nearshore region north of Bolinas in 2004 prior to the California Seafloor Mapping Program (CSMP). The nearshore region from south of Bolinas Lagoon to Stinson Beach was mapped by Fugro Pelagos in 2009 for a project outside of the CSMP and only bathymetry data were collected. Therefore, note that the shaded relief map coverage (see Bathymetry Hillshade--Offshore of Bolinas, California, DS 781) does not match the acoustic-backscatter map coverage (see Backscatter A-E--Offshore of Bolinas, California, DS 781). Within the acoustic-backscatter imagery, brighter tones indicate higher backscatter intensity, and darker tones indicate lower backscatter intensity. The intensity represents a complex interaction between the acoustic pulse and the seafloor, as well as characteristics within the shallow subsurface, providing a general indication of seafloor texture and sediment type. Backscatter intensity depends on the acoustic source level; the frequency used to image the seafloor; the grazing angle; the composition and character of the seafloor, including grain size, water content, bulk density, and seafloor roughness; and some biological cover. Harder and rougher bottom types such as rocky outcrops or coarse sediment typically return stronger intensities (high backscatter, lighter tones), whereas softer bottom types such as fine sediment return weaker intensities (low backscatter, darker tones). These data are not intended for navigational purposes.

This part of DS 781 presents data for the acoustic-backscatter map of the Offshore of Bolinas map area, California. Backscatter data are provided as separate grids depending on mapping system or processing method. The raster data files is included in "BackscatterE_Swath_OffshoreBolinas.zip", which are accessible from https://pubs.usgs.gov/ds/781/OffshoreBolinas/data_catalog_OffshoreBolinas.html. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Johnson, S.Y., Greene, H.G., Erdey, M.D., Golden, N.E., Hartwell, S.R., Manson, M.W., Sliter, R.W., Endris, C.A., Watt, J.T., Ross, S.L., Kvitek, R.G., Phillips, E.L., Bruns, T.R., and Chin, J.L. (G.R. Cochrane and S.A. Cochran, eds.), 2015, California State Waters Map Series — Offshore of Bolinas, California: U.S. Geological Survey Open-File Report 2015–1135, pamphlet 36 p., 10 sheets, https://doi.org/10.3133/ofr20151135. The acoustic-backscatter map of the Offshore of Bolinas map area, California, was generated from backscatter collected by California State University, Monterey Bay (CSUMB), by Fugro Pelagos, and by Moss Landing Marine Laboratory (MLML). Mapping was completed between 2004 and 2010, using a combination of 200-kHz and 400-kHz Reson 7125, and 244-kHz Reson 8101 multibeam echosounders, as well as 468-kHz SEA SWATHPlus and 250-kHz GeoSwath interferometric systems. Moss Landing Marine Laboratory mapped the nearshore region north of Bolinas in 2004 prior to the California Seafloor Mapping Program (CSMP). The nearshore region from south of Bolinas Lagoon to Stinson Beach was mapped by Fugro Pelagos in 2009 for a project outside of the CSMP and only bathymetry data were collected. Therefore, note that the shaded relief map coverage (see Bathymetry Hillshade--Offshore of Bolinas, California, DS 781) does not match the acoustic-backscatter map coverage (see Backscatter A-E--Offshore of Bolinas, California, DS 781). Within the acoustic-backscatter imagery, brighter tones indicate higher backscatter intensity, and darker tones indicate lower backscatter intensity. The intensity represents a complex interaction between the acoustic pulse and the seafloor, as well as characteristics within the shallow subsurface, providing a general indication of seafloor texture and sediment type. Backscatter intensity depends on the acoustic source level; the frequency used to image the seafloor; the grazing angle; the composition and character of the seafloor, including grain size, water content, bulk density, and seafloor roughness; and some biological cover. Harder and rougher bottom types such as rocky outcrops or coarse sediment typically return stronger intensities (high backscatter, lighter tones), whereas softer bottom types such as fine sediment return weaker intensities (low backscatter, darker tones). These data are not intended for navigational purposes.

This part of DS 781 presents data for the bathymetric contours for several seafloor maps of the Offshore of Bolinas map area, California. The vector data file is included in "Contours_OffshoreBolinas.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreBolinas/data_catalog_OffshoreBolinas.html. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Johnson, S.Y., Greene, H.G., Erdey, M.D., Golden, N.E., Hartwell, S.R., Manson, M.W., Sliter, R.W., Endris, C.A., Watt, J.T., Ross, S.L., Kvitek, R.G., Phillips, E.L., Bruns, T.R., and Chin, J.L. (G.R. Cochrane and S.A. Cochran, eds.), 2015, California State Waters Map Series — Offshore of Bolinas, California: U.S. Geological Survey Open-File Report 2015–1135, pamphlet 36 p., 10 sheets, https://doi.org/10.3133/ofr20151135. 10-m interval contours of the Offshore of Bolinas map area, California, were generated from bathymetry data collected by California State University, Monterey Bay (CSUMB), by Fugro Pelagos, and by Moss Landing Marine Laboratory (MLML). Mapping was completed between 2004 and 2010, using a combination of 200-kHz and 400-kHz Reson 7125, and 244-kHz Reson 8101 multibeam echosounders, as well as 468-kHz SEA SWATHPlus and 250-kHz GeoSwath interferometric systems. These mapping missions combined to collect bathymetry from about the 10-m isobath to beyond the 3-nautical-mile limit of California's State Waters. Bathymetric contours at 10-m intervals were generated from a modified 10-m bathymetric surface. The most continuous contour segments were preserved while smaller segments and isolated island polygons were excluded from the final output. Contours were smoothed via a polynomial approximation with exponential kernel (PAEK) algorithm using a tolerance value of 60 m. The contours were then clipped to the boundary of the map area. These data are not intended for navigational purposes.

This data set consists of physics-based Delft3D-FLOW and WAVE hydrodynamic model input files used for Coastal Storm Modeling System (CoSMoS) Tier 1 simulations. Tier 1 simulations cover the Northern California open-coast region, from the Golden Gate Bridge to the California/Oregon state border, and they provide boundary conditions to higher-resolution simulations. Simulations are run for several storm events (covering a range of no storm, 1-year, 20-year, and 100-year coastal storm conditions) and sea-level rise (SLR) scenarios.

This part of DS 781 presents data for the acoustic-backscatter map of the Offshore of San Francisco map area, California. Backscatter data are provided as separate grids depending on mapping system used and processing techniques. The raster data file is included in "BackscatterA_8101_2004_OffshoreSanFrancisco.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreSanFrancisco/data_catalog_OffshoreSanFrancisco.html. These data accompany the pamphlet and map sheets of Cochrane, G.R., Johnson, S.Y., Dartnell, P., Greene, H.G., Erdey, M.D., Golden, N.E., Hartwell, S.R., Endris, C.A., Manson, M.W., Sliter, R.W., Kvitek, R.G., Watt, J.T., Ross, S.L., and Bruns, T.R. (G.R. Cochrane and S.A. Cochran, eds.), 2015, California State Waters Map Series—Offshore of San Francisco, California (ver. 1.1, June 2015): U.S. Geological Survey Open-File Report 2015–1068, pamphlet 39 p., 10 sheets, scale 1:24,000, https://dx.doi.org/10.3133/ofr20151068. The acoustic-backscatter map of the Offshore of San Francisco Map Area, California was generated from backscatter data collected by Fugro Pelagos and by California State University, Monterey Bay (CSUMB). Mapping was completed between 2004 and 2008, using a combination of 400-kHz Reson 7125 and 244-kHz Reson 8101 multibeam echosounders. Within the final imagery, brighter tones indicate higher backscatter intensity, and darker tones indicate lower backscatter intensity. The intensity represents a complex interaction between the acoustic pulse and the seafloor, as well as characteristics within the shallow subsurface, providing a general indication of seafloor texture and composition. Backscatter intensity depends on the acoustic source level; the frequency used to image the seafloor; the grazing angle; the composition and character of the seafloor, including grain size, water content, bulk density, and seafloor roughness; and some biological cover. Harder and rougher bottom types such as rocky outcrops or coarse sediment typically return stronger intensities (high backscatter, lighter tones), whereas softer bottom types such as fine sediment return weaker intensities (low backscatter, darker tones).

This part of DS 781 presents data for the acoustic-backscatter map of the Offshore of San Francisco map area, California. Backscatter data are provided as separate grids depending on mapping system used and processing techniques. The raster data file is included in "BackscatterB_8101_2007_OffshoreSanFrancisco.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreSanFrancisco/data_catalog_OffshoreSanFrancisco.html. These data accompany the pamphlet and map sheets of Cochrane, G.R., Johnson, S.Y., Dartnell, P., Greene, H.G., Erdey, M.D., Golden, N.E., Hartwell, S.R., Endris, C.A., Manson, M.W., Sliter, R.W., Kvitek, R.G., Watt, J.T., Ross, S.L., and Bruns, T.R. (G.R. Cochrane and S.A. Cochran, eds.), 2015, California State Waters Map Series—Offshore of San Francisco, California (ver. 1.1, June 2015): U.S. Geological Survey Open-File Report 2015–1068, pamphlet 39 p., 10 sheets, scale 1:24,000, https://dx.doi.org/10.3133/ofr20151068. The acoustic-backscatter map of the Offshore of San Francisco Map Area, California was generated from backscatter data collected by Fugro Pelagos and by California State University, Monterey Bay (CSUMB). Mapping was completed between 2004 and 2008, using a combination of 400-kHz Reson 7125 and 244-kHz Reson 8101 multibeam echosounders. Within the final imagery, brighter tones indicate higher backscatter intensity, and darker tones indicate lower backscatter intensity. The intensity represents a complex interaction between the acoustic pulse and the seafloor, as well as characteristics within the shallow subsurface, providing a general indication of seafloor texture and composition. Backscatter intensity depends on the acoustic source level; the frequency used to image the seafloor; the grazing angle; the composition and character of the seafloor, including grain size, water content, bulk density, and seafloor roughness; and some biological cover. Harder and rougher bottom types such as rocky outcrops or coarse sediment typically return stronger intensities (high backscatter, lighter tones), whereas softer bottom types such as fine sediment return weaker intensities (low backscatter, darker tones).

This part of DS 781 presents data for the acoustic-backscatter map of the Offshore of San Francisco map area, California. Backscatter data are provided as separate grids depending on mapping system used and processing techniques. The raster data file is included in "BackscatterC_8101_2008_OffshoreSanFrancisco.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreSanFrancisco/data_catalog_OffshoreSanFrancisco.html. These data accompany the pamphlet and map sheets of Cochrane, G.R., Johnson, S.Y., Dartnell, P., Greene, H.G., Erdey, M.D., Golden, N.E., Hartwell, S.R., Endris, C.A., Manson, M.W., Sliter, R.W., Kvitek, R.G., Watt, J.T., Ross, S.L., and Bruns, T.R. (G.R. Cochrane and S.A. Cochran, eds.), 2015, California State Waters Map Series—Offshore of San Francisco, California (ver. 1.1, June 2015): U.S. Geological Survey Open-File Report 2015–1068, pamphlet 39 p., 10 sheets, scale 1:24,000, https://dx.doi.org/10.3133/ofr20151068. The acoustic-backscatter map of the Offshore of San Francisco Map Area, California was generated from backscatter data collected by Fugro Pelagos and by California State University, Monterey Bay (CSUMB). Mapping was completed between 2004 and 2008, using a combination of 400-kHz Reson 7125 and 244-kHz Reson 8101 multibeam echosounders. Within the final imagery, brighter tones indicate higher backscatter intensity, and darker tones indicate lower backscatter intensity. The intensity represents a complex interaction between the acoustic pulse and the seafloor, as well as characteristics within the shallow subsurface, providing a general indication of seafloor texture and composition. Backscatter intensity depends on the acoustic source level; the frequency used to image the seafloor; the grazing angle; the composition and character of the seafloor, including grain size, water content, bulk density, and seafloor roughness; and some biological cover. Harder and rougher bottom types such as rocky outcrops or coarse sediment typically return stronger intensities (high backscatter, lighter tones), whereas softer bottom types such as fine sediment return weaker intensities (low backscatter, darker tones).

This part of DS 781 presents data for the acoustic-backscatter map of the Offshore of San Francisco map area, California. Backscatter data are provided as separate grids depending on mapping system used and processing techniques. The raster data file is included in "BackscatterD_7125_2008_OffshoreSanFrancisco.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreSanFrancisco/data_catalog_OffshoreSanFrancisco.html. These data accompany the pamphlet and map sheets of Cochrane, G.R., Johnson, S.Y., Dartnell, P., Greene, H.G., Erdey, M.D., Golden, N.E., Hartwell, S.R., Endris, C.A., Manson, M.W., Sliter, R.W., Kvitek, R.G., Watt, J.T., Ross, S.L., and Bruns, T.R. (G.R. Cochrane and S.A. Cochran, eds.), 2015, California State Waters Map Series—Offshore of San Francisco, California (ver. 1.1, June 2015): U.S. Geological Survey Open-File Report 2015–1068, pamphlet 39 p., 10 sheets, scale 1:24,000, https://dx.doi.org/10.3133/ofr20151068. The acoustic-backscatter map of the Offshore of San Francisco Map Area, California was generated from backscatter data collected by Fugro Pelagos and by California State University, Monterey Bay (CSUMB). Mapping was completed between 2004 and 2008, using a combination of 400-kHz Reson 7125 and 244-kHz Reson 8101 multibeam echosounders. Within the final imagery, brighter tones indicate higher backscatter intensity, and darker tones indicate lower backscatter intensity. The intensity represents a complex interaction between the acoustic pulse and the seafloor, as well as characteristics within the shallow subsurface, providing a general indication of seafloor texture and composition. Backscatter intensity depends on the acoustic source level; the frequency used to image the seafloor; the grazing angle; the composition and character of the seafloor, including grain size, water content, bulk density, and seafloor roughness; and some biological cover. Harder and rougher bottom types such as rocky outcrops or coarse sediment typically return stronger intensities (high backscatter, lighter tones), whereas softer bottom types such as fine sediment return weaker intensities (low backscatter, darker tones).

This part of DS 781 presents data for the shaded-relief bathymetry map of the Offshore of San Francisco, California, map area. The raster data file is included in "BathymetryHS_OffshoreSanFrancisco.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreSanFrancisco/data_catalog_OffshoreSanFrancisco.html. These data accompany the pamphlet and map sheets of Cochrane, G.R., Johnson, S.Y., Dartnell, P., Greene, H.G., Erdey, M.D., Golden, N.E., Hartwell, S.R., Endris, C.A., Manson, M.W., Sliter, R.W., Kvitek, R.G., Watt, J.T., Ross, S.L., and Bruns, T.R. (G.R. Cochrane and S.A. Cochran, eds.), 2015, California State Waters Map Series—Offshore of San Francisco, California (ver. 1.1, June 2015): U.S. Geological Survey Open-File Report 2015–1068, pamphlet 39 p., 10 sheets, scale 1:24,000, https://dx.doi.org/10.3133/ofr20151068. The shaded-relief bathymetry map of Offshore of San Francisco, California, was generated from bathymetry data collected by Fugro Pelagos, and by California State University, Monterey Bay (CSUMB). Mapping was completed between 2004 and 2008, using a combination of 400-kHz Reson 7125 and 244-kHz Reson 8101 multibeam echosounders. These mapping missions combined to collect bathymetry (sheets 1, 2) from about the 10-m isobath to beyond the 3-nautical-mile limit of California's State Waters. A large portion of this map area was re-mapped in 2009, however the older bathymetry data were used in this map due to co-registered, acoustic backscatter data.

This part of DS 781 presents data for the bathymetric contours for several seafloor maps of the Offshore of San Francisco map area, California. The vector data file is included in "Contours_OffshoreSanFrancisco.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreSanFrancisco/data_catalog_OffshoreSanFrancisco.html. These data accompany the pamphlet and map sheets of Cochrane, G.R., Johnson, S.Y., Dartnell, P., Greene, H.G., Erdey, M.D., Golden, N.E., Hartwell, S.R., Endris, C.A., Manson, M.W., Sliter, R.W., Kvitek, R.G., Watt, J.T., Ross, S.L., and Bruns, T.R. (G.R. Cochrane and S.A. Cochran, eds.), 2015, California State Waters Map Series—Offshore of San Francisco, California (ver. 1.1, June 2015): U.S. Geological Survey Open-File Report 2015–1068, pamphlet 39 p., 10 sheets, scale 1:24,000, https://dx.doi.org/10.3133/ofr20151068. 10-m interval contours of the Offshore of San Francisco map area, California, were generated from bathymetry data collected by Fugro Pelagos and by California State University, Monterey Bay, Seafloor Mapping Lab (CSUMB). Mapping was completed between 2004 and 2008, using a combination of 400-kHz Reson 7125 and 244-kHz Reson 8101 multibeam echosounders. These mapping missions combined to collect bathymetry from about the 10-m isobath to beyond the 3-nautical-mile limit of California's State Waters. Bathymetric contours at 10-m intervals were generated from the merged 2-m bathymetric surface. The most continuous contour segments were preserved while smaller segments and isolated island polygons were excluded from the final output. Contours were smoothed via a polynomial approximation with exponential kernel (PAEK) algorithm using a tolerance value of 60 m. The contours were then clipped to the boundary of the map area. These data are not intended for navigational purposes.

This part of DS 781 presents data for the geologic and geomorphic map of the Offshore of Bolinas map area, California. The vector data file is included in "Geology_OffshoreBolinas.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreBolinas/data_catalog_OffshoreBolinas.html. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Johnson, S.Y., Greene, H.G., Erdey, M.D., Golden, N.E., Hartwell, S.R., Manson, M.W., Sliter, R.W., Endris, C.A., Watt, J.T., Ross, S.L., Kvitek, R.G., Phillips, E.L., Bruns, T.R., and Chin, J.L. (G.R. Cochrane and S.A. Cochran, eds.), 2015, California State Waters Map Series — Offshore of Bolinas, California: U.S. Geological Survey Open-File Report 2015–1135, pamphlet 36 p., 10 sheets, https://doi.org/10.3133/ofr20151135. Marine geology and geomorphology was mapped in the Offshore of Bolinas map area, California, from approximate Mean High Water (MHW) to the 3-nautical-mile limit of California's State Waters. Offshore geologic units were delineated on the basis of integrated analyses of adjacent onshore geology with multibeam bathymetry and backscatter imagery, seafloor-sediment and rock samples, digital camera and video imagery, and high-resolution seismic-reflection profiles.

This part of DS 781 presents data for the acoustic-backscatter map of Offshore of Pacifica map area, California. Backscatter data are provided as two separate grids depending on mapping system. The raster data files are included in "BackscatterA_8101_OffshorePacifica.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshorePacifica/data_catalog_OffshorePacifica.html. These data accompany the pamphlet and map sheets of Edwards, B.D., Phillips, E.L., Dartnell, P., Greene, H.G., Bretz, C.K., Kvitek, R.G., Hartwell, S.R., Johnson, S.Y., Cochrane, G.R., Dieter, B.E., Sliter, R.W., Ross, S.L., Golden, N.E., Watt, J.T., Chin, J.L., Erdey, M.D., Krigsman, L.M., Manson, M.W., and Endris, C.A. (S.A. Cochran and B.D. Edwards, eds.), 2014, California State Waters Map Series—Offshore of Pacifica, California: U.S. Geological Survey Open-File Report 2014–1260, pamphlet 38 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20141260. The acoustic-backscatter map of the Offshore of Pacifica, California was generated from backscatter data collected by Fugro Pelagos and by California State University, Monterey Bay (CSUMB). Mapping was completed between 2005 and 2007, using a combination of 400-kHz Reson 7125 and 244-kHz Reson 8101 multibeam echosounders. Within the final imagery, brighter tones indicate higher backscatter intensity, and darker tones indicate lower backscatter intensity. The intensity represents a complex interaction between the acoustic pulse and the seafloor, as well as characteristics within the shallow subsurface, providing a general indication of seafloor texture and composition. Backscatter intensity depends on the acoustic source level; the frequency used to image the seafloor; the grazing angle; the composition and character of the seafloor, including grain size, water content, bulk density, and seafloor roughness; and some biological cover. Harder and rougher bottom types such as rocky outcrops or coarse sediment typically return stronger intensities (high backscatter, lighter tones), whereas softer bottom types such as fine sediment return weaker intensities (low backscatter, darker tones).

This part of DS 781 presents data for the acoustic-backscatter map of Offshore of Pacifica map area, California. Backscatter data are provided as two separate grids depending on mapping system. The raster data files are included in "Backscatter7125_OffshorePacifica.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshorePacifica/data_catalog_OffshorePacifica.html. These data accompany the pamphlet and map sheets of Edwards, B.D., Phillips, E.L., Dartnell, P., Greene, H.G., Bretz, C.K., Kvitek, R.G., Hartwell, S.R., Johnson, S.Y., Cochrane, G.R., Dieter, B.E., Sliter, R.W., Ross, S.L., Golden, N.E., Watt, J.T., Chin, J.L., Erdey, M.D., Krigsman, L.M., Manson, M.W., and Endris, C.A. (S.A. Cochran and B.D. Edwards, eds.), 2014, California State Waters Map Series—Offshore of Pacifica, California: U.S. Geological Survey Open-File Report 2014–1260, pamphlet 38 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20141260. The acoustic-backscatter map of the Offshore of Pacifica, California was generated from backscatter data collected by Fugro Pelagos and by California State University, Monterey Bay (CSUMB). Mapping was completed between 2005 and 2007, using a combination of 400-kHz Reson 7125 and 244-kHz Reson 8101 multibeam echosounders. Within the final imagery, brighter tones indicate higher backscatter intensity, and darker tones indicate lower backscatter intensity. The intensity represents a complex interaction between the acoustic pulse and the seafloor, as well as characteristics within the shallow subsurface, providing a general indication of seafloor texture and composition. Backscatter intensity depends on the acoustic source level; the frequency used to image the seafloor; the grazing angle; the composition and character of the seafloor, including grain size, water content, bulk density, and seafloor roughness; and some biological cover. Harder and rougher bottom types such as rocky outcrops or coarse sediment typically return stronger intensities (high backscatter, lighter tones), whereas softer bottom types such as fine sediment return weaker intensities (low backscatter, darker tones).

This part of DS 781 presents data for the hillshaded bathymetry map of Offshore Pacifica, California. The raster data file is included in "BathymetryHS_OffshorePacifica.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshorePacifica/data_catalog_OffshorePacifica.html. These data accompany the pamphlet and map sheets of Edwards, B.D., Phillips, E.L., Dartnell, P., Greene, H.G., Bretz, C.K., Kvitek, R.G., Hartwell, S.R., Johnson, S.Y., Cochrane, G.R., Dieter, B.E., Sliter, R.W., Ross, S.L., Golden, N.E., Watt, J.T., Chin, J.L., Erdey, M.D., Krigsman, L.M., Manson, M.W., and Endris, C.A. (S.A. Cochran and B.D. Edwards, eds.), 2014, California State Waters Map Series—Offshore of Pacifica, California: U.S. Geological Survey Open-File Report 2014–1260, pamphlet 38 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20141260. The shaded-relief bathymetry of Offshore Pacifica, California, was generated from bathymetry data collected by Fugro Pelagos, and by California State University, Monterey Bay (CSUMB). Mapping was completed between 2005 and 2007, using a combination of 400-kHz Reson 7125 and 244-kHz Reson 8101 multibeam echosounders. These mapping missions combined to collect bathymetry from about the 10-m isobath to beyond the 3-nautical-mile limit of California's State Waters.

This part of DS 781 presents data for the bathymetry map of Offshore Pacifica, California. The raster data file is included in "Bathymetry_OffshorePacifica.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshorePacifica/data_catalog_OffshorePacifica.html. These data accompany the pamphlet and map sheets of Edwards, B.D., Phillips, E.L., Dartnell, P., Greene, H.G., Bretz, C.K., Kvitek, R.G., Hartwell, S.R., Johnson, S.Y., Cochrane, G.R., Dieter, B.E., Sliter, R.W., Ross, S.L., Golden, N.E., Watt, J.T., Chin, J.L., Erdey, M.D., Krigsman, L.M., Manson, M.W., and Endris, C.A. (S.A. Cochran and B.D. Edwards, eds.), 2014, California State Waters Map Series—Offshore of Pacifica, California: U.S. Geological Survey Open-File Report 2014–1260, pamphlet 38 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20141260. The bathymetry map of Offshore Pacifica, California, was generated from bathymetry data collected by Fugro Pelagos, and by California State University, Monterey Bay (CSUMB). Mapping was completed between 2005 and 2007, using a combination of 400-kHz Reson 7125 and 244-kHz Reson 8101 multibeam echosounders. These mapping missions combined to collect bathymetry from about the 10-m isobath to beyond the 3-nautical-mile limit of California's State Waters.

This part of DS 781 presents the seafloor-character map Offshore of Pacifica, California. The raster data file is included in "SFC_OffshorePacifica.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshorePacifica/data_catalog_OffshorePacifica.html. These data accompany the pamphlet and map sheets of Edwards, B.D., Phillips, E.L., Dartnell, P., Greene, H.G., Bretz, C.K., Kvitek, R.G., Hartwell, S.R., Johnson, S.Y., Cochrane, G.R., Dieter, B.E., Sliter, R.W., Ross, S.L., Golden, N.E., Watt, J.T., Chin, J.L., Erdey, M.D., Krigsman, L.M., Manson, M.W., and Endris, C.A. (S.A. Cochran and B.D. Edwards, eds.), 2014, California State Waters Map Series—Offshore of Pacifica, California: U.S. Geological Survey Open-File Report 2014–1260, pamphlet 38 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20141260. This raster-format seafloor-character map shows four substrate classes of Offshore of Pacifica, California. The substrate classes mapped in this area have been further divided into the following California Marine Life Protection Act depth zones and slope classes: Depth Zone 2 (intertidal to 30 m), Depth Zone 3 (30 to 100 m), and Slope Class 1 (0 degrees - 5 degrees). Depth Zone 1 (intertidal), Depth Zones 4-5 (greater than 100 m), and Slopes Classes 2-4 (greater than 5 degrees) are not present in the region covered by this block. The map is created using a supervised classification method described by Cochrane (2008). References Cited: California Department of Fish and Game, 2008, California Marine Life Protection Act master plan for marine protected areas; Revised draft: California Department of Fish and Game, accessed April 5 2011, at http://www.dfg.ca.gov/mlpa/masterplan.asp. Cochrane, G.R., 2008, Video-supervised classification of sonar data for mapping seafloor habitat, in Reynolds, J.R., and Greene, H.G., eds., Marine habitat mapping technology for Alaska: Fairbanks, University of Alaska, Alaska Sea Grant College Program, p. 185-194, accessed April 5, 2011, at http://doc.nprb.org/web/research/research%20pubs/615_habitat_mapping_workshop/Individual%20Chapters%20High-Res/Ch13%20Cochrane.pdf. Sappington, J.M., Longshore, K.M., and Thompson, D.B., 2007, Quantifying landscape ruggedness for animal habitat analysis--A case study using bighorn sheep in the Mojave Desert: Journal of Wildlife Management, v. 71, p. 1419-1426.

This part of DS 781 presents data for the shaded-relief bathymetry map of the Offshore of Bolinas, California. The raster data file is included in "BathymetryHS_OffshoreBolinas.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreBolinas/data_catalog_OffshoreBolinas.html. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Johnson, S.Y., Greene, H.G., Erdey, M.D., Golden, N.E., Hartwell, S.R., Manson, M.W., Sliter, R.W., Endris, C.A., Watt, J.T., Ross, S.L., Kvitek, R.G., Phillips, E.L., Bruns, T.R., and Chin, J.L. (G.R. Cochrane and S.A. Cochran, eds.), 2015, California State Waters Map Series — Offshore of Bolinas, California: U.S. Geological Survey Open-File Report 2015–1135, pamphlet 36 p., 10 sheets, https://doi.org/10.3133/ofr20151135. The shaded-relief bathymetry map of Offshore Bolinas, California, was generated from bathymetry data collected by California State University, Monterey Bay (CSUMB), by Fugro Pelagos, and by Moss Landing Marine Laboratory (MLML). Mapping was completed between 2004 and 2010, using a combination of 200-kHz and 400-kHz Reson 7125, and 244-kHz Reson 8101 multibeam echosounders, as well as 468-kHz SEA SWATHPlus and 250-kHz GeoSwath interferometric systems. Moss Landing Marine Laboratory mapped the nearshore region north of Bolinas in 2004 prior to the California Seafloor Mapping Program (CSMP). The nearshore region from south of Bolinas Lagoon to Stinson Beach was mapped by Fugro Pelagos in 2009 for a project outside of the CSMP and only bathymetry data were collected. These mapping missions combined to collect bathymetry from about the 10-m isobath to beyond the 3-nautical-mile limit of California's State Waters.

This part of DS 781 presents data for the bathymetry map of the Offshore of Bolinas, California. The raster data file is included in "Bathymetry_OffshoreBolinas.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreBolinas/data_catalog_OffshoreBolinas.html. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Johnson, S.Y., Greene, H.G., Erdey, M.D., Golden, N.E., Hartwell, S.R., Manson, M.W., Sliter, R.W., Endris, C.A., Watt, J.T., Ross, S.L., Kvitek, R.G., Phillips, E.L., Bruns, T.R., and Chin, J.L. (G.R. Cochrane and S.A. Cochran, eds.), 2015, California State Waters Map Series — Offshore of Bolinas, California: U.S. Geological Survey Open-File Report 2015–1135, pamphlet 36 p., 10 sheets, https://doi.org/10.3133/ofr20151135. The bathymetry map of Offshore Bolinas, California, was generated from bathymetry data collected by California State University, Monterey Bay (CSUMB), by Fugro Pelagos, and by Moss Landing Marine Laboratory (MLML). Mapping was completed between 2004 and 2010, using a combination of 200-kHz and 400-kHz Reson 7125, and 244-kHz Reson 8101 multibeam echosounders, as well as 468-kHz SEA SWATHPlus and 250-kHz GeoSwath interferometric systems. Moss Landing Marine Laboratory mapped the nearshore region north of Bolinas in 2004 prior to the California Seafloor Mapping Program (CSMP). The nearshore region from south of Bolinas Lagoon to Stinson Beach was mapped by Fugro Pelagos in 2009 for a project outside of the CSMP and only bathymetry data were collected. These mapping missions combined to collect bathymetry from about the 10-m isobath to beyond the 3-nautical-mile limit of California's State Waters. NOTE: the horizontal datum of the bathymetry data (NAD83) differs from the horizontal datum of other layers in this data series (WGS84). Some bathymetry grids within this map were projected horizontally from WGS84 to NAD83 using ESRI tools to be more consistent with the vertical reference of the North American Vertical Datum of 1988 (NAVD88). These data are not intended for navigational purposes.

This part of DS 781 presents the seafloor-character map Offshore of Bolinas, California (raster data file is included in "SeafloorCharacter_OffshoreBolinas.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreBolinas/data_catalog_OffshoreBolinas.html). These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Johnson, S.Y., Greene, H.G., Erdey, M.D., Golden, N.E., Hartwell, S.R., Manson, M.W., Sliter, R.W., Endris, C.A., Watt, J.T., Ross, S.L., Kvitek, R.G., Phillips, E.L., Bruns, T.R., and Chin, J.L. (G.R. Cochrane and S.A. Cochran, eds.), 2015, California State Waters Map Series — Offshore of Bolinas, California: U.S. Geological Survey Open-File Report 2015–1135, pamphlet 36 p., 10 sheets, https://doi.org/10.3133/ofr20151135. This raster-format seafloor-character map shows four substrate classes of Offshore of Bolinas, California. The substrate classes mapped in this area have been further divided into the following California Marine Life Protection Act depth zones and slope classes: Depth Zone 2 (intertidal to 30 m), Depth Zone 3 (30 to 100 m), Slope Class 1 (0 degrees - 5 degrees), and Slope Class 2 (5 degrees - 30 degrees). Depth Zone 1 (intertidal), Depth Zone 4 (100 to 200 m), Depth Zone 5 (greater than 200 m), and Slopes Classes 3-4 (greater than 30 degrees) are not present in the region covered by this block. The map is created using a supervised classification method described by Cochrane (2008). References Cited: California Department of Fish and Game, 2008, California Marine Life Protection Act master plan for marine protected areas; Revised draft: California Department of Fish and Game, accessed April 5 2011, at http://www.dfg.ca.gov/mlpa/masterplan.asp. Cochrane, G.R., 2008, Video-supervised classification of sonar data for mapping seafloor habitat, in Reynolds, J.R., and Greene, H.G., eds., Marine habitat mapping technology for Alaska: Fairbanks, University of Alaska, Alaska Sea Grant College Program, p. 185-194, accessed April 5, 2011, at http://doc.nprb.org/web/research/research%20pubs/615_habitat_mapping_workshop/Individual%20Chapters%20High-Res/Ch13%20Cochrane.pdf. Sappington, J.M., Longshore, K.M., and Thompson, D.B., 2007, Quantifying landscape ruggedness for animal habitat analysis--A case study using bighorn sheep in the Mojave Desert: Journal of Wildlife Management, v. 71, p. 1419-1426.

This part of DS 781 presents data for the acoustic-backscatter map of the Offshore of Fort Ross map area, California. Backscatter data are provided as separate grids depending on mapping system or processing method. The raster data file is included in "BackscatterB_7125_OffshoreFortRoss.zip", which is accessible from https://pubs.usgs.gov/ds/781/OffshoreFortRoss/data_catalog_OffshoreFortRoss.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Golden, N.E., Hartwell, S.R., Erdey, M.D., Greene, H.G., Cochrane, G.R., Kvitek, R.G., Manson, M.W., Endris, C.A., Dieter, B.E., Watt, J.T., Krigsman, L.M., Sliter, R.W., Lowe, E.N., and Chin, J.L. (S.Y. Johnson and S.A. Cochran, eds.), 2015, California State Waters Map Series--Offshore of Fort Ross, California: U.S. Geological Survey Open-File Report 2015–1211, pamphlet 37 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20151211. The acoustic-backscatter map of the Offshore of Fort Ross map area, California, was generated from backscatter data collected by California State University, Monterey Bay (CSUMB) and by Fugro Pelagos. Mapping was completed between 2007 and 2010, using a combination of 200-kHz and 400-kHz Reson 7125, and 244-kHz Reson 8101 multibeam echosounders, as well as 468-kHz SEA SWATHPlus interferometric system. These mapping missions combined to collect backscatter data from about the 10-m isobath to beyond the 3-nautical-mile limit of California State Waters. Within the acoustic-backscatter imagery, brighter tones indicate higher backscatter intensity, and darker tones indicate lower backscatter intensity. The intensity represents a complex interaction between the acoustic pulse and the seafloor, as well as characteristics within the shallow subsurface, providing a general indication of seafloor texture and composition. Backscatter intensity depends on the acoustic source level; the frequency used to image the seafloor; the grazing angle; the composition and character of the seafloor, including grain size, water content, bulk density, and seafloor roughness; and some biological cover. Harder and rougher bottom types such as rocky outcrops or coarse sediment typically return stronger intensities (high backscatter, lighter tones), whereas softer bottom types such as fine sediment return weaker intensities (low backscatter, darker tones). These data are not intended for navigational purposes.

This part of DS 781 presents data for the acoustic-backscatter map of the Offshore of Fort Ross map area, California. Backscatter data are provided as separate grids depending on mapping system or processing method. The raster data file is included in "BackscatterC_Swath_OffshoreFortRoss.zip", which is accessible from https://pubs.usgs.gov/ds/781/OffshoreFortRoss/data_catalog_OffshoreFortRoss.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Golden, N.E., Hartwell, S.R., Erdey, M.D., Greene, H.G., Cochrane, G.R., Kvitek, R.G., Manson, M.W., Endris, C.A., Dieter, B.E., Watt, J.T., Krigsman, L.M., Sliter, R.W., Lowe, E.N., and Chin, J.L. (S.Y. Johnson and S.A. Cochran, eds.), 2015, California State Waters Map Series--Offshore of Fort Ross, California: U.S. Geological Survey Open-File Report 2015–1211, pamphlet 37 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20151211. The acoustic-backscatter map of the Offshore of Fort Ross map area, California, was generated from backscatter data collected by California State University, Monterey Bay (CSUMB) and by Fugro Pelagos. Mapping was completed between 2007 and 2010, using a combination of 200-kHz and 400-kHz Reson 7125, and 244-kHz Reson 8101 multibeam echosounders, as well as 468-kHz SEA SWATHPlus interferometric system. These mapping missions combined to collect backscatter data from about the 10-m isobath to beyond the 3-nautical-mile limit of California State Waters. Within the acoustic-backscatter imagery, brighter tones indicate higher backscatter intensity, and darker tones indicate lower backscatter intensity. The intensity represents a complex interaction between the acoustic pulse and the seafloor, as well as characteristics within the shallow subsurface, providing a general indication of seafloor texture and composition. Backscatter intensity depends on the acoustic source level; the frequency used to image the seafloor; the grazing angle; the composition and character of the seafloor, including grain size, water content, bulk density, and seafloor roughness; and some biological cover. Harder and rougher bottom types such as rocky outcrops or coarse sediment typically return stronger intensities (high backscatter, lighter tones), whereas softer bottom types such as fine sediment return weaker intensities (low backscatter, darker tones). These data are not intended for navigational purposes.

This part of DS 781 presents data for the shaded-relief bathymetry map of the Offshore of Fort Ross map area, California. Raster data file is included in "Bathymetry_OffshoreFortRoss.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreFortRoss/data_catalog_OffshoreFortRoss.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Golden, N.E., Hartwell, S.R., Erdey, M.D., Greene, H.G., Cochrane, G.R., Kvitek, R.G., Manson, M.W., Endris, C.A., Dieter, B.E., Watt, J.T., Krigsman, L.M., Sliter, R.W., Lowe, E.N., and Chin, J.L. (S.Y. Johnson and S.A. Cochran, eds.), 2015, California State Waters Map Series--Offshore of Fort Ross, California: U.S. Geological Survey Open-File Report 2015–1211, pamphlet 37 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20151211. The shaded-relief bathymetry map of the Offshore of Fort Ross Map Area, California, was generated from bathymetry data collected by California State University, Monterey Bay (CSUMB), and by Fugro Pelagos. Mapping was completed between 2007 and 2010, using a combination of 200-kHz and 400-kHz Reson 7125, and 244-kHz Reson 8101 multibeam echosounders, as well as 468-kHz SEA SWATHPlus interferometric system. These mapping missions combined to collect bathymetry from about the 10-m isobath to beyond the 3-nautical-mile limit of California's State Waters.

This part of DS 781 presents data for the bathymetry map of the Offshore of Fort Ross map area, California. Raster data file is included in "Bathymetry_OffshoreFortRoss.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreFortRoss/data_catalog_OffshoreFortRoss.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Golden, N.E., Hartwell, S.R., Erdey, M.D., Greene, H.G., Cochrane, G.R., Kvitek, R.G., Manson, M.W., Endris, C.A., Dieter, B.E., Watt, J.T., Krigsman, L.M., Sliter, R.W., Lowe, E.N., and Chin, J.L. (S.Y. Johnson and S.A. Cochran, eds.), 2015, California State Waters Map Series--Offshore of Fort Ross, California: U.S. Geological Survey Open-File Report 2015–1211, pamphlet 37 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20151211. The bathymetry map of the Offshore of Fort Ross map area, California, was generated from bathymetry data collected by California State University, Monterey Bay (CSUMB), and by Fugro Pelagos. Mapping was completed between 2007 and 2010, using a combination of 200-kHz and 400-kHz Reson 7125, and 244-kHz Reson 8101 multibeam echosounders, as well as 468-kHz SEA SWATHPlus interferometric system. These mapping missions combined to collect bathymetry from about the 10-m isobath to beyond the 3-nautical-mile limit of California's State Waters. NOTE: the horizontal datum of the bathymetry data (NAD83) differs from the horizontal datum of other layers in this SIM (WGS84). These data are not intended for navigational purposes.

This part of DS 781 presents data for the bathymetric contours for several seafloor maps of the Offshore of Fort Ross map area, California. The vector data file is included in "Contours_OffshoreFortRoss.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreFortRoss/data_catalog_OffshoreFortRoss.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Golden, N.E., Hartwell, S.R., Erdey, M.D., Greene, H.G., Cochrane, G.R., Kvitek, R.G., Manson, M.W., Endris, C.A., Dieter, B.E., Watt, J.T., Krigsman, L.M., Sliter, R.W., Lowe, E.N., and Chin, J.L. (S.Y. Johnson and S.A. Cochran, eds.), 2015, California State Waters Map Series--Offshore of Fort Ross, California: U.S. Geological Survey Open-File Report 2015–1211, pamphlet 37 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20151211. 10-m interval contours of the Offshore of Fort Ross map area, California, were generated from bathymetry data collected by California State University, Monterey Bay (CSUMB) and by Fugro Pelagos. Mapping was completed between 2007 and 2010, using a combination of 200-kHz and 400-kHz Reson 7125, and 244-kHz Reson 8101 multibeam echosounders, as well as 468-kHz SEA SWATHPlus interferometric system. These mapping missions combined to collect bathymetry from about the 10-m isobath to beyond the 3-nautical-mile limit of California State Waters. Bathymetric contours at 10-m intervals were generated from a bathymetric surface model. The most continuous contour segments were preserved while smaller segments and isolated island polygons were excluded from the final output. Contours were smoothed via a polynomial approximation with exponential kernel (PAEK) algorithm using a tolerance value of 60 m. The contours were then clipped to the boundary of the map area. These data are not intended for navigational purposes.

This part of DS 781 presents data for the acoustic-backscatter map of the Offshore of Half Moon Bay map area, California. Backscatter data are provided as two separate grids depending on mapping system (Reson 7125 and Reson 8101). The raster data file is included in "BackscatterA_8101_OffshoreHalfMoonBay.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreHalfMoonBay/data_catalog_OffshoreHalfMoonBay.html. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Greene, H.G., Johnson, S.Y., Golden, N.E., Hartwell, S.R., Dieter, B.E., Manson, M.W., Sliter, R.W., Ross, S.L., Watt, J.T., Endris, C.A., Kvitek, R.G., Phillips, E.L., Erdey, M.D., Chin, J.L., and Bretz, C.K. (G.R. Cochrane and S.A. Cochran, eds.), 2014, California State Waters Map Series—Offshore of Half Moon Bay, California: U.S. Geological Survey Open-File Report 2014–1214, pamphlet 37 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20141214. The acoustic-backscatter map of the Offshore of Half Moon Bay, California, map area was generated from backscatter data collected by Fugro Pelagos and by California State University, Monterey Bay (CSUMB). Mapping was completed in 2006 and 2007, using a combination of 400-kHz Reson 7125 and 244-kHz Reson 8101 multibeam echosounders. Within the final imagery, brighter tones indicate higher backscatter intensity, and darker tones indicate lower backscatter intensity. The intensity represents a complex interaction between the acoustic pulse and the seafloor, as well as characteristics within the shallow subsurface, providing a general indication of seafloor texture and composition. Backscatter intensity depends on the acoustic source level; the frequency used to image the seafloor; the grazing angle; the composition and character of the seafloor, including grain size, water content, bulk density, and seafloor roughness; and some biological cover. Harder and rougher bottom types such as rocky outcrops or coarse sediment typically return stronger intensities (high backscatter, lighter tones), whereas softer bottom types such as fine sediment return weaker intensities (low backscatter, darker tones).

This part of DS 781 presents data for the acoustic-backscatter map of the Offshore of Half Moon Bay map area, California. Backscatter data are provided as two separate grids depending on mapping system (Reson 7125 and Reson 8101). The raster data file is included in "BackscatterB_7125_OffshoreHalfMoonBay.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreHalfMoonBay/data_catalog_OffshoreHalfMoonBay.html. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Greene, H.G., Johnson, S.Y., Golden, N.E., Hartwell, S.R., Dieter, B.E., Manson, M.W., Sliter, R.W., Ross, S.L., Watt, J.T., Endris, C.A., Kvitek, R.G., Phillips, E.L., Erdey, M.D., Chin, J.L., and Bretz, C.K. (G.R. Cochrane and S.A. Cochran, eds.), 2014, California State Waters Map Series—Offshore of Half Moon Bay, California: U.S. Geological Survey Open-File Report 2014–1214, pamphlet 37 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20141214. The acoustic-backscatter map of the Offshore of Half Moon Bay, California, map area was generated from backscatter data collected by Fugro Pelagos and by California State University, Monterey Bay (CSUMB). Mapping was completed in 2006 and 2007, using a combination of 400-kHz Reson 7125 and 244-kHz Reson 8101 multibeam echosounders. Within the final imagery, brighter tones indicate higher backscatter intensity, and darker tones indicate lower backscatter intensity. The intensity represents a complex interaction between the acoustic pulse and the seafloor, as well as characteristics within the shallow subsurface, providing a general indication of seafloor texture and composition. Backscatter intensity depends on the acoustic source level; the frequency used to image the seafloor; the grazing angle; the composition and character of the seafloor, including grain size, water content, bulk density, and seafloor roughness; and some biological cover. Harder and rougher bottom types such as rocky outcrops or coarse sediment typically return stronger intensities (high backscatter, lighter tones), whereas softer bottom types such as fine sediment return weaker intensities (low backscatter, darker tones).

This part of DS 781 presents data for the hillshaded bathymetry map of the Offshore Half Moon Bay map area, California. The raster data file is included in "BathymetryHS_OffshoreHalfMoonBay.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreHalfMoonBay/data_catalog_OffshoreHalfMoonBay.html. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Greene, H.G., Johnson, S.Y., Golden, N.E., Hartwell, S.R., Dieter, B.E., Manson, M.W., Sliter, R.W., Ross, S.L., Watt, J.T., Endris, C.A., Kvitek, R.G., Phillips, E.L., Erdey, M.D., Chin, J.L., and Bretz, C.K. (G.R. Cochrane and S.A. Cochran, eds.), 2014, California State Waters Map Series—Offshore of Half Moon Bay, California: U.S. Geological Survey Open-File Report 2014–1214, pamphlet 37 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20141214. The shaded-relief bathymetry map of Offshore Half Moon Bay, California, was generated from bathymetry data collected by Fugro Pelagos, and by California State University, Monterey Bay (CSUMB). Mapping was completed in 2006 and 2007, using a combination of 400-kHz Reson 7125 and 244-kHz Reson 8101 multibeam echosounders. These mapping missions combined to collect bathymetry from about the 10-m isobath to beyond the 3-nautical-mile limit of California's State Waters.

This part of DS 781 presents data for the bathymetry map of the Offshore Half Moon Bay, California. The raster data file is included in "Bathymetry_OffshoreHalfMoonBay.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreHalfMoonBay/data_catalog_OffshoreHalfMoonBay.html. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Greene, H.G., Johnson, S.Y., Golden, N.E., Hartwell, S.R., Dieter, B.E., Manson, M.W., Sliter, R.W., Ross, S.L., Watt, J.T., Endris, C.A., Kvitek, R.G., Phillips, E.L., Erdey, M.D., Chin, J.L., and Bretz, C.K. (G.R. Cochrane and S.A. Cochran, eds.), 2014, California State Waters Map Series—Offshore of Half Moon Bay, California: U.S. Geological Survey Open-File Report 2014–1214, pamphlet 37 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20141214. The bathymetry map of the Offshore Half Moon Bay, California, map area was generated from bathymetry data collected by Fugro Pelagos, and by California State University, Monterey Bay (CSUMB). Mapping was completed in 2006 and 2007, using a combination of 400-kHz Reson 7125 and 244-kHz Reson 8101 multibeam echosounders. These mapping missions combined to collect bathymetry from about the 10-m isobath to beyond the 3-nautical-mile limit of California's State Waters. These data are not intended for navigational purposes. NOTE: the horizontal datum of the bathymetry data (NAD83) differs from the horizontal datum of other layers in this SIM (WGS84).

This part of DS 781 presents data for the bathymetric contours for several seafloor maps of the Offshore of Half Moon map area, California. The vector data file is included in "Contours_OffshoreHalfMoonBay.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreHalfMoonBay/data_catalog_OffshoreHalfMoonBay.html. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Greene, H.G., Johnson, S.Y., Golden, N.E., Hartwell, S.R., Dieter, B.E., Manson, M.W., Sliter, R.W., Ross, S.L., Watt, J.T., Endris, C.A., Kvitek, R.G., Phillips, E.L., Erdey, M.D., Chin, J.L., and Bretz, C.K. (G.R. Cochrane and S.A. Cochran, eds.), 2014, California State Waters Map Series—Offshore of Half Moon Bay, California: U.S. Geological Survey Open-File Report 2014–1214, pamphlet 37 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20141214. 10-m interval contours of the Offshore of Half Moon Bay map area, California, were generated from bathymetry data collected by Fugro Pelagos and by California State University, Monterey Bay, Seafloor Mapping Lab (CSUMB). Mapping was completed in 2006 and 2007, using a combination of 400-kHz Reson 7125 and 244-kHz Reson 8101 multibeam echosounders. These mapping missions combined to collect bathymetry from about the 10-m isobath to beyond the 3-nautical-mile limit of California's State Waters. Bathymetric contours at 10-m intervals were generated from the merged 2-m bathymetric surface. The most continuous contour segments were preserved while smaller segments and isolated island polygons were excluded from the final output. Contours were smoothed via a polynomial approximation with exponential kernel (PAEK) algorithm using a tolerance value of 60 m. The contours were then clipped to the boundary of the map area. These data are not intended for navigational purposes.

This part of DS 781 presents the seafloor-character map of the Offshore of Half Moon Bay map area, California. The raster data file is included in "SeafloorCharacter_OffshoreHalfMoonBay.zip", which is accessible from https://pubs.usgs.gov/ds/781/OffshoreHalfMoonBay/data_catalog_OffshoreHalfMoonBay.html. This raster-format seafloor-character map shows four substrate classes of Offshore of Half Moon Bay, California. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Greene, H.G., Johnson, S.Y., Golden, N.E., Hartwell, S.R., Dieter, B.E., Manson, M.W., Sliter, R.W., Ross, S.L., Watt, J.T., Endris, C.A., Kvitek, R.G., Phillips, E.L., Erdey, M.D., Chin, J.L., and Bretz, C.K. (G.R. Cochrane and S.A. Cochran, eds.), 2014, California State Waters Map Series—Offshore of Half Moon Bay, California: U.S. Geological Survey Open-File Report 2014–1214, pamphlet 37 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20141214. This raster-format seafloor-character map shows four substrate classes in the Offshore of Half Moon Bay map area. The substrate classes mapped in this area have been further divided into the following California Marine Life Protection Act depth zones and slope classes: Depth Zone 2 (intertidal to 30 m), Depth Zone 3 (30 to 100 m), and Slope Class 1 (0 degrees - 5 degrees). Depth Zone 1 (intertidal), Depth Zones 4-5 (greater than 100 m), and Slopes Classes 2-4 (greater than 5 degrees) are not present in the region covered by this block. The map is created using a supervised classification method described by Cochrane (2008). References Cited: California Department of Fish and Game, 2008, California Marine Life Protection Act master plan for marine protected areas; Revised draft: California Department of Fish and Game, accessed April 5 2011, at http://www.dfg.ca.gov/mlpa/masterplan.asp. Cochrane, G.R., 2008, Video-supervised classification of sonar data for mapping seafloor habitat, in Reynolds, J.R., and Greene, H.G., eds., Marine habitat mapping technology for Alaska: Fairbanks, University of Alaska, Alaska Sea Grant College Program, p. 185-194, accessed April 5, 2011, at http://doc.nprb.org/web/research/research%20pubs/615_habitat_mapping_workshop/Individual%20Chapters%20High-Res/Ch13%20Cochrane.pdf. Sappington, J.M., Longshore, K.M., and Thompson, D.B., 2007, Quantifying landscape ruggedness for animal habitat analysis--A case study using bighorn sheep in the Mojave Desert: Journal of Wildlife Management, v. 71, p. 1419-1426.

This part of DS 781 presents data for the bathymetric contours for several seafloor maps of the Offshore of Pacifica map area, California. The vector data file is included in "Contours_OffshorePacifica.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshorePacifica/data_catalog_OffshorePacifica.html. These data accompany the pamphlet and map sheets of Edwards, B.D., Phillips, E.L., Dartnell, P., Greene, H.G., Bretz, C.K., Kvitek, R.G., Hartwell, S.R., Johnson, S.Y., Cochrane, G.R., Dieter, B.E., Sliter, R.W., Ross, S.L., Golden, N.E., Watt, J.T., Chin, J.L., Erdey, M.D., Krigsman, L.M., Manson, M.W., and Endris, C.A. (S.A. Cochran and B.D. Edwards, eds.), 2014, California State Waters Map Series—Offshore of Pacifica, California: U.S. Geological Survey Open-File Report 2014–1260, pamphlet 38 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20141260. 10-m interval contours of the Offshore of Pacifica map area, California, were generated from bathymetry data collected by Fugro Pelagos and by California State University, Monterey Bay, Seafloor Mapping Lab (CSUMB). Mapping was completed between 2005 and 2007, using a combination of 400-kHz Reson 7125 and 244-kHz Reson 8101 multibeam echosounders. These mapping missions combined to collect bathymetry from about the 10-m isobath to beyond the 3-nautical-mile limit of California's State Waters. Bathymetric contours at 10-m intervals were generated from the merged 2-m bathymetric surface. The most continuous contour segments were preserved while smaller segments and isolated island polygons were excluded from the final output. Contours were smoothed via a polynomial approximation with exponential kernel (PAEK) algorithm using a tolerance value of 60 m. The contours were then clipped to the boundary of the map area. These data are not intended for navigational purposes.

This part of DS 781 presents data for the acoustic-backscatter map of the Offshore of Salt Point map area, California. Backscatter data are provided as separate grids depending on mapping system or processing method. The raster data file is included in "Backscatter8101_SaltPoint.zip", which are accessible from https://pubs.usgs.gov/ds/781/OffshoreSaltPoint/data_catalog_OffshoreSaltPoint.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Golden, N.E., Hartwell, S.R., Erdey, M.D., Greene, H.G., Cochrane, G.R., Kvitek, R.G., Manson, M.W., Endris, C.A., Dieter, B.E., Watt, J.T., Krigsman, L.M., Sliter, R.W., Lowe, E.N., and Chin, J.L. (S.Y. Johnson and S.A. Cochran, eds.), 2015, California State Waters Map Series—Offshore of Salt Point, California: U.S. Geological Survey Open-File Report 2015–1098, pamphlet 37 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20151098. The acoustic-backscatter map of the Offshore of Salt Point map area, California, was generated from backscatter data collected by California State University, Monterey Bay (CSUMB), and by Fugro Pelagos. Mapping was completed between 2007 and 2010, using a combination of 200-kHz and 400-kHz Reson 7125, and 244-kHz Reson 8101 multibeam echosounders, as well as 468-kHz SEA SWATHPlus interferometric system. These mapping missions combined to collect backscatter data from about the 10-m isobath to beyond the 3-nautical-mile limit of California State Waters. Within the acoustic-backscatter imagery, brighter tones indicate higher backscatter intensity, and darker tones indicate lower backscatter intensity. The intensity represents a complex interaction between the acoustic pulse and the seafloor, as well as characteristics within the shallow subsurface, providing a general indication of seafloor texture and composition. Backscatter intensity depends on the acoustic source level; the frequency used to image the seafloor; the grazing angle; the composition and character of the seafloor, including grain size, water content, bulk density, and seafloor roughness; and some biological cover. Harder and rougher bottom types such as rocky outcrops or coarse sediment typically return stronger intensities (high backscatter, lighter tones), whereas softer bottom types such as fine sediment return weaker intensities (low backscatter, darker tones). These data are not intended for navigational purposes.

This part of DS 781 presents data for the acoustic-backscatter map of the Offshore of Salt Point map area, California. Backscatter data are provided as separate grids depending on mapping system or processing method. The raster data files are included in "BackscatterSwath_SaltPoint.zip", which are accessible from https://pubs.usgs.gov/ds/781/OffshoreSaltPoint/data_catalog_OffshoreSaltPoint.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Golden, N.E., Hartwell, S.R., Erdey, M.D., Greene, H.G., Cochrane, G.R., Kvitek, R.G., Manson, M.W., Endris, C.A., Dieter, B.E., Watt, J.T., Krigsman, L.M., Sliter, R.W., Lowe, E.N., and Chin, J.L. (S.Y. Johnson and S.A. Cochran, eds.), 2015, California State Waters Map Series—Offshore of Salt Point, California: U.S. Geological Survey Open-File Report 2015–1098, pamphlet 37 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20151098. The acoustic-backscatter map of the Offshore of Salt Point map area, California, was generated from backscatter data collected by California State University, Monterey Bay (CSUMB), and by Fugro Pelagos. Mapping was completed between 2007 and 2010, using a combination of 200-kHz and 400-kHz Reson 7125, and 244-kHz Reson 8101 multibeam echosounders, as well as 468-kHz SEA SWATHPlus interferometric system. These mapping missions combined to collect backscatter data from about the 10-m isobath to beyond the 3-nautical-mile limit of California State Waters. Within the acoustic-backscatter imagery, brighter tones indicate higher backscatter intensity, and darker tones indicate lower backscatter intensity. The intensity represents a complex interaction between the acoustic pulse and the seafloor, as well as characteristics within the shallow subsurface, providing a general indication of seafloor texture and composition. Backscatter intensity depends on the acoustic source level; the frequency used to image the seafloor; the grazing angle; the composition and character of the seafloor, including grain size, water content, bulk density, and seafloor roughness; and some biological cover. Harder and rougher bottom types such as rocky outcrops or coarse sediment typically return stronger intensities (high backscatter, lighter tones), whereas softer bottom types such as fine sediment return weaker intensities (low backscatter, darker tones). These data are not intended for navigational purposes.

This part of DS 781 presents data for the acoustic-backscatter map of the Offshore of Salt Point map area, California. Backscatter data are provided as separate grids depending on mapping system or processing method. The raster data files are included in "Backscatter7125_SaltPoint.zip", which are accessible from https://pubs.usgs.gov/ds/781/OffshoreSaltPoint/data_catalog_OffshoreSaltPoint.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Golden, N.E., Hartwell, S.R., Erdey, M.D., Greene, H.G., Cochrane, G.R., Kvitek, R.G., Manson, M.W., Endris, C.A., Dieter, B.E., Watt, J.T., Krigsman, L.M., Sliter, R.W., Lowe, E.N., and Chin, J.L. (S.Y. Johnson and S.A. Cochran, eds.), 2015, California State Waters Map Series—Offshore of Salt Point, California: U.S. Geological Survey Open-File Report 2015–1098, pamphlet 37 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20151098. The acoustic-backscatter map of the Offshore of Salt Point map area, California, was generated from backscatter data collected by California State University, Monterey Bay (CSUMB), and by Fugro Pelagos. Mapping was completed between 2007 and 2010, using a combination of 200-kHz and 400-kHz Reson 7125, and 244-kHz Reson 8101 multibeam echosounders, as well as 468-kHz SEA SWATHPlus interferometric system. These mapping missions combined to collect backscatter data from about the 10-m isobath to beyond the 3-nautical-mile limit of California State Waters. Within the acoustic-backscatter imagery, brighter tones indicate higher backscatter intensity, and darker tones indicate lower backscatter intensity. The intensity represents a complex interaction between the acoustic pulse and the seafloor, as well as characteristics within the shallow subsurface, providing a general indication of seafloor texture and composition. Backscatter intensity depends on the acoustic source level; the frequency used to image the seafloor; the grazing angle; the composition and character of the seafloor, including grain size, water content, bulk density, and seafloor roughness; and some biological cover. Harder and rougher bottom types such as rocky outcrops or coarse sediment typically return stronger intensities (high backscatter, lighter tones), whereas softer bottom types such as fine sediment return weaker intensities (low backscatter, darker tones). These data are not intended for navigational purposes.

This part of DS 781 presents data for the shaded-relief bathymetry map of the Offshore of Salt Point map area, California. The raster data file is included in "BathymetryHS_OffshoreSaltPoint.zip", which is accessible from https://pubs.usgs.gov/ds/781/OffshoreSaltPoint/data_catalog_OffshoreSaltPoint.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Golden, N.E., Hartwell, S.R., Erdey, M.D., Greene, H.G., Cochrane, G.R., Kvitek, R.G., Manson, M.W., Endris, C.A., Dieter, B.E., Watt, J.T., Krigsman, L.M., Sliter, R.W., Lowe, E.N., and Chin, J.L. (S.Y. Johnson and S.A. Cochran, eds.), 2015, California State Waters Map Series—Offshore of Salt Point, California: U.S. Geological Survey Open-File Report 2015–1098, pamphlet 37 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20151098. The shaded-relief bathymetry map of the Offshore of Salt Point Map Area, California, were generated from bathymetry data collected by California State University, Monterey Bay (CSUMB), and by Fugro Pelagos. Mapping was completed between 2007 and 2010, using a combination of 200-kHz and 400-kHz Reson 7125, and 244-kHz Reson 8101 multibeam echosounders, as well as 468-kHz SEA SWATHPlus interferometric system. These mapping missions combined to collect bathymetry from about the 10-m isobath to beyond the 3-nautical-mile limit of California's State Waters.

This part of DS 781 presents data for the bathymetry map of the Offshore of Salt Point map area, California. The raster data file is included in "Bathymetry_OffshoreSaltPoint.zip", which is accessible from https://pubs.usgs.gov/ds/781/OffshoreSaltPoint/data_catalog_OffshoreSaltPoint.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Golden, N.E., Hartwell, S.R., Erdey, M.D., Greene, H.G., Cochrane, G.R., Kvitek, R.G., Manson, M.W., Endris, C.A., Dieter, B.E., Watt, J.T., Krigsman, L.M., Sliter, R.W., Lowe, E.N., and Chin, J.L. (S.Y. Johnson and S.A. Cochran, eds.), 2015, California State Waters Map Series—Offshore of Salt Point, California: U.S. Geological Survey Open-File Report 2015–1098, pamphlet 37 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20151098. The bathymetry map of the Offshore of Salt Point map area, California, was generated from bathymetry data collected by California State University, Monterey Bay (CSUMB), and by Fugro Pelagos. Mapping was completed between 2007 and 2010, using a combination of 200-kHz and 400-kHz Reson 7125, and 244-kHz Reson 8101 multibeam echosounders, as well as 468-kHz SEA SWATHPlus interferometric system. These mapping missions combined to collect bathymetry from about the 10-m isobath to beyond the 3-nautical-mile limit of California's State Waters. NOTE: the horizontal datum of the bathymetry data (NAD83) differs from the horizontal datum of other layers in this DS (WGS84). These data are not intended for navigational purposes.

This part of DS 781 presents data for the bathymetric contours for several seafloor maps of the Offshore of Salt Point map area, California. The vector data file is included in "Contours_OffshoreSaltPoint.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreSaltPoint/data_catalog_OffshoreSaltPoint.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Golden, N.E., Hartwell, S.R., Erdey, M.D., Greene, H.G., Cochrane, G.R., Kvitek, R.G., Manson, M.W., Endris, C.A., Dieter, B.E., Watt, J.T., Krigsman, L.M., Sliter, R.W., Lowe, E.N., and Chin, J.L. (S.Y. Johnson and S.A. Cochran, eds.), 2015, California State Waters Map Series—Offshore of Salt Point, California: U.S. Geological Survey Open-File Report 2015–1098, pamphlet 37 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20151098. 10-m interval contours of the Offshore of SaltPoint map area, California, were generated from bathymetry data collected by California State University, Monterey Bay (CSUMB) and by Fugro Pelagos. Mapping was completed between 2007 and 2010, using a combination of 200-kHz and 400-kHz Reson 7125, and 244-kHz Reson 8101 multibeam echosounders, as well as 468-kHz SEA SWATHPlus interferometric system. These mapping missions combined to collect bathymetry from about the 10-m isobath to beyond the 3-nautical-mile limit of California State Waters. Bathymetric contours at 10-m intervals were generated from a bathymetric surface model. The most continuous contour segments were preserved while smaller segments and isolated island polygons were excluded from the final output. Contours were smoothed via a polynomial approximation with exponential kernel (PAEK) algorithm using a tolerance value of 60 m. The contours were then clipped to the boundary of the map area. These data are not intended for navigational purposes.

This part of DS 781 presents the seafloor-character map Offshore of Salt Point, California (raster data file is included in "SeafloorCharacter_SaltPoint.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreSaltPoint/data_catalog_OffshoreSaltPoint.html). These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Golden, N.E., Hartwell, S.R., Erdey, M.D., Greene, H.G., Cochrane, G.R., Kvitek, R.G., Manson, M.W., Endris, C.A., Dieter, B.E., Watt, J.T., Krigsman, L.M., Sliter, R.W., Lowe, E.N., and Chin, J.L. (S.Y. Johnson and S.A. Cochran, eds.), 2015, California State Waters Map Series—Offshore of Salt Point, California: U.S. Geological Survey Open-File Report 2015–1098, pamphlet 37 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20151098. This raster-format seafloor-character map shows four substrate classes offshore of Salt Point, California. The substrate classes mapped in this area have been further divided into the following California Marine Life Protection Act depth zones and slope classes: Depth Zone 2 (intertidal to 30 m), Depth Zone 3 (30 to 100 m), Slope Class 1 (0 degrees - 5 degrees), and Slope Class 2 (5 degrees - 30 degrees). Depth Zone 1 (intertidal), Depth Zone 4 (100 to 200 m), Depth Zone 5 (greater than 200 m), and Slopes Classes 3-4 (greater than 30 degrees) are not present in the region covered by this block. The map is created using a supervised classification method described by Cochrane (2008). References Cited: California Department of Fish and Game, 2008, California Marine Life Protection Act master plan for marine protected areas; Revised draft: California Department of Fish and Game, accessed April 5 2011, at http://www.dfg.ca.gov/mlpa/masterplan.asp. Cochrane, G.R., 2008, Video-supervised classification of sonar data for mapping seafloor habitat, in Reynolds, J.R., and Greene, H.G., eds., Marine habitat mapping technology for Alaska: Fairbanks, University of Alaska, Alaska Sea Grant College Program, p. 185-194, accessed April 5, 2011, at http://doc.nprb.org/web/research/research%20pubs/615_habitat_mapping_workshop/Individual%20Chapters%20High-Res/Ch13%20Cochrane.pdf. Sappington, J.M., Longshore, K.M., and Thompson, D.B., 2007, Quantifying landscape ruggedness for animal habitat analysis--A case study using bighorn sheep in the Mojave Desert: Journal of Wildlife Management, v. 71, p. 1419-1426.

This part of DS 781 presents data for the bathymetry map of the Offshore of San Francisco, California, map area. The raster data file is included in "Bathymetry_OffshoreSanFrancisco.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreSanFrancisco/data_catalog_OffshoreSanFrancisco.html. These data accompany the pamphlet and map sheets of Cochrane, G.R., Johnson, S.Y., Dartnell, P., Greene, H.G., Erdey, M.D., Golden, N.E., Hartwell, S.R., Endris, C.A., Manson, M.W., Sliter, R.W., Kvitek, R.G., Watt, J.T., Ross, S.L., and Bruns, T.R. (G.R. Cochrane and S.A. Cochran, eds.), 2015, California State Waters Map Series—Offshore of San Francisco, California (ver. 1.1, June 2015): U.S. Geological Survey Open-File Report 2015–1068, pamphlet 39 p., 10 sheets, scale 1:24,000, https://dx.doi.org/10.3133/ofr20151068. The bathymetry map of Offshore of San Francisco, California, was generated from bathymetry data collected by Fugro Pelagos, and by California State University, Monterey Bay (CSUMB). Mapping was completed between 2004 and 2008, using a combination of 400-kHz Reson 7125 and 244-kHz Reson 8101 multibeam echosounders. These mapping missions combined to collect bathymetry (sheets 1, 2) from about the 10-m isobath to beyond the 3-nautical-mile limit of California's State Waters. A large portion of this map area was re-mapped in 2009, however the older bathymetry data were used in this map due to co-registered, acoustic backscatter data. NOTE: the horizontal datum of the bathymetry data (NAD83) differs from the horizontal datum of other layers in this SIM (WGS84). Some bathymetry grids within this map were projected horizontally from WGS84 to NAD83 using ESRI tools to be more consistent with the vertical reference of the North American Vertical Datum of 1988 (NAVD88). These data are not intended for navigational purposes.

This part of DS 781 presents data for the geologic and geomorphic map of the Offshore of San Francisco map area, California. The polygon shapefile is included in "Geology_OffshoreSanFrancisco.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreSanFrancisco/data_catalog_OffshoreSanFrancisco.html. These data accompany the pamphlet and map sheets of Cochrane, G.R., Johnson, S.Y., Dartnell, P., Greene, H.G., Erdey, M.D., Golden, N.E., Hartwell, S.R., Endris, C.A., Manson, M.W., Sliter, R.W., Kvitek, R.G., Watt, J.T., Ross, S.L., and Bruns, T.R. (G.R. Cochrane and S.A. Cochran, eds.), 2015, California State Waters Map Series—Offshore of San Francisco, California (ver. 1.1, June 2015): U.S. Geological Survey Open-File Report 2015–1068, pamphlet 39 p., 10 sheets, scale 1:24,000, https://dx.doi.org/10.3133/ofr20151068. Marine geology and geomorphology was mapped in the Offshore of San Francisco map area, California, from approximate Mean High Water (MHW) to the 3-nautical-mile limit of California's State Waters. Offshore geologic units were delineated on the basis of integrated analyses of adjacent onshore geology with multibeam bathymetry and backscatter imagery, seafloor-sediment and rock samples, digital camera and video imagery, and high-resolution seismic-reflection profiles.

This part of DS 781 presents the seafloor-character map (see sheet 5) Offshore of San Francisco, California (raster data file is included in "SFC_OffshoreSanFrancisco.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreSanFrancisco/data_catalog_OffshoreSanFrancisco.html). These data accompany the pamphlet and map sheets of Cochrane, G.R., Johnson, S.Y., Dartnell, P., Greene, H.G., Erdey, M.D., Golden, N.E., Hartwell, S.R., Endris, C.A., Manson, M.W., Sliter, R.W., Kvitek, R.G., Watt, J.T., Ross, S.L., and Bruns, T.R. (G.R. Cochrane and S.A. Cochran, eds.), 2015, California State Waters Map Series—Offshore of San Francisco, California (ver. 1.1, June 2015): U.S. Geological Survey Open-File Report 2015–1068, pamphlet 39 p., 10 sheets, scale 1:24,000, https://dx.doi.org/10.3133/ofr20151068. This raster-format seafloor-character map shows six substrate classes of Offshore of San Francisco, California. The substrate classes mapped in this area have been further divided into the following California Marine Life Protection Act depth zones and slope classes: Depth Zone 2 (intertidal to 30 m), Depth Zone 3 (30 to 100 m), Depth Zone 4 (100 to 200 m), Slope Class 1 (0 degrees - 5 degrees), and Slope Class 2 (5 degrees - 30 degrees). Depth Zone 1 (intertidal), Depth Zone 5 (greater than 200 m), and Slopes Classes 3-4 (greater than 30 degrees) are not present in the region covered by this block. The map is created using a supervised classification method described by Cochrane (2008). References Cited: California Department of Fish and Game, 2008, California Marine Life Protection Act master plan for marine protected areas; Revised draft: California Department of Fish and Game, accessed April 5 2011, at http://www.dfg.ca.gov/mlpa/masterplan.asp. Cochrane, G.R., 2008, Video-supervised classification of sonar data for mapping seafloor habitat, in Reynolds, J.R., and Greene, H.G., eds., Marine habitat mapping technology for Alaska: Fairbanks, University of Alaska, Alaska Sea Grant College Program, p. 185-194, accessed April 5, 2011, at http://doc.nprb.org/web/research/research%20pubs/615_habitat_mapping_workshop/Individual%20Chapters%20High-Res/Ch13%20Cochrane.pdf. Sappington, J.M., Longshore, K.M., and Thompson, D.B., 2007, Quantifying landscape ruggedness for animal habitat analysis--A case study using bighorn sheep in the Mojave Desert: Journal of Wildlife Management, v. 71, p. 1419-1426.

This part of SIM 3306 presents data for the acoustic-backscatter map of the Offshore of San Gregorio map area, California. Backscatter data are provided as two separate grids depending on mapping system (Reson 7125 and Reson 8101). The raster data file is included in "BackscatterA_8101_OffshoreSanGregorio.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreSanGregorio/data_catalog_OffshoreSanGregorio.html. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Greene, H.G., Watt, J.T., Golden, N.E., Endris, C.A., Phillips, E.L., Hartwell, S.R., Johnson, S.Y., Kvitek, R.G., Erdey, M.D., Bretz, C.K., Manson, M.W., Sliter, R.W., Ross, S.L., Dieter, B.E., and Chin, J.L. (G.R. Cochrane and S.A. Cochran, eds.), 2014, California State Waters Map Series—Offshore of San Gregorio, California: U.S. Geological Survey Scientific Investigations Map 3306, pamphlet 38 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/sim3306. The acoustic-backscatter map of the Offshore of San Gregorio, California, map area was generated from backscatter data collected by Fugro Pelagos and by California State University, Monterey Bay (CSUMB). Mapping was completed in 2006 and 2007, using a combination of 400-kHz Reson 7125 and 244-kHz Reson 8101 multibeam echosounders. Within the final imagery, brighter tones indicate higher backscatter intensity, and darker tones indicate lower backscatter intensity. The intensity represents a complex interaction between the acoustic pulse and the seafloor, as well as characteristics within the shallow subsurface, providing a general indication of seafloor texture and composition. Backscatter intensity depends on the acoustic source level; the frequency used to image the seafloor; the grazing angle; the composition and character of the seafloor, including grain size, water content, bulk density, and seafloor roughness; and some biological cover. Harder and rougher bottom types such as rocky outcrops or coarse sediment typically return stronger intensities (high backscatter, lighter tones), whereas softer bottom types such as fine sediment return weaker intensities (low backscatter, darker tones).

This part of SIM 3306 presents data for the acoustic-backscatter map of the Offshore of San Gregorio map area, California. Backscatter data are provided as two separate grids depending on mapping system (Reson 7125 and Reson 8101). The raster data file is included in "BackscatterB_7125_OffshoreSanGregorio.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreSanGregorio/data_catalog_OffshoreSanGregorio.html. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Greene, H.G., Watt, J.T., Golden, N.E., Endris, C.A., Phillips, E.L., Hartwell, S.R., Johnson, S.Y., Kvitek, R.G., Erdey, M.D., Bretz, C.K., Manson, M.W., Sliter, R.W., Ross, S.L., Dieter, B.E., and Chin, J.L. (G.R. Cochrane and S.A. Cochran, eds.), 2014, California State Waters Map Series—Offshore of San Gregorio, California: U.S. Geological Survey Scientific Investigations Map 3306, pamphlet 38 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/sim3306. The acoustic-backscatter map of the Offshore of San Gregorio, California, map area was generated from backscatter data collected by Fugro Pelagos and by California State University, Monterey Bay (CSUMB). Mapping was completed in 2006 and 2007, using a combination of 400-kHz Reson 7125 and 244-kHz Reson 8101 multibeam echosounders. Within the final imagery, brighter tones indicate higher backscatter intensity, and darker tones indicate lower backscatter intensity. The intensity represents a complex interaction between the acoustic pulse and the seafloor, as well as characteristics within the shallow subsurface, providing a general indication of seafloor texture and composition. Backscatter intensity depends on the acoustic source level; the frequency used to image the seafloor; the grazing angle; the composition and character of the seafloor, including grain size, water content, bulk density, and seafloor roughness; and some biological cover. Harder and rougher bottom types such as rocky outcrops or coarse sediment typically return stronger intensities (high backscatter, lighter tones), whereas softer bottom types such as fine sediment return weaker intensities (low backscatter, darker tones).

This part of SIM 3306 presents data for the shaded-relief bathymetry map of the Offshore of San Gregorio map area, California. The raster data file is included in "Bathymetry_OffshoreSanGregorio.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreSanGregorio/data_catalog_OffshoreSanGregorio.html. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Greene, H.G., Watt, J.T., Golden, N.E., Endris, C.A., Phillips, E.L., Hartwell, S.R., Johnson, S.Y., Kvitek, R.G., Erdey, M.D., Bretz, C.K., Manson, M.W., Sliter, R.W., Ross, S.L., Dieter, B.E., and Chin, J.L. (G.R. Cochrane and S.A. Cochran, eds.), 2014, California State Waters Map Series—Offshore of San Gregorio, California: U.S. Geological Survey Scientific Investigations Map 3306, pamphlet 38 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/sim3306. The shaded-relief bathymetry map of Offshore San Gregorio, California, was generated from bathymetry data collected by Fugro Pelagos and by California State University, Monterey Bay (CSUMB). Mapping was completed in 2006 and 2007, using a combination of 400-kHz Reson 7125 and 244-kHz Reson 8101 multibeam echosounders. These mapping missions combined to collect bathymetry (sheets 1, 2) from about the 10-m isobath to beyond the 3-nautical-mile limit of California's State Waters.

This part of SIM 3306 presents data for the bathymetry map of the Offshore of San Gregorio map area, California. The raster data file is included in "Bathymetry_OffshoreSanGregorio.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreSanGregorio/data_catalog_OffshoreSanGregorio.html. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Greene, H.G., Watt, J.T., Golden, N.E., Endris, C.A., Phillips, E.L., Hartwell, S.R., Johnson, S.Y., Kvitek, R.G., Erdey, M.D., Bretz, C.K., Manson, M.W., Sliter, R.W., Ross, S.L., Dieter, B.E., and Chin, J.L. (G.R. Cochrane and S.A. Cochran, eds.), 2014, California State Waters Map Series—Offshore of San Gregorio, California: U.S. Geological Survey Scientific Investigations Map 3306, pamphlet 38 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/sim3306. The bathymetry map of Offshore San Gregorio, California, was generated from bathymetry data collected by Fugro Pelagos and by California State University, Monterey Bay (CSUMB). Mapping was completed in 2006 and 2007, using a combination of 400-kHz Reson 7125 and 244-kHz Reson 8101 multibeam echosounders. These mapping missions combined to collect bathymetry from about the 10-m isobath to beyond the 3-nautical-mile limit of California's State Waters.

This part of SIM 3306 presents data for the bathymetric contours for several seafloor maps of the Offshore of San Gregorio map area, California. The vector data file is included in "Contours_OffshoreSanGregorio.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreSanGregorio/data_catalog_OffshoreSanGregorio.html. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Greene, H.G., Watt, J.T., Golden, N.E., Endris, C.A., Phillips, E.L., Hartwell, S.R., Johnson, S.Y., Kvitek, R.G., Erdey, M.D., Bretz, C.K., Manson, M.W., Sliter, R.W., Ross, S.L., Dieter, B.E., and Chin, J.L. (G.R. Cochrane and S.A. Cochran, eds.), 2014, California State Waters Map Series—Offshore of San Gregorio, California: U.S. Geological Survey Scientific Investigations Map 3306, pamphlet 38 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/sim3306. 10-m interval contours of the Offshore of San Gregorio map area, California, were generated from bathymetry data collected by Fugro Pelagos and by California State University, Monterey Bay, Seafloor Mapping Lab (CSUMB). Mapping was completed in 2006 and 2007, using a combination of 400-kHz Reson 7125 and 244-kHz Reson 8101 multibeam echosounders. These mapping missions combined to collect bathymetry from about the 10-m isobath to beyond the 3-nautical-mile limit of California's State Waters. Bathymetric contours at 10-m intervals were generated from the merged 2-m bathymetric surface. The most continuous contour segments were preserved while smaller segments and isolated island polygons were excluded from the final output. Contours were smoothed via a polynomial approximation with exponential kernel (PAEK) algorithm using a tolerance value of 60 m. The contours were then clipped to the boundary of the map area.

This part of SIM 3306 presents data for the seafloor-character map of the Offshore of San Gregorio map area, California. The raster data file is included in "SeafloorCharacter_OffshoreSanGregorio.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreSanGregorio/data_catalog_OffshoreSanGregorio.html. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Greene, H.G., Watt, J.T., Golden, N.E., Endris, C.A., Phillips, E.L., Hartwell, S.R., Johnson, S.Y., Kvitek, R.G., Erdey, M.D., Bretz, C.K., Manson, M.W., Sliter, R.W., Ross, S.L., Dieter, B.E., and Chin, J.L. (G.R. Cochrane and S.A. Cochran, eds.), 2014, California State Waters Map Series—Offshore of San Gregorio, California: U.S. Geological Survey Scientific Investigations Map 3306, pamphlet 38 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/sim3306. This raster-format seafloor-character map shows four substrate classes in the Offshore of San Gregorio map area. The substrate classes mapped in this area have been colored to indicate which of the following California Marine Life Protection Act depth zones and slope classes they belong: Depth Zone 2 (intertidal to 30 m), Depth Zone 3 (30 to 100 m), and Slope Class 1 (0 degrees - 5 degrees). Depth Zones 1 (intertidal) and 4 to 5 (greater than 100 m), as well as Slopes Classes 2 to 4 (greater than 5 degrees), are not present in this map area. The map is created using a supervised classification method described by Cochrane (2008). References Cited: California Department of Fish and Game, 2008, California Marine Life Protection Act master plan for marine protected areas--Revised draft: California Department of Fish and Game, accessed April 5 2011, at http://www.dfg.ca.gov/mlpa/masterplan.asp. Cochrane, G.R., 2008, Video-supervised classification of sonar data for mapping seafloor habitat, in Reynolds, J.R., and Greene, H.G., eds., Marine habitat mapping technology for Alaska: Fairbanks, University of Alaska, Alaska Sea Grant College Program, p. 185-194, accessed April 5, 2011, at http://doc.nprb.org/web/research/research%20pubs/615_habitat_mapping_workshop/Individual%20Chapters%20High-Res/Ch13%20Cochrane.pdf. Sappington, J.M., Longshore, K.M., and Thompson, D.B., 2007, Quantifying landscape ruggedness for animal habitat analysis--A case study using bighorn sheep in the Mojave Desert: Journal of Wildlife Management, v. 71, p. 1419-1426.

This part of USGS Data Series 935 (Cochrane, 2014) presents bathymetry and topography data for the Offshore of Tacoma, California, map area, a part of the Southern Salish Sea Habitat Map Series. The data for this map area are a combination of topography extracted from a pre-existing Digital Elevation Model (DEM) merged with bathymetry data that were collected by the National Oceanic and Atmospheric Administration (NOAA) using multibeam sonar systems. The merged data are available for download in a single zip file (BathyTopo_OffshoreTacoma.zip).

This part of USGS Data Series 935 (Cochrane, 2014) presents substrate, geomorphic, and biotope data in the Offshore of Tacoma, Washington, map area, a part of the Southern Salish Sea Habitat Map Series. Given the variable bathymetric resolution, the complex geologic history of the region, and the lack of acoustic backscatter data, automated and semi-automated classification schemes of classifying seafloor substrate and geoform were deemed to have very low accuracy. Instead, classification of these properties was performed manually following the Coastal and Marine Ecological Classification Standard (CMECS; Federal Geographic Data Committee, 2012) using observations from underwater video footage. The best overall predictors of biotic assemblage were used to generate the CMECS biotopes. However, the nature of the biological data gathered makes it difficult to define clear biotopes. It was difficult to see or identify many organisms in the underwater video, and with an average of only 3-4 taxa identified per sampling unit, it is hard to characterize biotic assemblages. Some biological clusters of taxa were identified statistically for multiple map areas, and within each area, some of these groupings were found at consistent depths and/or with predictable substrates. The maps are not fine-grained enough to capture the physical variation seen within one-minute video units. Depth zones in the biotope map are based on Dethier (1992).

This part of DS 781 presents the seafloor-character map Offshore of Fort Ross, California (raster data file is included in "SeafloorCharacter_OffshoreFortRoss.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreFortRoss/data_catalog_OffshoreFortRoss.html). These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Golden, N.E., Hartwell, S.R., Erdey, M.D., Greene, H.G., Cochrane, G.R., Kvitek, R.G., Manson, M.W., Endris, C.A., Dieter, B.E., Watt, J.T., Krigsman, L.M., Sliter, R.W., Lowe, E.N., and Chin, J.L. (S.Y. Johnson and S.A. Cochran, eds.), 2015, California State Waters Map Series--Offshore of Fort Ross, California: U.S. Geological Survey Open-File Report 2015–1211, pamphlet 37 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20151211. This raster-format seafloor-character map shows four substrate classes offshore of Fort Ross, California. The substrate classes mapped in this area have been further divided into the following California Marine Life Protection Act depth zones and slope classes: Depth Zone 2 (intertidal to 30 m), Depth Zone 3 (30 to 100 m), Slope Class 1 (0 degrees - 5 degrees), and Slope Class 2 (5 degrees - 30 degrees). Depth Zone 1 (intertidal), Depth Zone 4 (100 to 200 m), Depth Zone 5 (greater than 200 m), and Slopes Classes 3-4 (greater than 30 degrees) are not present in the region covered by this block. The map is created using a supervised classification method described by Cochrane (2008). References Cited: California Department of Fish and Game, 2008, California Marine Life Protection Act master plan for marine protected areas; Revised draft: California Department of Fish and Game, accessed April 5 2011, at http://www.dfg.ca.gov/mlpa/masterplan.asp. Cochrane, G.R., 2008, Video-supervised classification of sonar data for mapping seafloor habitat, in Reynolds, J.R., and Greene, H.G., eds., Marine habitat mapping technology for Alaska: Fairbanks, University of Alaska, Alaska Sea Grant College Program, p. 185-194, accessed April 5, 2011, at http://doc.nprb.org/web/research/research%20pubs/615_habitat_mapping_workshop/Individual%20Chapters%20High-Res/Ch13%20Cochrane.pdf. Sappington, J.M., Longshore, K.M., and Thompson, D.B., 2007, Quantifying landscape ruggedness for animal habitat analysis--A case study using bighorn sheep in the Mojave Desert: Journal of Wildlife Management, v. 71, p. 1419-1426.

This part of DS 781 presents data for the acoustic-backscatter map of the Offshore of Point Reyes map area, California. Backscatter data are provided as separate grids depending on mapping system or processing method. The raster data files are included in "BackscatterA_8101_PtReyes.zip", which are accessible from https://pubs.usgs.gov/ds/781/OffshorePointReyes/data_catalog_PointReyes.html. These data accompany the pamphlet and map sheets of Watt, J.T., Dartnell, P., Golden, N.E., Greene, H.G., Erdey, M.D., Cochrane, G.R., Johnson, S.Y., Hartwell, S.R., Kvitek, R.G., Manson, M.W., Endris, C.A., Dieter, B.E., Sliter, R.W., Krigsman, L.M., Lowe, E.N., and Chin, J.L. (J.T. Watt and S.A. Cochran, eds.), 2015, California State Waters Map Series—Offshore of Point Reyes, California: U.S. Geological Survey Open-File Report 2015–1114, pamphlet 39 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20151114. The acoustic-backscatter map of the Offshore of Point Reyes map area, California, was generated from backscatter data collected by California State University, Monterey Bay (CSUMB), and by Fugro Pelagos. Mapping was completed between 2007 and 2010, using a combination of 200-kHz and 400-kHz Reson 7125, and 244-kHz Reson 8101 multibeam echosounders, as well as 468-kHz SEA SWATHPlus interferometric system. These mapping missions combined to collect backscatter data from about the 10-m isobath to beyond the 3-nautical-mile limit of California's State Waters. Within the acoustic-backscatter imagery, brighter tones indicate higher backscatter intensity, and darker tones indicate lower backscatter intensity. The intensity represents a complex interaction between the acoustic pulse and the seafloor, as well as characteristics within the shallow subsurface, providing a general indication of seafloor texture and composition. Backscatter intensity depends on the acoustic source level; the frequency used to image the seafloor; the grazing angle; the composition and character of the seafloor, including grain size, water content, bulk density, and seafloor roughness; and some biological cover. Harder and rougher bottom types such as rocky outcrops or coarse sediment typically return stronger intensities (high backscatter, lighter tones), whereas softer bottom types such as fine sediment return weaker intensities (low backscatter, darker tones). NOTE: the horizontal datum of the backscatter data (NAD83) differs from the horizontal datum of other layers in this DS (WGS84). These data are not intended for navigational purposes.

This part of DS 781 presents data for the acoustic-backscatter map of the Offshore of Point Reyes map area, California. Backscatter data are provided as separate grids depending on mapping system or processing method. The raster data files are included in "BackscatterB_Swath_PtReyes.zip", which are accessible from https://pubs.usgs.gov/ds/781/OffshorePointReyes/data_catalog_PointReyes.html. These data accompany the pamphlet and map sheets of Watt, J.T., Dartnell, P., Golden, N.E., Greene, H.G., Erdey, M.D., Cochrane, G.R., Johnson, S.Y., Hartwell, S.R., Kvitek, R.G., Manson, M.W., Endris, C.A., Dieter, B.E., Sliter, R.W., Krigsman, L.M., Lowe, E.N., and Chin, J.L. (J.T. Watt and S.A. Cochran, eds.), 2015, California State Waters Map Series—Offshore of Point Reyes, California: U.S. Geological Survey Open-File Report 2015–1114, pamphlet 39 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20151114. The acoustic-backscatter map of the Offshore of Point Reyes map area, California, was generated from backscatter data collected by California State University, Monterey Bay (CSUMB), and by Fugro Pelagos. Mapping was completed between 2007 and 2010, using a combination of 200-kHz and 400-kHz Reson 7125, and 244-kHz Reson 8101 multibeam echosounders, as well as 468-kHz SEA SWATHPlus interferometric system. These mapping missions combined to collect backscatter data from about the 10-m isobath to beyond the 3-nautical-mile limit of California's State Waters. Within the acoustic-backscatter imagery, brighter tones indicate higher backscatter intensity, and darker tones indicate lower backscatter intensity. The intensity represents a complex interaction between the acoustic pulse and the seafloor, as well as characteristics within the shallow subsurface, providing a general indication of seafloor texture and composition. Backscatter intensity depends on the acoustic source level; the frequency used to image the seafloor; the grazing angle; the composition and character of the seafloor, including grain size, water content, bulk density, and seafloor roughness; and some biological cover. Harder and rougher bottom types such as rocky outcrops or coarse sediment typically return stronger intensities (high backscatter, lighter tones), whereas softer bottom types such as fine sediment return weaker intensities (low backscatter, darker tones). NOTE: the horizontal datum of the backscatter data (NAD83) differs from the horizontal datum of other layers in this DS (WGS84). These data are not intended for navigational purposes.

This part of DS 781 presents data for the acoustic-backscatter map of the Offshore of Point Reyes map area, California. Backscatter data are provided as separate grids depending on mapping system or processing method. The raster data files are included in "BackscatterB_Swath_PtReyes.zip", which are accessible from https://pubs.usgs.gov/ds/781/OffshorePointReyes/data_catalog_PointReyes.html. These data accompany the pamphlet and map sheets of Watt, J.T., Dartnell, P., Golden, N.E., Greene, H.G., Erdey, M.D., Cochrane, G.R., Johnson, S.Y., Hartwell, S.R., Kvitek, R.G., Manson, M.W., Endris, C.A., Dieter, B.E., Sliter, R.W., Krigsman, L.M., Lowe, E.N., and Chin, J.L. (J.T. Watt and S.A. Cochran, eds.), 2015, California State Waters Map Series—Offshore of Point Reyes, California: U.S. Geological Survey Open-File Report 2015–1114, pamphlet 39 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20151114. The acoustic-backscatter map of the Offshore of Point Reyes map area, California, was generated from backscatter data collected by California State University, Monterey Bay (CSUMB), and by Fugro Pelagos. Mapping was completed between 2007 and 2010, using a combination of 200-kHz and 400-kHz Reson 7125, and 244-kHz Reson 8101 multibeam echosounders, as well as 468-kHz SEA SWATHPlus interferometric system. These mapping missions combined to collect backscatter data from about the 10-m isobath to beyond the 3-nautical-mile limit of California's State Waters. Within the acoustic-backscatter imagery, brighter tones indicate higher backscatter intensity, and darker tones indicate lower backscatter intensity. The intensity represents a complex interaction between the acoustic pulse and the seafloor, as well as characteristics within the shallow subsurface, providing a general indication of seafloor texture and composition. Backscatter intensity depends on the acoustic source level; the frequency used to image the seafloor; the grazing angle; the composition and character of the seafloor, including grain size, water content, bulk density, and seafloor roughness; and some biological cover. Harder and rougher bottom types such as rocky outcrops or coarse sediment typically return stronger intensities (high backscatter, lighter tones), whereas softer bottom types such as fine sediment return weaker intensities (low backscatter, darker tones). NOTE: the horizontal datum of the backscatter data (NAD83) differs from the horizontal datum of other layers in this DS (WGS84). These data are not intended for navigational purposes.

This part of DS 781 presents data for the shaded-relief bathymetry map of the Offshore of Point Reyes map area, California. Raster data file is included in "BathymetryHS_PointReyes.zip," which is accessible from https://pubs.usgs.gov/ds/781/PointReyes/data_catalog_PointReyes.html. These data accompany the pamphlet and map sheets of Watt, J.T., Dartnell, P., Golden, N.E., Greene, H.G., Erdey, M.D., Cochrane, G.R., Johnson, S.Y., Hartwell, S.R., Kvitek, R.G., Manson, M.W., Endris, C.A., Dieter, B.E., Sliter, R.W., Krigsman, L.M., Lowe, E.N., and Chin, J.L. (J.T. Watt and S.A. Cochran, eds.), 2015, California State Waters Map Series—Offshore of Point Reyes, California: U.S. Geological Survey Open-File Report 2015–1114, pamphlet 39 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20151114. The shaded-relief bathymetry map of the Offshore of Point Reyes map area, California, was generated from bathymetry data collected by California State University, Monterey Bay (CSUMB), and by Fugro Pelagos. Mapping was completed between 2007 and 2010, using a combination of 200-kHz and 400-kHz Reson 7125, and 244-kHz Reson 8101 multibeam echosounders, as well as 468-kHz SEA SWATHPlus interferometric system. These mapping missions combined to collect bathymetry from about the 10-m isobath to beyond the 3-nautical-mile limit of California's State Waters. NOTE: the horizontal datum of the bathymetry data (NAD83) differs from the horizontal datum of other layers in this DS (WGS84). These data are not intended for navigational purposes.

This part of DS 781 presents data for the bathymetry and shaded-relief maps of the Offshore of Point Reyes map area, California. Raster data file is included in "Bathymetry_PointReyes.zip," which is accessible from https://pubs.usgs.gov/ds/781/PointReyes/data_catalog_PointReyes.html. These data accompany the pamphlet and map sheets of Watt, J.T., Dartnell, P., Golden, N.E., Greene, H.G., Erdey, M.D., Cochrane, G.R., Johnson, S.Y., Hartwell, S.R., Kvitek, R.G., Manson, M.W., Endris, C.A., Dieter, B.E., Sliter, R.W., Krigsman, L.M., Lowe, E.N., and Chin, J.L. (J.T. Watt and S.A. Cochran, eds.), 2015, California State Waters Map Series—Offshore of Point Reyes, California: U.S. Geological Survey Open-File Report 2015–1114, pamphlet 39 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20151114. The bathymetry map of the Offshore of Point Reyes map area, California, was generated from bathymetry data collected by California State University, Monterey Bay (CSUMB), and by Fugro Pelagos. Mapping was completed between 2007 and 2010, using a combination of 200-kHz and 400-kHz Reson 7125, and 244-kHz Reson 8101 multibeam echosounders, as well as 468-kHz SEA SWATHPlus interferometric system. These mapping missions combined to collect bathymetry from about the 10-m isobath to beyond the 3-nautical-mile limit of California's State Waters. NOTE: the horizontal datum of the bathymetry data (NAD83) differs from the horizontal datum of other layers in this DS (WGS84). These data are not intended for navigational purposes.

This part of DS 781 presents data for the bathymetric contours for several seafloor maps of the Offshore of Point Reyes map area, California. The vector data file is included in "Contours_PointReyes.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshorePointReyes/data_catalog_PointReyes.html. These data accompany the pamphlet and map sheets of Watt, J.T., Dartnell, P., Golden, N.E., Greene, H.G., Erdey, M.D., Cochrane, G.R., Johnson, S.Y., Hartwell, S.R., Kvitek, R.G., Manson, M.W., Endris, C.A., Dieter, B.E., Sliter, R.W., Krigsman, L.M., Lowe, E.N., and Chin, J.L. (J.T. Watt and S.A. Cochran, eds.), 2015, California State Waters Map Series—Offshore of Point Reyes, California: U.S. Geological Survey Open-File Report 2015–1114, pamphlet 39 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20151114. 10-m interval contours of the Offshore of Point Reyes map area, California, were generated from bathymetry data collected by California State University, Monterey Bay (CSUMB) and by Fugro Pelagos. Mapping was completed between 2007 and 2010, using a combination of 200-kHz and 400-kHz Reson 7125, and 244-kHz Reson 8101 multibeam echosounders, as well as 468-kHz SEA SWATHPlus interferometric system. These mapping missions combined to collect bathymetry from about the 10-m isobath to beyond the 3-nautical-mile limit of California's State Waters. Bathymetric contours at 10-m intervals were generated from a bathymetric surface model. The most continuous contour segments were preserved while smaller segments and isolated island polygons were excluded from the final output. Contours were smoothed via a polynomial approximation with exponential kernel (PAEK) algorithm using a tolerance value of 60 m. The contours were then clipped to the boundary of the map area. These data are not intended for navigational purposes.

This part of DS 781 presents the seafloor-character map Offshore of Point Reyes, California (raster data file is included in "SFC_PointReyes.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshorePointReyes/data_catalog_PointReyes.html). These data accompany the pamphlet and map sheets of Watt, J.T., Dartnell, P., Golden, N.E., Greene, H.G., Erdey, M.D., Cochrane, G.R., Johnson, S.Y., Hartwell, S.R., Kvitek, R.G., Manson, M.W., Endris, C.A., Dieter, B.E., Sliter, R.W., Krigsman, L.M., Lowe, E.N., and Chin, J.L. (J.T. Watt and S.A. Cochran, eds.), 2015, California State Waters Map Series—Offshore of Point Reyes, California: U.S. Geological Survey Open-File Report 2015–1114, pamphlet 39 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20151114. This raster-format seafloor-character map shows four substrate classes offshore of Point Reyes, California. The substrate classes mapped in this area have been further divided into the following California Marine Life Protection Act depth zones and slope classes: Depth Zone 2 (intertidal to 30 m), Depth Zone 3 (30 to 100 m), Slope Class 1 (0 degrees - 5 degrees), and Slope Class 2 (5 degrees - 30 degrees). Depth Zone 1 (intertidal), Depth Zone 4 (100 to 200 m), Depth Zone 5 (greater than 200 m), and Slope Classes 3-4 (greater than 30 degrees) are not present in the region covered by this block. The map is created using a supervised classification method described by Cochrane (2008). References Cited: California Department of Fish and Game, 2008, California Marine Life Protection Act master plan for marine protected areas; Revised draft: California Department of Fish and Game, accessed April 5 2011, at http://www.dfg.ca.gov/mlpa/masterplan.asp. Cochrane, G.R., 2008, Video-supervised classification of sonar data for mapping seafloor habitat, in Reynolds, J.R., and Greene, H.G., eds., Marine habitat mapping technology for Alaska: Fairbanks, University of Alaska, Alaska Sea Grant College Program, p. 185-194, accessed April 5, 2011, at http://doc.nprb.org/web/research/research%20pubs/615_habitat_mapping_workshop/Individual%20Chapters%20High-Res/Ch13%20Cochrane.pdf. Sappington, J.M., Longshore, K.M., and Thompson, D.B., 2007, Quantifying landscape ruggedness for animal habitat analysis--A case study using bighorn sheep in the Mojave Desert: Journal of Wildlife Management, v. 71, p. 1419-1426.

This part of DS 781 presents data for the acoustic-backscatter map of the Offshore of Refugio Beach map area, California. The raster data file is included in "Backscatter_OffshoreRefugioBeach.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreRefugioBeach/data_catalog_OffshoreRefugioBeach.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Krigsman, L.M., Dieter, B.E., Conrad, J.E., Greene, H.G., Seitz, G.G., Endris, C.A., Sliter, R.W., Wong, F.L., Erdey, M.D., Gutierrez, C.I., Yoklavich, M.M., East, A.E., and Hart, P.E. (S.Y. Johnson and S.A. Cochran, eds.), 2015, California State Waters Map Series—Offshore of Refugio Beach, California: U.S. Geological Survey Scientific Investigations Map 3319, pamphlet 42 p., 11 sheets, scale 1:24,000, https://doi.org/10.3133/sim3319. The acoustic-backscatter map of the Offshore of Refugio Beach map area, California, was generated from backscatter data collected by the U.S. Geological Survey (USGS). The USGS mapped this region in the summer 2008 using a 234.5 kHz SEA (AP) Ltd. SWATHplus-M phase-differencing sidescan sonar. These data were later re-processed in 2012. Within the acoustic-backscatter imagery, brighter tones indicate higher backscatter intensity, and darker tones indicate lower backscatter intensity. The intensity represents a complex interaction between the acoustic pulse and the seafloor, as well as characteristics within the shallow subsurface, providing a general indication of seafloor texture and sediment type. Backscatter intensity depends on the acoustic source level; the frequency used to image the seafloor; the grazing angle; the composition and character of the seafloor, including grain size, water content, bulk density, and seafloor roughness; and some biological cover. Harder and rougher bottom types such as rocky outcrops or coarse sediment typically return stronger intensities (high backscatter, lighter tones), whereas softer bottom types such as fine sediment return weaker intensities (low backscatter, darker tones).

This part of DS 781 presents data for the shaded-relief bathymetry map of the Offshore of Refugio Beach map area, California. The raster data file for the shaded-relief map is included in "BathymetryHS_OffshoreRefugioBeach.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreRefugioBeach/data_catalog_OffshoreRefugioBeach.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Krigsman, L.M., Dieter, B.E., Conrad, J.E., Greene, H.G., Seitz, G.G., Endris, C.A., Sliter, R.W., Wong, F.L., Erdey, M.D., Gutierrez, C.I., Yoklavich, M.M., East, A.E., and Hart, P.E. (S.Y. Johnson and S.A. Cochran, eds.), 2015, California State Waters Map Series—Offshore of Refugio Beach, California: U.S. Geological Survey Scientific Investigations Map 3319, pamphlet 42 p., 11 sheets, scale 1:24,000, https://doi.org/10.3133/sim3319. The shaded-relief bathymetry map of the Offshore of Refugio Beach map area, California, was generated from bathymetry data collected by the U.S. Geological Survey (USGS), and by Fugro Pelagos, for the U.S. Army Corps of Engineers (USACE) Joint Lidar Bathymetry Technical Center of Expertise. The offshore region was mapped by the USGS in 2008, using a 234.5-kHz SEA (AP) Ltd. SWATHplus-M phase-differencing sidescan sonar. The nearshore bathymetry and coastal topography were mapped for USACE by Fugro Pelagos in 2009, using the SHOALS-1000T bathymetric-lidar and Leica ALS60 topographic-lidar systems. All these mapping missions combined to collect bathymetry from the 0-m isobath to beyond the 3-nautical-mile limit of California's State Waters.

This part of DS 781 presents data for the bathymetry map of the Offshore of Refugio Beach map area, California. The raster data file for the bathymetry map is included in "Bathymetry_OffshoreRefugioBeach.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreRefugioBeach/data_catalog_OffshoreRefugioBeach.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Krigsman, L.M., Dieter, B.E., Conrad, J.E., Greene, H.G., Seitz, G.G., Endris, C.A., Sliter, R.W., Wong, F.L., Erdey, M.D., Gutierrez, C.I., Yoklavich, M.M., East, A.E., and Hart, P.E. (S.Y. Johnson and S.A. Cochran, eds.), 2015, California State Waters Map Series—Offshore of Refugio Beach, California: U.S. Geological Survey Scientific Investigations Map 3319, pamphlet 42 p., 11 sheets, scale 1:24,000, https://doi.org/10.3133/sim3319. The bathymetry map of the Offshore of Refugio Beach map area, California, was generated from bathymetry data collected by the U.S. Geological Survey (USGS), and by Fugro Pelagos, for the U.S. Army Corps of Engineers (USACE) Joint Lidar Bathymetry Technical Center of Expertise. The offshore region was mapped by the USGS in 2008, using a 234.5-kHz SEA (AP) Ltd. SWATHplus-M phase-differencing sidescan sonar. The nearshore bathymetry and coastal topography were mapped for USACE by Fugro Pelagos in 2009, using the SHOALS-1000T bathymetric-lidar and Leica ALS60 topographic-lidar systems. All these mapping missions combined to collect bathymetry from the 0-m isobath to beyond the 3-nautical-mile limit of California's State Waters.

This part of DS 781 presents data for the acoustic-backscatter map of the Offshore of Tomales Point map area, California. Backscatter data are provided as separate grids depending on mapping system or processing method. The raster data file is included in "BackscatterA_8101_ OffshoreTomalesPoint.zip", which is accessible from https://pubs.usgs.gov/ds/781/OffshoreTomalesPoint/data_catalog_OffshoreTomalesPoint.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Golden, N.E., Hartwell, S.R., Greene, H.G., Erdey, M.D., Cochrane, G.R., Watt, J.T., Kvitek, R.G., Manson, M.W., Endris, C.A., Dieter, B.E., Krigsman, L.M., Sliter, R.W., Lowe, E.N., and Chin, J.L. (S.Y. Johnson and S.A. Cochran, eds.), 2015, California State Waters Map Series—Offshore of Tomales Point, California: U.S. Geological Survey Open-File Report 2015–1088, pamphlet 38 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20151088. The acoustic-backscatter map of the Offshore of Tomales Point map area, California, was generated from backscatter data collected by California State University, Monterey Bay (CSUMB), by Fugro Pelagos, and by the U.S. Geological Survey. Mapping was completed between 2004 and 2010, using a combination of 200-kHz and 400-kHz Reson 7125, and 244-kHz Reson 8101 multibeam echosounders, as well as 234-kHz and 468-kHz SEA SWATHPlus phase-differencing sidescan sonars. These mapping missions combined to collect backscatter data from about the 10-m isobath to beyond the 3-nautical-mile limit of California's State Waters. Within the acoustic-backscatter imagery, brighter tones indicate higher backscatter intensity, and darker tones indicate lower backscatter intensity. The intensity represents a complex interaction between the acoustic pulse and the seafloor, as well as characteristics within the shallow subsurface, providing a general indication of seafloor texture and composition. Backscatter intensity depends on the acoustic source level; the frequency used to image the seafloor; the grazing angle; the composition and character of the seafloor, including grain size, water content, bulk density, and seafloor roughness; and some biological cover. Harder and rougher bottom types such as rocky outcrops or coarse sediment typically return stronger intensities (high backscatter, lighter tones), whereas softer bottom types such as fine sediment return weaker intensities (low backscatter, darker tones). These data are not intended for navigational purposes.

This part of DS 781 presents data for the acoustic-backscatter map of the Offshore of Tomales Point map area, California. Backscatter data are provided as separate grids depending on mapping system or processing method. The raster data file is included in "BackscatterB_7125_OffshoreTomalesPoint.zip", which is accessible from https://pubs.usgs.gov/ds/781/OffshoreTomalesPoint/data_catalog_OffshoreTomalesPoint.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Golden, N.E., Hartwell, S.R., Greene, H.G., Erdey, M.D., Cochrane, G.R., Watt, J.T., Kvitek, R.G., Manson, M.W., Endris, C.A., Dieter, B.E., Krigsman, L.M., Sliter, R.W., Lowe, E.N., and Chin, J.L. (S.Y. Johnson and S.A. Cochran, eds.), 2015, California State Waters Map Series—Offshore of Tomales Point, California: U.S. Geological Survey Open-File Report 2015–1088, pamphlet 38 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20151088. The acoustic-backscatter map of the Offshore of Tomales Point map area, California, was generated from backscatter data collected by California State University, Monterey Bay (CSUMB), by Fugro Pelagos, and by the U.S. Geological Survey. Mapping was completed between 2004 and 2010, using a combination of 200-kHz and 400-kHz Reson 7125, and 244-kHz Reson 8101 multibeam echosounders, as well as 234-kHz and 468-kHz SEA SWATHPlus phase-differencing sidescan sonars. These mapping missions combined to collect backscatter data from about the 10-m isobath to beyond the 3-nautical-mile limit of California's State Waters. Within the acoustic-backscatter imagery, brighter tones indicate higher backscatter intensity, and darker tones indicate lower backscatter intensity. The intensity represents a complex interaction between the acoustic pulse and the seafloor, as well as characteristics within the shallow subsurface, providing a general indication of seafloor texture and composition. Backscatter intensity depends on the acoustic source level; the frequency used to image the seafloor; the grazing angle; the composition and character of the seafloor, including grain size, water content, bulk density, and seafloor roughness; and some biological cover. Harder and rougher bottom types such as rocky outcrops or coarse sediment typically return stronger intensities (high backscatter, lighter tones), whereas softer bottom types such as fine sediment return weaker intensities (low backscatter, darker tones). These data are not intended for navigational purposes.

This part of DS 781 presents data for the acoustic-backscatter map of the Offshore of Tomales Point map area, California. Backscatter data are provided as separate grids depending on mapping system or processing method. The raster data file is included in "BackscatterC_Swath_OffshoreTomalesPoint.zip", which is accessible from https://pubs.usgs.gov/ds/781/OffshoreTomalesPoint/data_catalog_OffshoreTomalesPoint.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Golden, N.E., Hartwell, S.R., Greene, H.G., Erdey, M.D., Cochrane, G.R., Watt, J.T., Kvitek, R.G., Manson, M.W., Endris, C.A., Dieter, B.E., Krigsman, L.M., Sliter, R.W., Lowe, E.N., and Chin, J.L. (S.Y. Johnson and S.A. Cochran, eds.), 2015, California State Waters Map Series—Offshore of Tomales Point, California: U.S. Geological Survey Open-File Report 2015–1088, pamphlet 38 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20151088. The acoustic-backscatter map of the Offshore of Tomales Point map area, California, was generated from backscatter data collected by California State University, Monterey Bay (CSUMB), by Fugro Pelagos, and by the U.S. Geological Survey. Mapping was completed between 2004 and 2010, using a combination of 200-kHz and 400-kHz Reson 7125, and 244-kHz Reson 8101 multibeam echosounders, as well as 234-kHz and 468-kHz SEA SWATHPlus phase-differencing sidescan sonars. These mapping missions combined to collect backscatter data from about the 10-m isobath to beyond the 3-nautical-mile limit of California's State Waters. Within the acoustic-backscatter imagery, brighter tones indicate higher backscatter intensity, and darker tones indicate lower backscatter intensity. The intensity represents a complex interaction between the acoustic pulse and the seafloor, as well as characteristics within the shallow subsurface, providing a general indication of seafloor texture and composition. Backscatter intensity depends on the acoustic source level; the frequency used to image the seafloor; the grazing angle; the composition and character of the seafloor, including grain size, water content, bulk density, and seafloor roughness; and some biological cover. Harder and rougher bottom types such as rocky outcrops or coarse sediment typically return stronger intensities (high backscatter, lighter tones), whereas softer bottom types such as fine sediment return weaker intensities (low backscatter, darker tones). These data are not intended for navigational purposes.

This part of DS 781 presents data for the shaded-relief bathymetry map of the Offshore of Tomales Point map area, California. Raster data file is included in "BathymetryHS_OffshoreTomalesPoint.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreTomalesPoint/data_catalog_OffshoreTomalesPoint.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Golden, N.E., Hartwell, S.R., Greene, H.G., Erdey, M.D., Cochrane, G.R., Watt, J.T., Kvitek, R.G., Manson, M.W., Endris, C.A., Dieter, B.E., Krigsman, L.M., Sliter, R.W., Lowe, E.N., and Chin, J.L. (S.Y. Johnson and S.A. Cochran, eds.), 2015, California State Waters Map Series—Offshore of Tomales Point, California: U.S. Geological Survey Open-File Report 2015–1088, pamphlet 38 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20151088. The hillshaded bathymetry map of the Offshore of Tomales Point Map Area, California, was generated from bathymetry data collected by California State University, Monterey Bay (CSUMB), by Fugro Pelagos, and by the U.S. Geological Survey. Mapping was completed between 2004 and 2010, using a combination of 200-kHz and 400-kHz Reson 7125, and 244-kHz Reson 8101 multibeam echosounders, as well as 234-kHz and 468-kHz SEA SWATHPlus phase-differencing sidescan sonars. These mapping missions combined to collect bathymetry from about the 10-m isobath to beyond the 3-nautical-mile limit of California's State Waters.

This part of DS 781 presents data for the bathymetric contours for several seafloor maps of the Offshore of Tomales Point map area, California. The vector data file is included in "Contours_OffshoreTomalesPoint.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreTomalesPoint/data_catalog_OffshoreTomalesPoint.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Golden, N.E., Hartwell, S.R., Greene, H.G., Erdey, M.D., Cochrane, G.R., Watt, J.T., Kvitek, R.G., Manson, M.W., Endris, C.A., Dieter, B.E., Krigsman, L.M., Sliter, R.W., Lowe, E.N., and Chin, J.L. (S.Y. Johnson and S.A. Cochran, eds.), 2015, California State Waters Map Series—Offshore of Tomales Point, California: U.S. Geological Survey Open-File Report 2015–1088, pamphlet 38 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20151088. 10-m interval contours of the Offshore of Tomales Point map area, California, were generated from bathymetry data collected by California State University, Monterey Bay (CSUMB), by Fugro Pelagos, and by the U.S. Geological Survey. Mapping was completed between 2004 and 2010, using a combination of 200-kHz and 400-kHz Reson 7125, and 244-kHz Reson 8101 multibeam echosounders, as well as 234-kHz and 468-kHz SEA SWATHPlus phase-differencing sidescan sonars. These mapping missions combined to collect bathymetry from about the 10-m isobath to beyond the 3-nautical-mile limit of California's State Waters. Bathymetric contours at 10-m intervals were generated from a bathymetric surface model. The most continuous contour segments were preserved while smaller segments and isolated island polygons were excluded from the final output. Contours were smoothed via a polynomial approximation with exponential kernel (PAEK) algorithm using a tolerance value of 60 m. The contours were then clipped to the boundary of the map area. These data are not intended for navigational purposes.

This part of DS 781 presents the seafloor-character map of the Offshore of Tomales Point map area, California. The raster data file is included in "SeafloorCharacter_OffshoreTomalesPoint.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreTomalesPoint/data_catalog_OffshoreTomalesPoint.html). These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Golden, N.E., Hartwell, S.R., Greene, H.G., Erdey, M.D., Cochrane, G.R., Watt, J.T., Kvitek, R.G., Manson, M.W., Endris, C.A., Dieter, B.E., Krigsman, L.M., Sliter, R.W., Lowe, E.N., and Chin, J.L. (S.Y. Johnson and S.A. Cochran, eds.), 2015, California State Waters Map Series—Offshore of Tomales Point, California: U.S. Geological Survey Open-File Report 2015–1088, pamphlet 38 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20151088. This raster-format seafloor-character map shows four substrate classes offshore of Tomales Point, California. The substrate classes mapped in this area have been further divided into the following California Marine Life Protection Act depth zones and slope classes: Depth Zone 2 (intertidal to 30 m), Depth Zone 3 (30 to 100 m), Slope Class 1 (0 degrees - 5 degrees), and Slope Class 2 (5 degrees - 30 degrees). Depth Zone 1 (intertidal), Depth Zone 4 (100 to 200 m), Depth Zone 5 (greater than 200 m), and Slopes Classes 3-4 (greater than 30 degrees) are not present in the region covered by this block. The map is created using a supervised classification method described by Cochrane (2008). References Cited: California Department of Fish and Game, 2008, California Marine Life Protection Act master plan for marine protected areas; Revised draft: California Department of Fish and Game, accessed April 5 2011, at http://www.dfg.ca.gov/mlpa/masterplan.asp. Cochrane, G.R., 2008, Video-supervised classification of sonar data for mapping seafloor habitat, in Reynolds, J.R., and Greene, H.G., eds., Marine habitat mapping technology for Alaska: Fairbanks, University of Alaska, Alaska Sea Grant College Program, p. 185-194, accessed April 5, 2011, at http://doc.nprb.org/web/research/research%20pubs/615_habitat_mapping_workshop/Individual%20Chapters%20High-Res/Ch13%20Cochrane.pdf. Sappington, J.M., Longshore, K.M., and Thompson, D.B., 2007, Quantifying landscape ruggedness for animal habitat analysis--A case study using bighorn sheep in the Mojave Desert: Journal of Wildlife Management, v. 71, p. 1419-1426.

This part of DS 781 presents data for part of the acoustic-backscatter map of the Offshore of Carpinteria map area, California. The raster data file is included in "BackscatterA_CSUMB_OffshoreCarpinteria.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreCarpinteria/data_catalog_OffshoreCarpinteria.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Kvitek, R.G., Greene, H.G., Endris, C.A., Seitz, G.G., Sliter, R.W., Erdey, M.D., Wong, F.L., Gutierrez, C.I., Krigsman, L.M., Draut, A.E., and Hart, P.E. (S.Y. Johnson and S.A. Cochran, eds.), 2013, California State Waters Map Series—Offshore of Carpinteria, California: U.S. Geological Survey Scientific Investigations Map 3261, 42 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/sim3261. The acoustic-backscatter map of the Offshore of Carpinteria map area, California, was generated from backscatter data collected by California State University, Monterey Bay, Seafloor Mapping Lab (CSUMB) and by the U.S. Geological Survey (USGS). These metadata describe the acoustic-backscatter data collected by CSUMB and reprocessed by the USGS. See "BackscatterB_USGS_OffshoreCarpinteria_metadata.txt" metadata for a description of the acoustic-backscatter data collected by the USGS. The southeastern nearshore and shelf areas, as well as the western midshelf area, were mapped by CSUMB in the summer of 2007, using a 244-kHz Reson 8101 multibeam echosounder. Within the acoustic-backscatter imagery, brighter tones indicate higher backscatter intensity, and darker tones indicate lower backscatter intensity. The intensity represents a complex interaction between the acoustic pulse and the seafloor, as well as characteristics within the shallow subsurface, providing a general indication of seafloor texture and sediment type. Backscatter intensity depends on the acoustic source level; the frequency used to image the seafloor; the grazing angle; the composition and character of the seafloor, including grain size, water content, bulk density, and seafloor roughness; and some biological cover. Harder and rougher bottom types such as rocky outcrops or coarse sediment typically return stronger intensities (high backscatter, lighter tones), whereas softer bottom types such as fine sediment return weaker intensities (low backscatter, darker tones).

This part of DS 781 presents data for part of the acoustic-backscatter map of the Offshore of Carpinteria map area, California. The raster data file is included in "BackscatterB_USGS_OffshoreCarpinteria.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreCarpinteria/data_catalog_OffshoreCarpinteria.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Kvitek, R.G., Greene, H.G., Endris, C.A., Seitz, G.G., Sliter, R.W., Erdey, M.D., Wong, F.L., Gutierrez, C.I., Krigsman, L.M., Draut, A.E., and Hart, P.E. (S.Y. Johnson and S.A. Cochran, eds.), 2013, California State Waters Map Series—Offshore of Carpinteria, California: U.S. Geological Survey Scientific Investigations Map 3261, 42 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/sim3261. The acoustic-backscatter map of the Offshore of Carpinteria map area, California, was generated from backscatter data collected by California State University, Monterey Bay, Seafloor Mapping Lab (CSUMB) and by the U.S. Geological Survey (USGS). These metadata describe the acoustic-backscatter data collected by the USGS. See "BackscatterA_CSUMB_OffshoreCarpinteria_metadata.txt" metadata for a description of the acoustic-backscatter data collected by CSUMB. The western nearshore area, as well as the western outer shelf area, were mapped by the USGS in 2005 and 2006, using 117-kHz and 234.5-kHz SEA (AP) Ltd. SWATHplus-M phase-differencing sidescan sonars. This mapping mission collected acoustic-backscatter data from about the 10-m isobath to about the 3-nautical-mile limit of California's State Waters. Within the acoustic-backscatter imagery, brighter tones indicate higher backscatter intensity, and darker tones indicate lower backscatter intensity. The intensity represents a complex interaction between the acoustic pulse and the seafloor, as well as characteristics within the shallow subsurface, providing a general indication of seafloor texture and sediment type. Backscatter intensity depends on the acoustic source level; the frequency used to image the seafloor; the grazing angle; the composition and character of the seafloor, including grain size, water content, bulk density, and seafloor roughness; and some biological cover. Harder and rougher bottom types such as rocky outcrops or coarse sediment typically return stronger intensities (high backscatter, lighter tones), whereas softer bottom types such as fine sediment return weaker intensities (low backscatter, darker tones).

This part of DS 781 presents data for the shaded-relief bathymetry map of the Offshore of Carpinteria map area, California. The raster data file for the shaded-relief map is included in "BathymetryHS_OffshoreCarpinteria.zip." Both are accessible from https://pubs.usgs.gov/ds/781/OffshoreCarpinteria/data_catalog_OffshoreCarpinteria.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Kvitek, R.G., Greene, H.G., Endris, C.A., Seitz, G.G., Sliter, R.W., Erdey, M.D., Wong, F.L., Gutierrez, C.I., Krigsman, L.M., Draut, A.E., and Hart, P.E. (S.Y. Johnson and S.A. Cochran, eds.), 2013, California State Waters Map Series—Offshore of Carpinteria, California: U.S. Geological Survey Scientific Investigations Map 3261, 42 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/sim3261. The hillshaded bathymetry map of the Offshore of Carpinteria map area, California, was generated from bathymetry data collected by California State University, Monterey Bay, Seafloor Mapping Lab (CSUMB), by the U.S. Geological Survey (USGS), and by Fugro Pelagos for the U.S. Army Corps of Engineers (USACE) Joint Lidar Bathymetry Technical Center of Expertise. The southeastern nearshore and shelf areas, as well as the western midshelf area, were mapped by CSUMB in the summer of 2007, using a 244-kHz Reson 8101 multibeam echosounder. The western nearshore area, as well as the western outer shelf area, were mapped by the USGS in 2005 and 2006, using 117-kHz and 234.5-kHz SEA (AP) Ltd. SWATHplus-M phase-differencing sidescan sonars. The nearshore bathymetry and coastal topography were mapped for USACE by Fugro Pelagos in 2009, using the SHOALS-1000T bathymetric-lidar and Leica ALS60 topographic-lidar systems. All these mapping missions combined to collect bathymetry from the 0-m isobath to beyond the 3-nautical-mile limit of California's State Waters.

This part of DS 781 presents data for the bathymetry map of the Offshore of Carpinteria map area, California. The raster data file for the bathymetry map is included in "Bathymetry_OffshoreCarpinteria.zip," which is accessible from http://pubs.usgs.gov/ds/781/OffshoreCarpinteria/data_catalog_OffshoreCarpinteria.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Kvitek, R.G., Greene, H.G., Endris, C.A., Seitz, G.G., Sliter, R.W., Erdey, M.D., Wong, F.L., Gutierrez, C.I., Krigsman, L.M., Draut, A.E., and Hart, P.E. (S.Y. Johnson and S.A. Cochran, eds.), 2013, California State Waters Map Series—Offshore of Carpinteria, California: U.S. Geological Survey Scientific Investigations Map 3261, 42 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/sim3261. The bathymetry map of the Offshore of Carpinteria map area, California, was generated from bathymetry data collected by California State University, Monterey Bay, Seafloor Mapping Lab (CSUMB), by the U.S. Geological Survey (USGS), and by Fugro Pelagos for the U.S. Army Corps of Engineers (USACE) Joint Lidar Bathymetry Technical Center of Expertise. The southeastern nearshore and shelf areas, as well as the western midshelf area, were mapped by CSUMB in the summer of 2007, using a 244-kHz Reson 8101 multibeam echosounder. The western nearshore area, as well as the western outer shelf area, were mapped by the USGS in 2005 and 2006, using 117-kHz and 234.5-kHz SEA (AP) Ltd. SWATHplus-M phase-differencing sidescan sonars. The nearshore bathymetry and coastal topography were mapped for USACE by Fugro Pelagos in 2009, using the SHOALS-1000T bathymetric-lidar and Leica ALS60 topographic-lidar systems. All these mapping missions combined to collect bathymetry from the 0-m isobath to beyond the 3-nautical-mile limit of California's State Waters.

This part of DS 781 presents data for the bathymetric contours for several seafloor maps of the Offshore of Carpinteria map area, California. The vector data file is included in "Contours_OffshoreCarpinteria.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreCarpinteria/data_catalog_OffshoreCarpinteria.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Kvitek, R.G., Greene, H.G., Endris, C.A., Seitz, G.G., Sliter, R.W., Erdey, M.D., Wong, F.L., Gutierrez, C.I., Krigsman, L.M., Draut, A.E., and Hart, P.E. (S.Y. Johnson and S.A. Cochran, eds.), 2013, California State Waters Map Series—Offshore of Carpinteria, California: U.S. Geological Survey Scientific Investigations Map 3261, 42 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/sim3261. Contours of the Offshore of Carpinteria map area, California, were generated from bathymetry data collected by California State University, Monterey Bay, Seafloor Mapping Lab (CSUMB), by the U.S. Geological Survey (USGS), and by Fugro Pelagos for the U.S. Army Corps of Engineers (USACE) Joint Lidar Bathymetry Technical Center of Expertise. The southeastern nearshore and shelf areas, as well as the western midshelf area, were mapped by CSUMB in the summer of 2007, using a 244-kHz Reson 8101 multibeam echosounder. The western nearshore area, as well as the western outer shelf area, were mapped by the USGS in 2005 and 2006, using 117-kHz and 234.5-kHz SEA (AP) Ltd. SWATHplus-M phase-differencing sidescan sonars. The nearshore bathymetry and coastal topography were mapped for USACE by Fugro Pelagos in 2009, using the SHOALS-1000T bathymetric-lidar and Leica ALS60 topographic-lidar systems. All these mapping missions combined to collect bathymetry from the 0-m isobath to beyond the 3-nautical-mile limit of California's State Waters. A smooth arithmetic mean convolution function applying a weight of one-ninth to each cell in a 3-pixel by 3-pixel matrix was then applied iteratively to the grid ten times. Following smoothing, contour lines were generated at 10-m intervals, from -10 m to -100 m, and at 50-m intervals, from -100 m to -400 m, then the contours were clipped to the boundary of the map area.

This part of DS 781 presents data for the seafloor-character map of the Offshore of Carpinteria map area, California. The raster data file is included in "SeafloorCharacter_OffshoreCarpinteria.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreCarpinteria/data_catalog_OffshoreCarpinteria.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Kvitek, R.G., Greene, H.G., Endris, C.A., Seitz, G.G., Sliter, R.W., Erdey, M.D., Wong, F.L., Gutierrez, C.I., Krigsman, L.M., Draut, A.E., and Hart, P.E. (S.Y. Johnson and S.A. Cochran, eds.), 2013, California State Waters Map Series—Offshore of Carpinteria, California: U.S. Geological Survey Scientific Investigations Map 3261, 42 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/sim3261. This raster-format seafloor-character map shows five substrate classes of Offshore of Carpinteria map area. The five substrate classes mapped in this area have been colored to indicate which of the following California Marine Life Protection Act depth zones and slope classes they belong: Depth Zone 2 (intertidal to 30 m), Depth Zone 3 (30 to 100 m), and Slope Class 1, 0 degrees to 5 degrees (flat). Depth Zone 1 (intertidal), Depth Zones 4 and 5 (greater than 100 m), and Slopes Classes 2 to 4, greater than 5 degrees (sloping to vertical) are not present in this map area. The map is created using a supervised classification method described by Cochrane (2008). References Cited: California Department of Fish and Game, 2008, California Marine Life Protection Act master plan for marine protected areas--Revised draft: California Department of Fish and Game, accessed April 5 2011, at http://www.dfg.ca.gov/mlpa/masterplan.asp. Cochrane, G.R., 2008, Video-supervised classification of sonar data for mapping seafloor habitat, in Reynolds, J.R., and Greene, H.G., eds., Marine habitat mapping technology for Alaska: Fairbanks, University of Alaska, Alaska Sea Grant College Program, p. 185-194, accessed April 5, 2011, at http://doc.nprb.org/web/research/research%20pubs/615_habitat_mapping_workshop/Individual%20Chapters%20High-Res/Ch13%20Cochrane.pdf. Sappington, J.M., Longshore, K.M., and Thompson, D.B., 2007, Quantifying landscape ruggedness for animal habitat analysis--A case study using bighorn sheep in the Mojave Desert: Journal of Wildlife Management, v. 71, p. 1,419-1,426.

This part of DS 781 presents data for part of the acoustic-backscatter map of the Offshore of Coal Oil Point map area, California. The raster data file is included in "BackscatterA_CSUMB_OffshoreCoalOilPoint.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreCoalOilPoint/data_catalog_OffshoreCoalOilPoint.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Kvitek, R.G., Dieter, B.E., Conrad, J.E., Lorenson, T.D., Krigsman, L.M., Greene, H.G., Endris, C.A., Seitz, G.G., Finlayson, D.P., Sliter, R.W., Wong, F.L., Erdey, M.D., Gutierrez, C.I., Leifer, I., Yoklavich, M.M., Draut, A.E., Hart, P.E., Hostettler, F.D., Peters, K.E., Kvenvolden, K.A., Rosenbauer, R.J., and Fong, G. (S.Y. Johnson and S.A. Cochran, eds.), 2014, California State Waters Map Series—Offshore of Coal Oil Point, California: U.S. Geological Survey Scientific Investigations Map 3302, pamphlet 57 p., 12 sheets, scale 1:24,000, https://doi.org/10.3133/sim3302. The acoustic-backscatter map of Offshore Coal Oil Point, California was generated from backscatter data collected by California State University, Monterey Bay, Seafloor Mapping Lab (CSUMB), by the U.S. Geological Survey (USGS) and by Fugro Pelagos. This metadata describes the acoustic-backscatter data collected by CSUMB and reprocessed by the USGS. See "BackscatterB_USGS_OffshoreCoalOilPt_metadata.txt" metadata for a description of the acoustic-backscatter data collected by the USGS and "BackscatterC_Fugro_OffshoreCoalOilPt_metadata.txt" metadata for a description of the acoustic-backscatter data collected by Fugro Pelagros. The far eastern nearshore and shelf region of the Offshore Coal Oil Point map was mapped by CSUMB in the summer of 2007 using a 244 kHz Reson 8101 multibeam echosounder. Within the final imagery, brighter tones indicate higher backscatter intensity, and darker tones indicate lower backscatter intensity. The intensity represents a complex interaction between the acoustic pulse and the seafloor, as well as characteristics within the shallow subsurface, providing a general indication of seafloor texture and sediment type. Backscatter intensity depends on the acoustic source level; the frequency used to image the seafloor; the grazing angle; the composition and character of the seafloor, including grain size, water content, bulk density, and seafloor roughness; and some biological cover. Harder and rougher bottom types such as rocky outcrops or coarse sediment typically return stronger intensities (high backscatter, lighter tones), whereas softer bottom types such as fine sediment return weaker intensities (low backscatter, darker tones).

This part of DS 781 presents data for part of the acoustic-backscatter map of the Offshore of Coal Oil Point map area, California. The raster data file is included in "BackscatterB_USGS_OffshoreCoalOilPoint.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreCoalOilPoint/data_catalog_OffshoreCoalOilPoint.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Kvitek, R.G., Dieter, B.E., Conrad, J.E., Lorenson, T.D., Krigsman, L.M., Greene, H.G., Endris, C.A., Seitz, G.G., Finlayson, D.P., Sliter, R.W., Wong, F.L., Erdey, M.D., Gutierrez, C.I., Leifer, I., Yoklavich, M.M., Draut, A.E., Hart, P.E., Hostettler, F.D., Peters, K.E., Kvenvolden, K.A., Rosenbauer, R.J., and Fong, G. (S.Y. Johnson and S.A. Cochran, eds.), 2014, California State Waters Map Series—Offshore of Coal Oil Point, California: U.S. Geological Survey Scientific Investigations Map 3302, pamphlet 57 p., 12 sheets, scale 1:24,000, https://doi.org/10.3133/sim3302. The acoustic-backscatter map of the Offshore of Coal Oil Point map area, California, was generated from backscatter data collected by California State University, Monterey Bay, Seafloor Mapping Lab (CSUMB), by the U.S. Geological Survey (USGS), and by Fugro Pelagos. This metadata describea the acoustic-backscatter data collected by the USGS. See "BackscatterA_CSUMB_OffshoreCoalOilPoint_metadata.txt" metadata for a description of the acoustic-backscatter data collected by CSUMB, and see "BackscatterC_Fugro_OffshoreCoalOilPoint_metadata.txt" metadata for a description of the acoustic-backscatter data collected by Fugro Pelagos. Most of the nearshore and shelf areas in the Offshore of Coal Oil Point map area were mapped by the USGS in the summers of 2006, 2007, and 2008, using a combination of 117-kHz and 234.5-kHz SEA (AP) Ltd. SWATHplus-M phase-differencing sidescan sonars. Within the acoustic-backscatter imagery, brighter tones indicate higher backscatter intensity, and darker tones indicate lower backscatter intensity. The intensity represents a complex interaction between the acoustic pulse and the seafloor, as well as characteristics within the shallow subsurface, providing a general indication of seafloor texture and sediment type. Backscatter intensity depends on the acoustic source level; the frequency used to image the seafloor; the grazing angle; the composition and character of the seafloor, including grain size, water content, bulk density, and seafloor roughness; and some biological cover. Harder and rougher bottom types such as rocky outcrops or coarse sediment typically return stronger intensities (high backscatter, lighter tones), whereas softer bottom types such as fine sediment return weaker intensities (low backscatter, darker tones).

This part of DS 781 presents data for the acoustic-backscatter map of the Offshore of Coal Oil Point map area, California. The raster data file is included in "BackscatterC_Fugro_OffshoreCoalOilPoint.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreCoalOilPoint/data_catalog_OffshoreCoalOilPoint.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Kvitek, R.G., Dieter, B.E., Conrad, J.E., Lorenson, T.D., Krigsman, L.M., Greene, H.G., Endris, C.A., Seitz, G.G., Finlayson, D.P., Sliter, R.W., Wong, F.L., Erdey, M.D., Gutierrez, C.I., Leifer, I., Yoklavich, M.M., Draut, A.E., Hart, P.E., Hostettler, F.D., Peters, K.E., Kvenvolden, K.A., Rosenbauer, R.J., and Fong, G. (S.Y. Johnson and S.A. Cochran, eds.), 2014, California State Waters Map Series—Offshore of Coal Oil Point, California: U.S. Geological Survey Scientific Investigations Map 3302, pamphlet 57 p., 12 sheets, scale 1:24,000, https://doi.org/10.3133/sim3302. The acoustic-backscatter map of the Offshore of Coal Oil Point map area, California, was generated from backscatter data collected by California State University, Monterey Bay, Seafloor Mapping Lab (CSUMB), by the U.S. Geological Survey (USGS), and by Fugro Pelagos. This metadata describes the acoustic-backscatter data collected by Fugro Pelagos and reprocessed by CSUMB. See "BackscatterA_CSUMB_OffshoreCoalOilPoint_metadata.txt" metadata for a description of the acoustic-backscatter data collected by CSUMB, and see "BackscatterB_USGS_OffshoreCoalOilPoint_metadata.txt" metadata for a description of the acoustic-backscatter data collected by the USGS. Fugro Pelagos collected backscatter data offshore the Coal Oil Point region in 2008 using a combination of several sonars (400-kHz Reson 7125, 240-kHz Reson 8101, 100-kHz Reson 8111) aboard a series of Fugro Pelagos-directed vessels. An Applanix POS MV (Position and Orientation System for Marine Vessels) was used to accurately position the vessels during data collection, and it also accounted for vessel motion such as heave, pitch, and roll (position accuracy, +/-2 m; pitch, roll, and heading accuracy, +/-0.02 degrees; heave accuracy, +/-5 percent, or 5 cm). KGPS (GPS with real-time kinematic corrections) altitude data were used to account for tide-cycle fluctuations, and sound-velocity profiles were collected with an Applied Microsystems SVPlus sound velocimeter. Data were cleaned, and final products were created by the Seafloor Mapping Lab at CSUMB from the postprocessed multibeam-bathymetry data. Within the acoustic-backscatter imagery, brighter tones indicate higher backscatter intensity, and darker tones indicate lower backscatter intensity. The intensity represents a complex interaction between the acoustic pulse and the seafloor, as well as characteristics within the shallow subsurface, providing a general indication of seafloor texture and sediment type. Backscatter intensity depends on the acoustic source level; the frequency used to image the seafloor; the grazing angle; the composition and character of the seafloor, including grain size, water content, bulk density, and seafloor roughness; and some biological cover. Harder and rougher bottom types such as rocky outcrops or coarse sediment typically return stronger intensities (high backscatter, lighter tones), whereas softer bottom types such as fine sediment return weaker intensities (low backscatter, darker tones).

This part of DS 781 presents data for the shaded-relief bathymetry map of the Offshore of Coal Oil Point map area, California. The raster data file is included in "Bathymetry_OffshoreCoalOilPoint.zip." The raster data file for the shaded-relief map is included in "BathymetryHS_OffshoreCoalOilPoint.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreCoalOilPoint/data_catalog_OffshoreCoalOilPoint.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Kvitek, R.G., Dieter, B.E., Conrad, J.E., Lorenson, T.D., Krigsman, L.M., Greene, H.G., Endris, C.A., Seitz, G.G., Finlayson, D.P., Sliter, R.W., Wong, F.L., Erdey, M.D., Gutierrez, C.I., Leifer, I., Yoklavich, M.M., Draut, A.E., Hart, P.E., Hostettler, F.D., Peters, K.E., Kvenvolden, K.A., Rosenbauer, R.J., and Fong, G. (S.Y. Johnson and S.A. Cochran, eds.), 2014, California State Waters Map Series—Offshore of Coal Oil Point, California: U.S. Geological Survey Scientific Investigations Map 3302, pamphlet 57 p., 12 sheets, scale 1:24,000, https://doi.org/10.3133/sim3302. The shaded-relief bathymetry map of the Offshore of Coal Oil Point map area, California, was generated from bathymetry data collected by the U.S. Geological Survey (USGS), by California State University, Monterey Bay, Seafloor Mapping Lab (CSUMB), and by Fugro Pelagos. Most of the nearshore and shelf areas were mapped by the USGS in the summers of 2006, 2007, and 2008, using a combination of 117-kHz and 234.5-kHz SEA (AP) Ltd. SWATHplus-M phase-differencing sidescan sonars. A small area in the far-eastern nearshore and shelf was mapped by CSUMB in the summer of 2007, using a 244-kHz Reson 8101 multibeam echosounder. The outer shelf and slope were mapped by Fugro Pelagos in 2008, using a combination of 400-kHz Reson 7125, 240-kHz Reson 8101, and 100-kHz Reson 8111 multibeam echosounders. The nearshore bathymetry and coastal topography were also mapped by Fugro Pelagos in 2009 for the U.S. Army Corps of Engineers (USACE) Joint Lidar Bathymetry Technical Center of Expertise, using the SHOALS-1000T bathymetric-lidar and the Leica ALS60 topographic-lidar systems. All of these mapping missions combined to collect bathymetry from the 0-m isobath to beyond the 3-nautical-mile limit of California's State Waters.

This part of DS 781 presents data for the bathymetry map of the Offshore of Coal Oil Point map area, California. The raster data file is included in "Bathymetry_OffshoreCoalOilPoint.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreCoalOilPoint/data_catalog_OffshoreCoalOilPoint.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Kvitek, R.G., Dieter, B.E., Conrad, J.E., Lorenson, T.D., Krigsman, L.M., Greene, H.G., Endris, C.A., Seitz, G.G., Finlayson, D.P., Sliter, R.W., Wong, F.L., Erdey, M.D., Gutierrez, C.I., Leifer, I., Yoklavich, M.M., Draut, A.E., Hart, P.E., Hostettler, F.D., Peters, K.E., Kvenvolden, K.A., Rosenbauer, R.J., and Fong, G. (S.Y. Johnson and S.A. Cochran, eds.), 2014, California State Waters Map Series—Offshore of Coal Oil Point, California: U.S. Geological Survey Scientific Investigations Map 3302, pamphlet 57 p., 12 sheets, scale 1:24,000, https://doi.org/10.3133/sim3302. The bathymetry map of the Offshore of Coal Oil Point map area, California, was generated from bathymetry data collected by the U.S. Geological Survey (USGS), by California State University, Monterey Bay, Seafloor Mapping Lab (CSUMB), and by Fugro Pelagos. Most of the nearshore and shelf areas were mapped by the USGS in the summers of 2006, 2007, and 2008, using a combination of 117-kHz and 234.5-kHz SEA (AP) Ltd. SWATHplus-M phase-differencing sidescan sonars. A small area in the far-eastern nearshore and shelf was mapped by CSUMB in the summer of 2007, using a 244-kHz Reson 8101 multibeam echosounder. The outer shelf and slope were mapped by Fugro Pelagos in 2008, using a combination of 400-kHz Reson 7125, 240-kHz Reson 8101, and 100-kHz Reson 8111 multibeam echosounders. The nearshore bathymetry and coastal topography were also mapped by Fugro Pelagos in 2009 for the U.S. Army Corps of Engineers (USACE) Joint Lidar Bathymetry Technical Center of Expertise, using the SHOALS-1000T bathymetric-lidar and the Leica ALS60 topographic-lidar systems. All of these mapping missions combined to collect bathymetry from the 0-m isobath to beyond the 3-nautical-mile limit of California's State Waters.

This part of DS 781 presents bathymetric contours for several seafloor maps of Offshore Coal Oil Point, California. The vector data file is included in "Contours_OffshoreCoalOilPoint.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreCoalOilPoint/data_catalog_OffshoreCoalOilPoint.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Kvitek, R.G., Dieter, B.E., Conrad, J.E., Lorenson, T.D., Krigsman, L.M., Greene, H.G., Endris, C.A., Seitz, G.G., Finlayson, D.P., Sliter, R.W., Wong, F.L., Erdey, M.D., Gutierrez, C.I., Leifer, I., Yoklavich, M.M., Draut, A.E., Hart, P.E., Hostettler, F.D., Peters, K.E., Kvenvolden, K.A., Rosenbauer, R.J., and Fong, G. (S.Y. Johnson and S.A. Cochran, eds.), 2014, California State Waters Map Series—Offshore of Coal Oil Point, California: U.S. Geological Survey Scientific Investigations Map 3302, pamphlet 57 p., 12 sheets, scale 1:24,000, https://doi.org/10.3133/sim3302. Contours of the Offshore of Coal Oil Point map area, California, were generated from bathymetry data collected by the U.S. Geological Survey (USGS), by California State University, Monterey Bay, Seafloor Mapping Lab (CSUMB), and by Fugro Pelagos. Most of the nearshore and shelf regions were mapped by the USGS in the summers of 2006, 2007, and 2008 using a combination of 117 kHz and 234.5 kHz SEA (AP) Ltd. SWATHplus-M phase-differencing sidescan sonars. The far eastern nearshore and shelf regions were mapped by CSUMB in the summer of 2007 using a 244 kHz Reson 8101 multibeam echosounder. The outer shelf and slope regions were mapped by Fugro Pelagos in 2008 using a combination of 400 kHz Reson 7125, 240 kHz Reson 8101, and 100 kHz Reson 8111 multibeam echosounders. The nearshore bathymetry and coastal topography were also mapped by Fugro Pelagos in 2009 for the U.S. Army Corps of Engineers (USACE) Joint Lidar Bathymetry Technical Center of Expertise using the SHOALS-1000T bathymetric and the Leica ALS60 topographic lidar systems. All of these mapping missions combined to collect bathymetry from the 0-m isobath to beyond the 3-nautical mile limit of California's state waters. A smooth arithmetic mean convolution function applying a weight of 1/9 to each cell in a 3x3 matrix was applied iteratively to the merged bathymetry grid ten times. Following smoothing, contour lines were generated at 10-meter intervals from 10 to 100 m and 50-meter intervals from 100 to 250 m.

This part of DS 781 presents 2-m resolution data for the seafloor-character map of the Offshore of Coal Oil Point map area, California. The raster data file is included in "SeafloorCharacter_OffshoreCoalOilPoint_2m.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreCoalOilPoint/data_catalog_OffshoreCoalOilPoint.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Kvitek, R.G., Dieter, B.E., Conrad, J.E., Lorenson, T.D., Krigsman, L.M., Greene, H.G., Endris, C.A., Seitz, G.G., Finlayson, D.P., Sliter, R.W., Wong, F.L., Erdey, M.D., Gutierrez, C.I., Leifer, I., Yoklavich, M.M., Draut, A.E., Hart, P.E., Hostettler, F.D., Peters, K.E., Kvenvolden, K.A., Rosenbauer, R.J., and Fong, G. (S.Y. Johnson and S.A. Cochran, eds.), 2014, California State Waters Map Series—Offshore of Coal Oil Point, California: U.S. Geological Survey Scientific Investigations Map 3302, pamphlet 57 p., 12 sheets, scale 1:24,000, https://doi.org/10.3133/sim3302. The raster-format seafloor-character map shows five substrate classes of the Offshore of Coal Oil Point map area. The substrate classes mapped in this map area have been colored to indicate in which of the following California Marine Life Protection Act depth zones and slope classes they belong: Depth Zone 2 (intertidal to 30 m), Depth Zone 3 (30 to 100 m), Depth Zone 4 (100 to 200 m), Slope Class 1, 0 degrees to 5 degrees (flat), Slope Class 2, 5 degrees to 30 degrees (sloping), and Slope Class 3, 30 degrees to 60 degrees (steeply sloping). Depth Zone 1 (intertidal), Depth Zone 5 (greater than 200 m), and Slope Classes 4 and 5, greater than 60 degrees (vertical to overhang) are not present in this map area. The map is created using a supervised classification method described by Cochrane (2008). Bathymetry data were collected at two different resolutions: at 2-m resolution, down to approximately 80-m water depth (2006-2008 USGS data, and 2007 CSUMB data); and at 5-m resolution, in the deeper areas (2009 Fugro Pelagos data). The final resolution of the seafloor-character map is determined by the resolution of both the backscatter and bathymetry datasets; therefore, separate seafloor-character maps (2-m and 5-m resolutions) were generated to retain the maximum resolution of the source data. References Cited: California Department of Fish and Game, 2008, California Marine Life Protection Act master plan for marine protected areas--Revised draft: California Department of Fish and Game, accessed April 5, 2011, at http://www.dfg.ca.gov/mlpa/masterplan.asp. Cochrane, G.R., 2008, Video-supervised classification of sonar data for mapping seafloor habitat, in Reynolds, J.R., and Greene, H.G., eds., Marine habitat mapping technology for Alaska: Fairbanks, University of Alaska, Alaska Sea Grant College Program, p. 185-194, accessed April 5, 2011, at http://doc.nprb.org/web/research/research%20pubs/615_habitat_mapping_workshop/Individual%20Chapters%20High-Res/Ch13%20Cochrane.pdf. Sappington, J.M., Longshore, K.M., and Thompson, D.B., 2007, Quantifying landscape ruggedness for animal habitat analysis--A case study using bighorn sheep in the Mojave Desert: Journal of Wildlife Management, v. 71, p. 1,419-1,426.

This part of DS 781 presents 5-m resolution data for the seafloor-character map of the Offshore of Coal Oil Point map area, California. The raster data file is included in "SeafloorCharacter_OffshoreCoalOilPoint_5m.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreCoalOilPoint/data_catalog_OffshoreCoalOilPoint.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Kvitek, R.G., Dieter, B.E., Conrad, J.E., Lorenson, T.D., Krigsman, L.M., Greene, H.G., Endris, C.A., Seitz, G.G., Finlayson, D.P., Sliter, R.W., Wong, F.L., Erdey, M.D., Gutierrez, C.I., Leifer, I., Yoklavich, M.M., Draut, A.E., Hart, P.E., Hostettler, F.D., Peters, K.E., Kvenvolden, K.A., Rosenbauer, R.J., and Fong, G. (S.Y. Johnson and S.A. Cochran, eds.), 2014, California State Waters Map Series—Offshore of Coal Oil Point, California: U.S. Geological Survey Scientific Investigations Map 3302, pamphlet 57 p., 12 sheets, scale 1:24,000, https://doi.org/10.3133/sim3302. The raster-format seafloor-character map shows five substrate classes of the Offshore of Coal Oil Point map area. The substrate classes mapped in this map area have been colored to indicate in which of the following California Marine Life Protection Act depth zones and slope classes they belong: Depth Zone 2 (intertidal to 30 m), Depth Zone 3 (30 to 100 m), Depth Zone 4 (100 to 200 m), Slope Class 1, 0 degrees to 5 degrees (flat), Slope Class 2, 5 degrees to 30 degrees (sloping), and Slope Class 3, 30 degrees to 60 degrees (steeply sloping). Depth Zone 1 (intertidal), Depth Zone 5 (greater than 200 m), and Slope Classes 4 and 5, greater than 60 degrees (vertical to overhang) are not present in this map area. The map is created using a supervised classification method described by Cochrane (2008). Bathymetry data were collected at two different resolutions: at 2-m resolution, down to approximately 80-m water depth (2006-2008 USGS data, and 2007 CSUMB data); and at 5-m resolution, in the deeper areas (2009 Fugro Pelagos data). The final resolution of the seafloor-character map is determined by the resolution of both the backscatter and bathymetry datasets; therefore, separate seafloor-character maps (2-m and 5-m resolutions) were generated to retain the maximum resolution of the source data. References Cited: California Department of Fish and Game, 2008, California Marine Life Protection Act master plan for marine protected areas--Revised draft: California Department of Fish and Game, accessed April 5, 2011, at http://www.dfg.ca.gov/mlpa/masterplan.asp. Cochrane, G.R., 2008, Video-supervised classification of sonar data for mapping seafloor habitat, in Reynolds, J.R., and Greene, H.G., eds., Marine habitat mapping technology for Alaska: Fairbanks, University of Alaska, Alaska Sea Grant College Program, p. 185-194, accessed April 5, 2011, at http://doc.nprb.org/web/research/research%20pubs/615_habitat_mapping_workshop/Individual%20Chapters%20High-Res/Ch13%20Cochrane.pdf. Sappington, J.M., Longshore, K.M., and Thompson, D.B., 2007, Quantifying landscape ruggedness for animal habitat analysis--A case study using bighorn sheep in the Mojave Desert: Journal of Wildlife Management, v. 71, p. 1,419-1,426.

This part of DS 781 presents the seafloor-character map of the Drakes Bay and Vicinity map area, California (raster data file is included in "SeafloorCharacter_DrakesBay.zip," which is accessible from https://pubs.usgs.gov/ds/781/DrakesBay/data_catalog_DrakesBay.html). These data accompany the pamphlet and map sheets of Watt, J.T., Dartnell, P., Golden, N.E., Greene, H.G., Erdey, M.D., Cochrane, G.R., Johnson, S.Y., Hartwell, S.R., Kvitek, R.G., Manson, M.W., Endris, C.A., Dieter, B.E., Sliter, R.W., Krigsman, L.M., Lowe, E.N., and Chin, J.L. (J.T. Watt and S.A. Cochran, eds.), 2015, California State Waters Map Series—Drakes Bay and Vicinity, California: U.S. Geological Survey Open-File Report 2015–1041, pamphlet 36 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20151041. This raster-format seafloor-character map shows four substrate classes of Drakes Bay and Vicinity, California. The substrate classes mapped in this area have been further divided into the following California Marine Life Protection Act depth zones and slope classes: Depth Zone 2 (intertidal to 30 m), Depth Zone 3 (30 to 100 m), Slope Class 1 (0 degrees - 5 degrees), and Slope Class 2 (5 degrees - 30 degrees). Depth Zone 1 (intertidal), Depth Zone 4 (100 to 200 m), Depth Zone 5 (greater than 200 m), and Slope Classes 3-4 (greater than 30 degrees) are not present in the region covered by this block. The map is created using a supervised classification method described by Cochrane (2008). References Cited: California Department of Fish and Game, 2008, California Marine Life Protection Act master plan for marine protected areas; Revised draft: California Department of Fish and Game, accessed April 5 2011, at http://www.dfg.ca.gov/mlpa/masterplan.asp. Cochrane, G.R., 2008, Video-supervised classification of sonar data for mapping seafloor habitat, in Reynolds, J.R., and Greene, H.G., eds., Marine habitat mapping technology for Alaska: Fairbanks, University of Alaska, Alaska Sea Grant College Program, p. 185-194, accessed April 5, 2011, at http://doc.nprb.org/web/research/research%20pubs/615_habitat_mapping_workshop/Individual%20Chapters%20High-Res/Ch13%20Cochrane.pdf. Sappington, J.M., Longshore, K.M., and Thompson, D.B., 2007, Quantifying landscape ruggedness for animal habitat analysis--A case study using bighorn sheep in the Mojave Desert: Journal of Wildlife Management, v. 71, p. 1419-1426.

This part of DS 781 presents data for the geologic and geomorphic map of the Offshore of Pacifica map area, California. The vector data file is included in "Geology_OffshorePacifica.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshorePacifica/data_catalog_OffshorePacifica.html. These data accompany the pamphlet and map sheets of Edwards, B.D., Phillips, E.L., Dartnell, P., Greene, H.G., Bretz, C.K., Kvitek, R.G., Hartwell, S.R., Johnson, S.Y., Cochrane, G.R., Dieter, B.E., Sliter, R.W., Ross, S.L., Golden, N.E., Watt, J.T., Chin, J.L., Erdey, M.D., Krigsman, L.M., Manson, M.W., and Endris, C.A. (S.A. Cochran and B.D. Edwards, eds.), 2014, California State Waters Map Series—Offshore of Pacifica, California: U.S. Geological Survey Open-File Report 2014–1260, pamphlet 38 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20141260. Marine geology and geomorphology was mapped in the Offshore of Pacifica map area, California, from approximate Mean High Water (MHW) to the 3-nautical-mile limit of California's State Waters. Offshore geologic units were delineated on the basis of integrated analyses of adjacent onshore geology with multibeam bathymetry and backscatter imagery, seafloor-sediment and rock samples, digital camera and video imagery, and high-resolution seismic-reflection profiles.

This part of DS 781 presents bathymetric contours for several seafloor maps of the Offshore of Refugio Beach, California, map area. The vector data file is included in "Contours_OffshoreRefugioBeach.zip," which is accessible from https://pubs.usgs.ov/ds/781/OffshoreRefugioBeach/data_catalog_OffshoreRefugioBeach.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Krigsman, L.M., Dieter, B.E., Conrad, J.E., Greene, H.G., Seitz, G.G., Endris, C.A., Sliter, R.W., Wong, F.L., Erdey, M.D., Gutierrez, C.I., Yoklavich, M.M., East, A.E., and Hart, P.E. (S.Y. Johnson and S.A. Cochran, eds.), 2015, California State Waters Map Series—Offshore of Refugio Beach, California: U.S. Geological Survey Scientific Investigations Map 3319, pamphlet 42 p., 11 sheets, scale 1:24,000, https://doi.org/10.3133/sim3319. Contours of the Offshore of Refugio Beach, California, were generated from bathymetry data collected by the U.S. Geological Survey (USGS), by California State University, Monterey Bay, Seafloor Mapping Lab (CSUMB), and by Fugro Pelagos. The USGS conducted mapping within State waters in the summers of 2005, 2006, 2007, and 2008 using a combination of 117 kHz and 234.5 kHz SEA (AP) Ltd. SWATHplus-M phase-differencing sidescan sonars. CSUMB conducted mapping in the summers of 2006 and 2007 using a 244 kHz Reson 8101 multibeam echosounder. Fugro Pelagos conducted multibeam mapping in 2008 using a combination of 400 kHz Reson 7125, 240 kHz Reson 8101, and 100 kHz Reson 8111 multibeam echosounders. Fugro Pelagos also conducted coastal bathymetric and topographic lidar mapping in 2009 for the U.S. Army Corps of Engineers (USACE) Joint Lidar Bathymetry Technical Center of Expertise using the SHOALS-1000T bathymetric and the Leica ALS60 topographic lidar systems. All of these mapping missions combined to collect bathymetry from the 0-m isobath to beyond the 3-nautical mile limit of California's state waters.

This part of DS 781 presents the seafloor-character map of the Offshore of Refugio Beach map area, California. The raster data file is included in "SeafloorCharacter_OffshoreRefugioBeach.zip," which is accessible from https ://pubs.usgs.ov/ds/781/OffshoreRefugioBeach/data_catalog_OffshoreRefugioBeach.html). These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Krigsman, L.M., Dieter, B.E., Conrad, J.E., Greene, H.G., Seitz, G.G., Endris, C.A., Sliter, R.W., Wong, F.L., Erdey, M.D., Gutierrez, C.I., Yoklavich, M.M., East, A.E., and Hart, P.E. (S.Y. Johnson and S.A. Cochran, eds.), 2015, California State Waters Map Series—Offshore of Refugio Beach, California: U.S. Geological Survey Scientific Investigations Map 3319, pamphlet 42 p., 11 sheets, scale 1:24,000, https://doi.org/10.3133/sim3319. This raster-format seafloor-character map shows five substrate classes of Offshore of Refugio Beach, California. The substrate classes mapped in this area have been divided into the following California Marine Life Protection Act depth zones and slope classes: Depth Zone 2 (intertidal to 30 m), Depth Zone 3 (30 to 100 m), Depth Zone 4 (100 to 200 m), Slope Class 1 (0 degrees - 5 degrees), and Slope Class 2 (5 degrees - 30 degrees). Depth Zone 1 (intertidal); Depth Zone 5 (greater than 200 m), and Slope Classes 3-4 (greater than 30 degrees) are not present in this map area. The map is created using a supervised classification method described by Cochrane (2008). References Cited: California Department of Fish and Game, 2008, California Marine Life Protection Act master plan for marine protected areas; Revised draft: California Department of Fish and Game, accessed April 5 2011, at http://www.dfg.ca.gov/mlpa/masterplan.asp. Cochrane, G.R., 2008, Video-supervised classification of sonar data for mapping seafloor habitat, in Reynolds, J.R., and Greene, H.G., eds., Marine habitat mapping technology for Alaska: Fairbanks, University of Alaska, Alaska Sea Grant College Program, p. 185-194, accessed April 5, 2011, at http://doc.nprb.org/web/research/research%20pubs/615_habitat_mapping_workshop/Individual%20Chapters%20High-Res/Ch13%20Cochrane.pdf. Sappington, J.M., Longshore, K.M., and Thompson, D.B., 2007, Quantifying landscape ruggedness for animal habitat analysis--A case study using bighorn sheep in the Mojave Desert: Journal of Wildlife Management, v. 71, p. 1419-1426.

This part of DS 781 presents data for part of the acoustic-backscatter map of the Offshore of Santa Barbara map area, California. The raster data file is included in "BackscatterA_CSUMB_OffshoreSantaBarbara.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreSantaBarbara/data_catalog_OffshoreSantaBarbara.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Greene, H.G., Krigsman, L.M., Kvitek, R.G., Dieter, B.E., Endris, C.A., Seitz, G.G., Sliter, R.W., Erdey, M.E., Gutierrez, C.I., Wong, F.L., Yoklavich, M.M., Draut, A.E., Hart, P.E., and Conrad, J.E. (S.Y. Johnson and S.A. Cochran, eds.), 2013, California State Waters Map Series—Offshore of Santa Barbara, California: U.S. Geological Survey Scientific Investigations Map 3281, 45 p., 11 sheets, scale 1:24,000, https://doi.org/10.3133/sim3281. The acoustic-backscatter map of the Offshore of Santa Barbara map area, California, was generated from backscatter data collected by California State University, Monterey Bay, Seafloor Mapping Lab (CSUMB) and by the U.S. Geological Survey (USGS). These metadata describe the acoustic-backscatter data collected by CSUMB and reprocessed by the USGS. See "BackscatterB_USGS_OffshoreSantaBarbara_metadata.txt" metadata for a description of the acoustic-backscatter data collected by the USGS. Most of the offshore area was mapped by CSUMB in the summer of 2007, using a 244-kHz Reson 8101 multibeam echosounder. Within the acoustic-backscatter imagery, brighter tones indicate higher backscatter intensity, and darker tones indicate lower backscatter intensity. The intensity represents a complex interaction between the acoustic pulse and the seafloor, as well as characteristics within the shallow subsurface, providing a general indication of seafloor texture and sediment type. Backscatter intensity depends on the acoustic source level; the frequency used to image the seafloor; the grazing angle; the composition and character of the seafloor, including grain size, water content, bulk density, and seafloor roughness; and some biological cover. Harder and rougher bottom types such as rocky outcrops or coarse sediment typically return stronger intensities (high backscatter, lighter tones), whereas softer bottom types such as fine sediment return weaker intensities (low backscatter, darker tones).

This part of DS 781 presents data for part of the acoustic-backscatter map of the Offshore of Santa Barbara map area, California. The raster data file is included in "BackscatterB_USGS_OffshoreSantaBarbara.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreSantaBarbara/data_catalog_OffshoreSantaBarbara.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Greene, H.G., Krigsman, L.M., Kvitek, R.G., Dieter, B.E., Endris, C.A., Seitz, G.G., Sliter, R.W., Erdey, M.E., Gutierrez, C.I., Wong, F.L., Yoklavich, M.M., Draut, A.E., Hart, P.E., and Conrad, J.E. (S.Y. Johnson and S.A. Cochran, eds.), 2013, California State Waters Map Series—Offshore of Santa Barbara, California: U.S. Geological Survey Scientific Investigations Map 3281, 45 p., 11 sheets, scale 1:24,000, https://doi.org/10.3133/sim3281. The acoustic-backscatter map of the Offshore of Santa Barbara map area, California, was generated from backscatter data collected by California State University, Monterey Bay, Seafloor Mapping Lab (CSUMB) and by the U.S. Geological Survey (USGS). These metadata describe the acoustic-backscatter data collected by the USGS. See "BackscatterA_CSUMB_OffshoreSantaBarbara_metadata.txt" metadata for a description of the acoustic-backscatter data collected by CSUMB. Small areas in the far-east nearshore, as well as further offshore to the west and in the southeast outer shelf area, were mapped by the USGS in 2005 and 2006, using a combination of 468-kHz (2005) and 117-kHz (2006) SEA (AP) Ltd. SWATHplus-M phase-differencing sidescan sonars. Within the acoustic-backscatter imagery, brighter tones indicate higher backscatter intensity, and darker tones indicate lower backscatter intensity. The intensity represents a complex interaction between the acoustic pulse and the seafloor, as well as characteristics within the shallow subsurface, providing a general indication of seafloor texture and sediment type. Backscatter intensity depends on the acoustic source level; the frequency used to image the seafloor; the grazing angle; the composition and character of the seafloor, including grain size, water content, bulk density, and seafloor roughness; and some biological cover. Harder and rougher bottom types such as rocky outcrops or coarse sediment typically return stronger intensities (high backscatter, lighter tones), whereas softer bottom types such as fine sediment return weaker intensities (low backscatter, darker tones).

This part of DS 781 presents data for the shaded-relief bathymetry map of the Offshore of Santa Barbara map area, California. The raster data file for the hillshaded bathymetry map is included in "BathymetryHS_OffshoreSantaBarbara.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreSantaBarbara/data_catalog_OffshoreSantaBarbara.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Greene, H.G., Krigsman, L.M., Kvitek, R.G., Dieter, B.E., Endris, C.A., Seitz, G.G., Sliter, R.W., Erdey, M.E., Gutierrez, C.I., Wong, F.L., Yoklavich, M.M., Draut, A.E., Hart, P.E., and Conrad, J.E. (S.Y. Johnson and S.A. Cochran, eds.), 2013, California State Waters Map Series—Offshore of Santa Barbara, California: U.S. Geological Survey Scientific Investigations Map 3281, 45 p., 11 sheets, scale 1:24,000, https://doi.org/10.3133/sim3281. The shaded-relief bathymetry map of the Offshore of Santa Barbara map area, California, was generated from bathymetry data collected by California State University, Monterey Bay, Seafloor Mapping Lab (CSUMB), by the U.S. Geological Survey (USGS), and by Fugro Pelagos for the U.S. Army Corps of Engineers (USACE) Joint Lidar Bathymetry Technical Center of Expertise. Most of the offshore area was mapped by CSUMB in the summer of 2007, using a 244-kHz Reson 8101 multibeam echosounder. Smaller areas in the far-east nearshore, as well as further offshore to the west and in the southeast outer shelf area, were mapped by the USGS in 2005 and 2006, using a combination of 468-kHz (2005) and 117-kHz (2006) SEA (AP) Ltd. SWATHplus-M phase-differencing sidescan sonars. The nearshore bathymetry and coastal topography were mapped for USACE by Fugro Pelagos in 2009, using the SHOALS-1000T bathymetric-lidar and Leica ALS60 topographic-lidar systems. All these mapping missions combined to collect bathymetry from the 0-m isobath to beyond the 3-nautical-mile limit of California's State Waters. NOTE: The horizontal datum of this bathymetry data (NAD83) differs from the horizontal datum of other layers in this SIM (WGS84). Some bathymetry grids within this map area were projected horizontally from WGS84 to NAD83 using ESRI tools to be more consistent with the vertical reference of the North American Vertical Datum of 1988 (NAVD88).

This part of DS 781 presents data for the bathymetry map of the Offshore of Santa Barbara map area, California. The raster data file is included in "Bathymetry_OffshoreSantaBarbara.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreSantaBarbara/data_catalog_OffshoreSantaBarbara.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Greene, H.G., Krigsman, L.M., Kvitek, R.G., Dieter, B.E., Endris, C.A., Seitz, G.G., Sliter, R.W., Erdey, M.E., Gutierrez, C.I., Wong, F.L., Yoklavich, M.M., Draut, A.E., Hart, P.E., and Conrad, J.E. (S.Y. Johnson and S.A. Cochran, eds.), 2013, California State Waters Map Series—Offshore of Santa Barbara, California: U.S. Geological Survey Scientific Investigations Map 3281, 45 p., 11 sheets, scale 1:24,000, https://doi.org/10.3133/sim3281. The bathymetry map of the Offshore of Santa Barbara map area, California, was generated from bathymetry data collected by California State University, Monterey Bay, Seafloor Mapping Lab (CSUMB), by the U.S. Geological Survey (USGS), and by Fugro Pelagos for the U.S. Army Corps of Engineers (USACE) Joint Lidar Bathymetry Technical Center of Expertise. Most of the offshore area was mapped by CSUMB in the summer of 2007, using a 244-kHz Reson 8101 multibeam echosounder. Smaller areas in the far-east nearshore, as well as further offshore to the west and in the southeast outer shelf area, were mapped by the USGS in 2005 and 2006, using a combination of 468-kHz (2005) and 117-kHz (2006) SEA (AP) Ltd. SWATHplus-M phase-differencing sidescan sonars. The nearshore bathymetry and coastal topography were mapped for USACE by Fugro Pelagos in 2009, using the SHOALS-1000T bathymetric-lidar and Leica ALS60 topographic-lidar systems. All these mapping missions combined to collect bathymetry from the 0-m isobath to beyond the 3-nautical-mile limit of California's State Waters. NOTE: The horizontal datum of this bathymetry data (NAD83) differs from the horizontal datum of other layers in this SIM (WGS84). Some bathymetry grids within this map area were projected horizontally from WGS84 to NAD83 using ESRI tools to be more consistent with the vertical reference of the North American Vertical Datum of 1988 (NAVD88).

This part of DS 781 presents data for the bathymetric contours for several seafloor maps of the Offshore of Santa Barbara map area, California. The vector data file is included in "Contours_OffshoreSantaBarbara.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreSantaBarbara/data_catalog_OffshoreSantaBarbara.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Greene, H.G., Krigsman, L.M., Kvitek, R.G., Dieter, B.E., Endris, C.A., Seitz, G.G., Sliter, R.W., Erdey, M.E., Gutierrez, C.I., Wong, F.L., Yoklavich, M.M., Draut, A.E., Hart, P.E., and Conrad, J.E. (S.Y. Johnson and S.A. Cochran, eds.), 2013, California State Waters Map Series—Offshore of Santa Barbara, California: U.S. Geological Survey Scientific Investigations Map 3281, 45 p., 11 sheets, scale 1:24,000, https://doi.org/10.3133/sim3281. Contours of the Offshore of Santa Barbara map area, California, were generated from bathymetry data collected by California State University, Monterey Bay, Seafloor Mapping Lab (CSUMB), by the U.S. Geological Survey (USGS), and by Fugro Pelagos for the U.S. Army Corps of Engineers (USACE) Joint Lidar Bathymetry Technical Center of Expertise. Most of the offshore area was mapped by CSUMB in the summer of 2007, using a 244-kHz Reson 8101 multibeam echosounder. Smaller areas in the far-east nearshore, as well as further offshore to the west and in the southeast outer shelf area, were mapped by the USGS in 2005 and 2006, using a combination of 468-kHz (2005) and 117-kHz (2006) SEA (AP) Ltd. SWATHplus-M phase-differencing sidescan sonars. The nearshore bathymetry and coastal topography were mapped for USACE by Fugro Pelagos in 2009, using the SHOALS-1000T bathymetric-lidar and Leica ALS60 topographic-lidar systems. All these mapping missions combined to collect bathymetry from the 0-m isobath to beyond the 3-nautical-mile limit of California's State Waters. A smooth arithmetic mean convolution function that assigns a weight of one-ninth to each cell in a 3-pixel by 3-pixel matrix was then applied iteratively to the grid ten times. Following smoothing, contour lines were generated at 10-m intervals, then the contours were clipped to the boundary of the map area.

This part of DS 781 presents data for the seafloor-character map of the Offshore of Santa Barbara map area, California. The raster data file is included in "SeafloorCharacter_OffshoreSantaBarbara.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreSantaBarbara/data_catalog_OffshoreSantaBarbara.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Greene, H.G., Krigsman, L.M., Kvitek, R.G., Dieter, B.E., Endris, C.A., Seitz, G.G., Sliter, R.W., Erdey, M.E., Gutierrez, C.I., Wong, F.L., Yoklavich, M.M., Draut, A.E., Hart, P.E., and Conrad, J.E. (S.Y. Johnson and S.A. Cochran, eds.), 2013, California State Waters Map Series—Offshore of Santa Barbara, California: U.S. Geological Survey Scientific Investigations Map 3281, 45 p., 11 sheets, scale 1:24,000, https://doi.org/10.3133/sim3281. This raster-format seafloor-character map shows six substrate classes of the Offshore of Santa Barbara map area. The six substrate classes mapped in this area have been colored to indicate which of the following California Marine Life Protection Act depth zones and slope classes they belong: Depth Zone 2 (intertidal to 30 m), Depth Zone 3 (30 to 100 m), and Slope Class 1, 0 degrees to 5 degrees (flat). Depth Zone 1 (intertidal), Depth Zones 4 and 5 (greater than 100 m), and Slope Classes 2 to 4, greater than 5 degrees (sloping to vertical) are not present in this map area. The map is created using a supervised classification method described by Cochrane (2008). References Cited: California Department of Fish and Game, 2008, California Marine Life Protection Act master plan for marine protected areas--Revised draft: California Department of Fish and Game, accessed April 5 2011, at http://www.dfg.ca.gov/mlpa/masterplan.asp. Cochrane, G.R., 2008, Video-supervised classification of sonar data for mapping seafloor habitat, in Reynolds, J.R., and Greene, H.G., eds., Marine habitat mapping technology for Alaska: Fairbanks, University of Alaska, Alaska Sea Grant College Program, p. 185-194, accessed April 5, 2011, at http://doc.nprb.org/web/research/research%20pubs/615_habitat_mapping_workshop/Individual%20Chapters%20High-Res/Ch13%20Cochrane.pdf. Sappington, J.M., Longshore, K.M., and Thompson, D.B., 2007, Quantifying landscape ruggedness for animal habitat analysis--A case study using bighorn sheep in the Mojave Desert: Journal of Wildlife Management, v. 71, p. 1,419-1,426.

This part of DS 781 presents data for the acoustic-backscatter map of the Offshore of Tomales Point map area, California. Backscatter data are provided as separate grids depending on mapping system or processing method. The raster data file is included in "BackscatterD_USGS_OffshoreTomalesPoint.zip", which is accessible from https://pubs.usgs.gov/ds/781/OffshoreTomalesPoint/data_catalog_OffshoreTomalesPoint.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Golden, N.E., Hartwell, S.R., Greene, H.G., Erdey, M.D., Cochrane, G.R., Watt, J.T., Kvitek, R.G., Manson, M.W., Endris, C.A., Dieter, B.E., Krigsman, L.M., Sliter, R.W., Lowe, E.N., and Chin, J.L. (S.Y. Johnson and S.A. Cochran, eds.), 2015, California State Waters Map Series—Offshore of Tomales Point, California: U.S. Geological Survey Open-File Report 2015–1088, pamphlet 38 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20151088. The acoustic-backscatter map of the Offshore of Tomales Point map area, California, was generated from backscatter data collected by California State University, Monterey Bay (CSUMB), by Fugro Pelagos, and by the U.S. Geological Survey. Mapping was completed between 2004 and 2010, using a combination of 200-kHz and 400-kHz Reson 7125, and 244-kHz Reson 8101 multibeam echosounders, as well as 234-kHz and 468-kHz SEA SWATHPlus phase-differencing sidescan sonars. These mapping missions combined to collect backscatter data from about the 10-m isobath to beyond the 3-nautical-mile limit of California's State Waters. Within the acoustic-backscatter imagery, brighter tones indicate higher backscatter intensity, and darker tones indicate lower backscatter intensity. The intensity represents a complex interaction between the acoustic pulse and the seafloor, as well as characteristics within the shallow subsurface, providing a general indication of seafloor texture and composition. Backscatter intensity depends on the acoustic source level; the frequency used to image the seafloor; the grazing angle; the composition and character of the seafloor, including grain size, water content, bulk density, and seafloor roughness; and some biological cover. Harder and rougher bottom types such as rocky outcrops or coarse sediment typically return stronger intensities (high backscatter, lighter tones), whereas softer bottom types such as fine sediment return weaker intensities (low backscatter, darker tones). These data are not intended for navigational purposes.

This part of DS 781 presents data for the bathymetry map of the Offshore of Tomales Point map area, California. Raster data file is included in "Bathymetry_OffshoreTomalesPoint.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreTomalesPoint/data_catalog_OffshoreTomalesPoint.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Golden, N.E., Hartwell, S.R., Greene, H.G., Erdey, M.D., Cochrane, G.R., Watt, J.T., Kvitek, R.G., Manson, M.W., Endris, C.A., Dieter, B.E., Krigsman, L.M., Sliter, R.W., Lowe, E.N., and Chin, J.L. (S.Y. Johnson and S.A. Cochran, eds.), 2015, California State Waters Map Series—Offshore of Tomales Point, California: U.S. Geological Survey Open-File Report 2015–1088, pamphlet 38 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20151088. The bathymetry map of the Offshore of Tomales Point Map Area, California, was generated from bathymetry data collected by California State University, Monterey Bay (CSUMB), by Fugro Pelagos, and by the U.S. Geological Survey. Mapping was completed between 2004 and 2010, using a combination of 200-kHz and 400-kHz Reson 7125, and 244-kHz Reson 8101 multibeam echosounders, as well as 234-kHz and 468-kHz SEA SWATHPlus phase-differencing sidescan sonars. These mapping missions combined to collect bathymetry from about the 10-m isobath to beyond the 3-nautical-mile limit of California's State Waters. NOTE: the horizontal datum of the bathymetry data (NAD83) differs from the horizontal datum of other layers in this data series (WGS84). Some bathymetry grids within this map were projected horizontally from WGS84 to NAD83 using ESRI tools to be more consistent with the vertical reference of the North American Vertical Datum of 1988 (NAVD88). These data are not intended for navigational purposes.

This part of DS 781 presents acoustic-backscatter data for the Offshore of Ventura map area, California. The raster data file is included in "BackscatterA_CSUMB_OffshoreVentura.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreVentura/data_catalog_OffshoreVentura.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Kvitek, R.G., Greene, H.G., Krigsman, L.M., Endris, C.A., Seitz, G.G., Gutierrez, C.I., Sliter, R.W., Erdey, M.D., Wong, F.L., Yoklavich, M.M., Draut, A.E., and Hart, P.E. (S.Y. Johnson and S.A. Cochran, eds.), 2013, California State Waters Map Series—Offshore of Ventura, California: U.S. Geological Survey Scientific Investigations Map 3254, pamphlet 42 p., 11 sheets, scale 1:24,000, https://doi.org/10.3133/sim3254. The acoustic-backscatter map of the Offshore of Ventura map area, California, was generated from backscatter data collected by California State University, Monterey Bay, Seafloor Mapping Lab (CSUMB) and by the U.S. Geological Survey (USGS). These metadata describe the acoustic-backscatter data collected by CSUMB and reprocessed by the USGS (see "BackscatterB_USGS_OffshoreVentura_metadata.txt" metadata for a description of the acoustic-backscatter data collected by the USGS). The majority of the acoustic-backscatter data within the Offshore of Ventura map area, California, was collected by CSUMB in the summers of 2006 and 2007, using a 244-kHz Reson 8101 multibeam echosounder. Within the final imagery, brighter tones indicate higher backscatter intensity, and darker tones indicate lower backscatter intensity. The intensity represents a complex interaction between the acoustic pulse and the seafloor, as well as characteristics within the shallow subsurface, providing a general indication of seafloor texture and sediment type. Backscatter intensity depends on the acoustic source level; the frequency used to image the seafloor; the grazing angle; the composition and character of the seafloor, including grain size, water content, bulk density, and seafloor roughness; and some biological cover. Harder and rougher bottom types such as rocky outcrops or coarse sediment typically return stronger intensities (high backscatter, lighter tones), whereas softer bottom types such as fine sediment return weaker intensities (low backscatter, darker tones).

This part of DS 781 presents acoustic-backscatter data for the Offshore of Ventura map area, California. The raster data file is included in "BackscatterB_USGS_OffshoreVentura.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreVentura/data_catalog_OffshoreVentura.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Kvitek, R.G., Greene, H.G., Krigsman, L.M., Endris, C.A., Seitz, G.G., Gutierrez, C.I., Sliter, R.W., Erdey, M.D., Wong, F.L., Yoklavich, M.M., Draut, A.E., and Hart, P.E. (S.Y. Johnson and S.A. Cochran, eds.), 2013, California State Waters Map Series—Offshore of Ventura, California: U.S. Geological Survey Scientific Investigations Map 3254, pamphlet 42 p., 11 sheets, scale 1:24,000, https://doi.org/10.3133/sim3254. The acoustic-backscatter map of the Offshore Ventura map area, California, was generated from backscatter data collected by California State University, Monterey Bay, Seafloor Mapping Lab (CSUMB) and by the U.S. Geological Survey (USGS). These metadata describes the acoustic-backscatter data collected by the USGS (see "BackscatterA_CSUMB_OffshoreVentura_metadata.txt" metadata for a description of the acoustic-backscatter data collected by CSUMB). The seafloor west of Ventura Harbor was mapped by the USGS in 2006 and 2010, using 117-kHz (2006) and 234.5-kHz (2010) SEA (AP) Ltd. SWATHplus-M phase-differencing sidescan sonars. These mapping missions collected acoustic-backscatter data from about the 10-m isobath to beyond the 3-nautical-mile limit of California's State Waters. Within the acoustic-backscatter imagery, brighter tones indicate higher backscatter intensity, and darker tones indicate lower backscatter intensity. The intensity represents a complex interaction between the acoustic pulse and the seafloor, as well as characteristics within the shallow subsurface, providing a general indication of seafloor texture and sediment type. Backscatter intensity depends on the acoustic source level; the frequency used to image the seafloor; the grazing angle; the composition and character of the seafloor, including grain size, water content, bulk density, and seafloor roughness; and some biological cover. Harder and rougher bottom types such as rocky outcrops or coarse sediment typically return stronger intensities (high backscatter, lighter tones), whereas softer bottom types such as fine sediment return weaker intensities (low backscatter, darker tones).

This part of DS 781 presents data for the shaded-relief bathymetry map of the Offshore of Ventura map area, California. The raster data file for the shaded-relief map is included in "BathymetryHS_OffshoreVentura.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreVentura/data_catalog_OffshoreVentura.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Kvitek, R.G., Greene, H.G., Krigsman, L.M., Endris, C.A., Seitz, G.G., Gutierrez, C.I., Sliter, R.W., Erdey, M.D., Wong, F.L., Yoklavich, M.M., Draut, A.E., and Hart, P.E. (S.Y. Johnson and S.A. Cochran, eds.), 2013, California State Waters Map Series—Offshore of Ventura, California: U.S. Geological Survey Scientific Investigations Map 3254, pamphlet 42 p., 11 sheets, scale 1:24,000, https://doi.org/10.3133/sim3254. The shaded-relief bathymetry map of the Offshore of Ventura map area, California, was generated from bathymetry data collected by California State University, Monterey Bay, Seafloor Mapping Lab (CSUMB) and by the U.S. Geological Survey (USGS). Most of the offshore area was mapped by CSUMB in the summers of 2006 and 2007, using a 244-kHz Reson 8101 multibeam echosounder. The seafloor west of Ventura Harbor was mapped by the USGS in 2006 and 2010, using 117-kHz (2006) and 234.5-kHz (2010) SEA (AP) Ltd. SWATHplus-M phase-differencing sidescan sonars. These mapping missions combined to collect bathymetry from about the 10-m isobath to beyond the 3-nautical-mile limit of California's State Waters.

This part of DS 781 presents data for the bathymetry map of the Offshore of Ventura map area, California. The raster data file is included in "Bathymetry_OffshoreVentura.zip, which is accessible from https://pubs.usgs.gov/ds/781/OffshoreVentura/data_catalog_OffshoreVentura.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Kvitek, R.G., Greene, H.G., Krigsman, L.M., Endris, C.A., Seitz, G.G., Gutierrez, C.I., Sliter, R.W., Erdey, M.D., Wong, F.L., Yoklavich, M.M., Draut, A.E., and Hart, P.E. (S.Y. Johnson and S.A. Cochran, eds.), 2013, California State Waters Map Series—Offshore of Ventura, California: U.S. Geological Survey Scientific Investigations Map 3254, pamphlet 42 p., 11 sheets, scale 1:24,000, https://doi.org/10.3133/sim3254. The bathymetry maps of the Offshore of Ventura map area, California, was generated from bathymetry data collected by California State University, Monterey Bay, Seafloor Mapping Lab (CSUMB) and by the U.S. Geological Survey (USGS). Most of the offshore area was mapped by CSUMB in the summers of 2006 and 2007, using a 244-kHz Reson 8101 multibeam echosounder. The seafloor west of Ventura Harbor was mapped by the USGS in 2006 and 2010, using 117-kHz (2006) and 234.5-kHz (2010) SEA (AP) Ltd. SWATHplus-M phase-differencing sidescan sonars. These mapping missions combined to collect bathymetry from about the 10-m isobath to beyond the 3-nautical-mile limit of California's State Waters.

This part of DS 781 presents data for the bathymetric contours of the Offshore of Ventura map area, California. The vector data file is included in "Contours_OffshoreVentura.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreVentura/data_catalog_OffshoreVentura.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Kvitek, R.G., Greene, H.G., Krigsman, L.M., Endris, C.A., Seitz, G.G., Gutierrez, C.I., Sliter, R.W., Erdey, M.D., Wong, F.L., Yoklavich, M.M., Draut, A.E., and Hart, P.E. (S.Y. Johnson and S.A. Cochran, eds.), 2013, California State Waters Map Series—Offshore of Ventura, California: U.S. Geological Survey Scientific Investigations Map 3254, pamphlet 42 p., 11 sheets, scale 1:24,000, https://doi.org/10.3133/sim3254. Contours of the Offshore of Ventura map area, California, were generated from bathymetry data collected by California State University, Monterey Bay, Seafloor Mapping Lab (CSUMB) and by the U.S. Geological Survey (USGS). Most of the offshore area was mapped by CSUMB in the summers of 2006 and 2007, using a 244-kHz Reson 8101 multibeam echosounder. The seafloor west of Ventura Harbor was mapped by the USGS in 2006 and 2010, using 117-kHz (2006) and 234.5-kHz (2010) SEA (AP) Ltd. SWATHplus-M phase-differencing sidescan sonars. These mapping missions combined to collect bathymetry from about the 10-m isobath to beyond the 3-nautical-mile limit of California's State Waters. A smooth arithmetic mean convolution function applying a weight of one-ninth to each cell in a 3-pixel by 3-pixel matrix was then applied iteratively to the grid ten times. Following smoothing, contour lines were generated at 10-m intervals, from -10 m to -100 m, and at 50-m intervals, from -100 m to -400 m, then the contours were clipped to the boundary of the map area.

This part of DS 781 presents data for the seafloor-character map of the Offshore of Ventura map area, California. The raster data file is included in "SeafloorCharacter_OffshoreVentura.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreVentura/data_catalog_OffshoreVentura.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Kvitek, R.G., Greene, H.G., Krigsman, L.M., Endris, C.A., Seitz, G.G., Gutierrez, C.I., Sliter, R.W., Erdey, M.D., Wong, F.L., Yoklavich, M.M., Draut, A.E., and Hart, P.E. (S.Y. Johnson and S.A. Cochran, eds.), 2013, California State Waters Map Series—Offshore of Ventura, California: U.S. Geological Survey Scientific Investigations Map 3254, pamphlet 42 p., 11 sheets, scale 1:24,000, https://doi.org/10.3133/sim3254. This raster-format seafloor-character map shows four substrate classes in the Offshore of Ventura map area. The substrate classes mapped in this area have been colored to indicate which of the following California Marine Life Protection Act depth zones and slope classes they belong: Depth Zone 2 (intertidal to 30 m), Depth Zone 3 (30 to 100 m), and Slope Class 1 (0 degrees - 5 degrees). Depth Zones 1 (intertidal) and 4 to 5 (greater than 100 m), as well as Slopes Classes 2 to 4 (greater than 5 degrees), are not present in this map area. The map is created using a supervised classification method described by Cochrane (2008). References Cited: California Department of Fish and Game, 2008, California Marine Life Protection Act master plan for marine protected areas--Revised draft: California Department of Fish and Game, accessed April 5 2011, at http://www.dfg.ca.gov/mlpa/masterplan.asp. Cochrane, G.R., 2008, Video-supervised classification of sonar data for mapping seafloor habitat, in Reynolds, J.R., and Greene, H.G., eds., Marine habitat mapping technology for Alaska: Fairbanks, University of Alaska, Alaska Sea Grant College Program, p. 185-194, accessed April 5, 2011, at http://doc.nprb.org/web/research/research%20pubs/615_habitat_mapping_workshop/Individual%20Chapters%20High-Res/Ch13%20Cochrane.pdf. Sappington, J.M., Longshore, K.M., and Thompson, D.B., 2007, Quantifying landscape ruggedness for animal habitat analysis--A case study using bighorn sheep in the Mojave Desert: Journal of Wildlife Management, v. 71, p. 1,419-1,426.

This part of DS 781 presents data for the acoustic-backscatter map of the Offshore of Fort Ross map area, California. Backscatter data are provided as separate grids depending on mapping system or processing method. The raster data file is included in "BackscatterA_8101_OffshoreFortRoss.zip", which is accessible from https://pubs.usgs.gov/ds/781/OffshoreFortRoss/data_catalog_OffshoreFortRoss.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Golden, N.E., Hartwell, S.R., Erdey, M.D., Greene, H.G., Cochrane, G.R., Kvitek, R.G., Manson, M.W., Endris, C.A., Dieter, B.E., Watt, J.T., Krigsman, L.M., Sliter, R.W., Lowe, E.N., and Chin, J.L. (S.Y. Johnson and S.A. Cochran, eds.), 2015, California State Waters Map Series--Offshore of Fort Ross, California: U.S. Geological Survey Open-File Report 2015–1211, pamphlet 37 p., 10 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20151211. The acoustic-backscatter map of the Offshore of Fort Ross map area, California, was generated from backscatter data collected by California State University, Monterey Bay (CSUMB) and by Fugro Pelagos. Mapping was completed between 2007 and 2010, using a combination of 200-kHz and 400-kHz Reson 7125, and 244-kHz Reson 8101 multibeam echosounders, as well as 468-kHz SEA SWATHPlus interferometric system. These mapping missions combined to collect backscatter data from about the 10-m isobath to beyond the 3-nautical-mile limit of California State Waters. Within the acoustic-backscatter imagery, brighter tones indicate higher backscatter intensity, and darker tones indicate lower backscatter intensity. The intensity represents a complex interaction between the acoustic pulse and the seafloor, as well as characteristics within the shallow subsurface, providing a general indication of seafloor texture and composition. Backscatter intensity depends on the acoustic source level; the frequency used to image the seafloor; the grazing angle; the composition and character of the seafloor, including grain size, water content, bulk density, and seafloor roughness; and some biological cover. Harder and rougher bottom types such as rocky outcrops or coarse sediment typically return stronger intensities (high backscatter, lighter tones), whereas softer bottom types such as fine sediment return weaker intensities (low backscatter, darker tones). These data are not intended for navigational purposes.

This part of DS 781 presents video observations from cruise C0111SC in southern California. The vector data file is included in "c0111sc_video_observations.zip," which is accessible from https://pubs.usgs.gov/ds/781/video_observations/data_catalog_video_observations.html. In 1999 and 2009, the seafloor in southern California was mapped by California State University, Monterey Bay, Seafloor Mapping Lab (CSUMB) and by the U.S. Geological Survey (USGS), using both multibeam echosounders and bathymetric sidescan sonar units. These mapping missions combined to collect bathymetry and acoustic-backscatter data from about the 10-m isobath to out beyond the 3-nautical-mile limit of California's State Waters. To validate the interpretations of sonar data in order to turn it into geologically and biologically useful information, the USGS ground-truth surveyed the data by towing camera sleds over specific locations throughout the region. During the 2011 ground-truth cruise, the camera sled housed two video cameras (one forward looking and the other vertical looking), a high-definition video camera, and an 8-megapixel digital still camera. The video was fed in real time to the research vessel, where USGS and NOAA scientists recorded both the geologic and biologic character of the seafloor into programmable keypads once every minute. In addition to recording the seafloor characteristics, a digital still photograph was captured once every 30 seconds. This ArcGIS shape file includes the position of the camera, the time each observation was started, and the visual observations of geologic and biologic habitat.

This part of DS 781 presents video observations from cruise C0212SC in southern California. The vector data file is included in "c0212sc_video_observations.zip," which is accessible from https://pubs.usgs.gov/ds/781/video_observations/data_catalog_video_observations.html. In 2006 and 2009, the seafloor in central California was mapped by California State University, Monterey Bay, Seafloor Mapping Lab (CSUMB) and by the U.S. Geological Survey (USGS), using both multibeam echosounders and bathymetric sidescan sonar units. These mapping missions combined to collect bathymetry and acoustic-backscatter data from about the 10-m isobath to out beyond the 3-nautical-mile limit of California's State Waters. To validate the interpretations of sonar data in order to turn it into geologically and biologically useful information, the USGS ground-truth surveyed the data by towing camera sleds over specific locations throughout the region. During the 2012 ground-truth cruise, the camera sled housed two video cameras (one forward looking and the other vertical looking), a high-definition video camera, and an 8-megapixel digital still camera. The video was fed in real time to the research vessel, where USGS and NOAA scientists recorded both the geologic and biologic character of the seafloor into programmable keypads once every minute. In addition to recording the seafloor characteristics, a digital still photograph was captured once every 30 seconds. This ArcGIS shape file includes the position of the camera, the time each observation was started, and the visual observations of geologic and biologic habitat.

This part of DS 781 presents video observations from cruise C210NC in northern California. The vector data file is included in "c201nc_video_observations.zip," which is accessible from https://pubs.usgs.gov/ds/781/video_observations/data_catalog_video_observations.html. In 2010, the seafloor in northern California was mapped by California State University, Monterey Bay, Seafloor Mapping Lab (CSUMB) using both multibeam echosounders and bathymetric sidescan sonar units. This mapping mission collected bathymetry and acoustic-backscatter data from about the 10-m isobath to out beyond the 3-nautical-mile limit of California's State Waters. To validate the interpretations of sonar data in order to turn it into geologically and biologically useful information, the USGS ground-truth surveyed the data by towing camera sleds over specific locations throughout the region. During the 2010 ground-truth cruise, the camera sled housed two video cameras (one forward looking and the other vertical looking), a high-definition video camera, and an 8-megapixel digital still camera. The video was fed in real time to the research vessel, where USGS and NOAA scientists recorded both the geologic and biologic character of the seafloor into programmable keypads once every minute. In addition to recording the seafloor characteristics, a digital still photograph was captured once every 30 seconds. This ArcGIS shape file includes the position of the camera, the time each observation was started, and the visual observations of geologic and biologic habitat.

This part of DS 781 presents video observations from cruise F208NC in northern California. The vector data file is included in "f208nc_video_observations.zip," which is accessible from https://pubs.usgs.gov/ds/781/video_observations/data_catalog_video_observations.html. Between 2006 and 2007, the seafloor in central California was mapped by California State University, Monterey Bay, Seafloor Mapping Lab (CSUMB) and by the U.S. Geological Survey (USGS), using both multibeam echosounders and bathymetric sidescan sonar units. These mapping missions combined to collect bathymetry and acoustic-backscatter data from about the 10-m isobath to out beyond the 3-nautical-mile limit of California's State Waters. To validate the interpretations of sonar data in order to turn it into geologically and biologically useful information, the USGS ground-truth surveyed the data by towing camera sleds over specific locations throughout the region. During the 2008 ground-truth cruise, the camera sled housed two video cameras (one forward looking and the other vertical looking), a high-definition video camera, and an 8-megapixel digital still camera. The video was fed in real time to the research vessel, where USGS and NOAA scientists recorded both the geologic and biologic character of the seafloor into programmable keypads once every minute. In addition to recording the seafloor characteristics, a digital still photograph was captured once every 30 seconds. This ArcGIS shape file includes the position of the camera, the time each observation was started, and the visual observations of geologic and biologic habitat.

This part of DS 781 presents video observations from cruise F307NC in northern California The vector data file is included in "f307nc_video_observations.zip," which is accessible from https://pubs.usgs.gov/ds/781/video_observations/data_catalog_video_observations.html. Between 2006 and 2007, the seafloor in northern California was mapped by California State University, Monterey Bay, Seafloor Mapping Lab (CSUMB) and by the U.S. Geological Survey (USGS), using both multibeam echosounders and bathymetric sidescan sonar units. These mapping missions combined to collect bathymetry and acoustic-backscatter data from about the 10-m isobath to out beyond the 3-nautical-mile limit of California's State Waters. To validate the interpretations of sonar data in order to turn it into geologically and biologically useful information, the USGS ground-truth surveyed the data by towing camera sleds over specific locations throughout the region. During the 2007 ground-truth cruise, the camera sled housed two video cameras (one forward looking and the other vertical looking), a high-definition video camera, and an 8-megapixel digital still camera. The video was fed in real time to the research vessel, where USGS and NOAA scientists recorded both the geologic and biologic character of the seafloor into programmable keypads once every minute. In addition to recording the seafloor characteristics, a digital still photograph was captured once every 30 seconds. This ArcGIS shape file includes the position of the camera, the time each observation was started, and the visual observations of geologic and biologic habitat.

This part of DS 781 presents video observations from cruise L908NC for northern California. The vector data file is included in "l908nc_video_observations.zip," which is accessible from https://pubs.usgs.gov/ds/781/video_observations/data_catalog_video_observations.html. Between 2006 and 2007, the seafloor in central California was mapped by California State University, Monterey Bay, Seafloor Mapping Lab (CSUMB) and by the U.S. Geological Survey (USGS), using both multibeam echosounders and bathymetric sidescan sonar units. These mapping missions combined to collect bathymetry and acoustic-backscatter data from about the 10-m isobath to out beyond the 3-nautical-mile limit of California's State Waters. To validate the interpretations of sonar data in order to turn it into geologically and biologically useful information, the USGS ground-truth surveyed the data by towing camera sleds over specific locations throughout the region. During the 2008 ground-truth cruise, the camera sled housed two video cameras (one forward looking and the other vertical looking), a high-definition video camera, and an 8-megapixel digital still camera. The video was fed in real time to the research vessel, where USGS and NOAA scientists recorded both the geologic and biologic character of the seafloor into programmable keypads once every minute. In addition to recording the seafloor characteristics, a digital still photograph was captured once every 30 seconds. This ArcGIS shape file includes the position of the camera, the time each observation was started, and the visual observations of geologic and biologic habitat.

This part of DS 781 presents video observations from cruise S1C08SC for the Santa Barbara Channel region and beyond in southern California. The vector data file is included in "s1c08sc_video_observations.zip," which is accessible from https://pubs.usgs.gov/ds/781/video_observations/data_catalog_video_observations.html. Between 2006 and 2007, the seafloor southern California was mapped by California State University, Monterey Bay, Seafloor Mapping Lab (CSUMB) and by the U.S. Geological Survey (USGS), using both multibeam echosounders and bathymetric sidescan sonar units. These mapping missions combined to collect bathymetry and acoustic-backscatter data from about the 10-m isobath to out beyond the 3-nautical-mile limit of California's State Waters. To validate the interpretations of sonar data in order to turn it into geologically and biologically useful information, the USGS ground-truth surveyed the data by towing camera sleds over specific locations throughout the region. During the 2008 ground-truth cruise, the camera sled housed two video cameras (one forward looking and the other vertical looking), a high-definition video camera, and an 8-megapixel digital still camera. The video was fed in real time to the research vessel, where USGS and NOAA scientists recorded both the geologic and biologic character of the seafloor into programmable keypads once every minute. In addition to recording the seafloor characteristics, a digital still photograph was captured once every 30 seconds. This ArcGIS shape file includes the position of the camera, the time each observation was started, and the visual observations of geologic and biologic habitat.

This part of DS 781 presents video observations from cruise S2210MB in northern California. The vector data file is included in "s2210mb_video_observations.zip," which is accessible from https://pubs.usgs.gov/ds/781/video_observations/data_catalog_video_observations.html. In 2006 and 2009, the seafloor in central California was mapped by California State University, Monterey Bay, Seafloor Mapping Lab (CSUMB) and by the U.S. Geological Survey (USGS), using both multibeam echosounders and bathymetric sidescan sonar units. These mapping missions combined to collect bathymetry and acoustic-backscatter data from about the 10-m isobath to out beyond the 3-nautical-mile limit of California's State Waters. To validate the interpretations of sonar data in order to turn it into geologically and biologically useful information, the USGS ground-truth surveyed the data by towing camera sleds over specific locations throughout the region. During the 2012 ground-truth cruise, the camera sled housed two video cameras (one forward looking and the other vertical looking), a high-definition video camera, and an 8-megapixel digital still camera. The video was fed in real time to the research vessel, where USGS and NOAA scientists recorded both the geologic and biologic character of the seafloor into programmable keypads once every minute. In addition to recording the seafloor characteristics, a digital still photograph was captured once every 30 seconds. This ArcGIS shape file includes the position of the camera, the time each observation was started, and the visual observations of geologic and biologic habitat.

This part of DS 781 presents video observations from cruise SW109SC for the Santa Barbara Channel region and beyond in southern California. The vector data file is included in "sw109sc_video_observations.zip," which is accessible from https://pubs.usgs.gov/ds/781/video_observations/data_catalog_video_observations.html. Between 2006 and 2007, the seafloor in southern California was mapped by California State University, Monterey Bay, Seafloor Mapping Lab (CSUMB) and by the U.S. Geological Survey (USGS), using both multibeam echosounders and bathymetric sidescan sonar units. These mapping missions combined to collect bathymetry and acoustic-backscatter data from about the 10-m isobath to out beyond the 3-nautical-mile limit of California's State Waters. To validate the interpretations of sonar data in order to turn it into geologically and biologically useful information, the USGS ground-truth surveyed the data by towing camera sleds over specific locations throughout the region. During the 2008 ground-truth cruise, the camera sled housed two video cameras (one forward looking and the other vertical looking), a high-definition video camera, and an 8-megapixel digital still camera. The video was fed in real time to the research vessel, where USGS and NOAA scientists recorded both the geologic and biologic character of the seafloor into programmable keypads once every minute. In addition to recording the seafloor characteristics, a digital still photograph was captured once every 30 seconds. This ArcGIS shape file includes the position of the camera, the time each observation was started, and the visual observations of geologic and biologic habitat.

This part of DS 781 presents video observations from cruise Z107SC in southern California. The vector data file is included in "z107sc_video_observations.zip," which is accessible from https://pubs.usgs.gov/ds/781/video_observations/data_catalog_video_observations.html. Between 2006 and 2007, the seafloor southern California was mapped by California State University, Monterey Bay, Seafloor Mapping Lab (CSUMB) and by the U.S. Geological Survey (USGS), using both multibeam echosounders and bathymetric sidescan sonar units. These mapping missions combined to collect bathymetry and acoustic-backscatter data from about the 10-m isobath to out beyond the 3-nautical-mile limit of California's State Waters. To validate the interpretations of sonar data in order to turn it into geologically and biologically useful information, the USGS ground-truth surveyed the data by towing camera sleds over specific locations throughout the region. During the 2008 ground-truth cruise, the camera sled housed two video cameras (one forward looking and the other vertical looking), a high-definition video camera, and an 8-megapixel digital still camera. The video was fed in real time to the research vessel, where USGS and NOAA scientists recorded both the geologic and biologic character of the seafloor into programmable keypads once every minute. In addition to recording the seafloor characteristics, a digital still photograph was captured once every 30 seconds. This ArcGIS shape file includes the position of the camera, the time each observation was started, and the visual observations of geologic and biologic habitat.

This part of DS 781 presents video observations from cruise Z206SC in southern California. The vector data file is included in "z206sc_video_observations.zip," which is accessible from https://pubs.usgs.gov/ds/781/video_observations/data_catalog_video_observations.html. Between 2006 and 2007, the seafloor in southern California was mapped by California State University, Monterey Bay, Seafloor Mapping Lab (CSUMB) and by the U.S. Geological Survey (USGS), using both multibeam echosounders and bathymetric sidescan sonar units. These mapping missions combined to collect bathymetry and acoustic-backscatter data from about the 10-m isobath to out beyond the 3-nautical-mile limit of California's State Waters. To validate the interpretations of sonar data in order to turn it into geologically and biologically useful information, the USGS ground-truth surveyed the data by towing camera sleds over specific locations throughout the region. During the 2008 ground-truth cruise, the camera sled housed two video cameras (one forward looking and the other vertical looking), a high-definition video camera, and an 8-megapixel digital still camera. The video was fed in real time to the research vessel, where USGS and NOAA scientists recorded both the geologic and biologic character of the seafloor into programmable keypads once every minute. In addition to recording the seafloor characteristics, a digital still photograph was captured once every 30 seconds. This ArcGIS shape file includes the position of the camera, the time each observation was started, and the visual observations of geologic and biologic habitat.

This part of DS 781 presents benthic biological observations of the California coast in support of the California Seafloor Mapping Project. A shapefile and corresponding comma-delimited text file are included in "Benthic_Biological_Interpretation.zip," which is accessible from https://pubs.usgs.gov/ds/781/video_observations/data_catalog_video_observations.html.

This part of DS 781 presents video observations from cruise C109NC in northern California. The vector data file is included in "c109nc_video_observations.zip," which is accessible from https://pubs.usgs.gov/ds/781/video_observations/data_catalog_video_observations.html. In 2006 and 2007, the seafloor in northern California was mapped by California State University, Monterey Bay, Seafloor Mapping Lab (CSUMB), using both multibeam echosounders and bathymetric sidescan sonar units. This mapping mission collected bathymetry and acoustic-backscatter data from about the 10-m isobath to out beyond the 3-nautical-mile limit of California's State Waters. To validate the interpretations of sonar data in order to turn it into geologically and biologically useful information, the USGS ground-truth surveyed the data by towing camera sleds over specific locations throughout the region. During the 2009 ground-truth cruise, the camera sled housed two video cameras (one forward looking and the other vertical looking), a high-definition video camera, and an 8-megapixel digital still camera. The video was fed in real time to the research vessel, where USGS and NOAA scientists recorded both the geologic and biologic character of the seafloor into programmable keypads once every minute. In addition to recording the seafloor characteristics, a digital still photograph was captured once every 30 seconds. This ArcGIS shape file includes the position of the camera, the time each observation was started, and the visual observations of geologic and biologic habitat.

In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ecosystems as part of the design and proposal process for the establishment of Marine Protected Areas. A focus of CSMP is to map California’s State Waters with consistent methods at a consistent scale. The CSMP approach is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar data (the undersea equivalent of satellite remote-sensing data in terrestrial mapping), acoustic backscatter, seafloor video, seafloor photography, high-resolution seismic-reflection profiles, and bottom-sediment sampling data. The map products display seafloor morphology and character, identify potential marine benthic habitats, and illustrate both the surficial seafloor geology and shallow (to about 100 m) subsurface geology. It is emphasized that the more interpretive habitat and geology data rely on the integration of multiple, new high-resolution datasets and that mapping at small scales would not be possible without such data. This approach and CSMP planning is based in part on recommendations of the Marine Mapping Planning Workshop (Kvitek and others, 2006), attended by coastal and marine managers and scientists from around the state. That workshop established geographic priorities for a coastal mapping project and identified the need for coverage of “lands” from the shore strand line (defined as Mean Higher High Water; MHHW) out to the 3-nautical-mile (5.6-km) limit of California’s State Waters. Unfortunately, surveying the zone from MHHW out to 10-m water depth is not consistently possible using ship-based surveying methods, owing to sea state (for example, waves, wind, or currents), kelp coverage, and shallow rock outcrops. Accordingly, some of the data presented in this series commonly do not cover the zone from the shore out to 10-m depth. This data is part of a series of online U.S. Geological Survey (USGS) publications, each of which includes several map sheets, some explanatory text, and a descriptive pamphlet. Each map sheet is published as a PDF file. Geographic information system (GIS) files that contain both ESRI ArcGIS raster grids (for example, bathymetry, seafloor character) and geotiffs (for example, shaded relief) are also included for each publication. For those who do not own the full suite of ESRI GIS and mapping software, the data can be read using ESRI ArcReader, a free viewer that is available at http://www.esri.com/software/arcgis/arcreader/index.html (last accessed September 20, 2013). The California Seafloor Mapping Program is a collaborative venture between numerous different federal and state agencies, academia, and the private sector. CSMP partners include the California Coastal Conservancy, the California Ocean Protection Council, the California Department of Fish and Wildlife, the California Geological Survey, California State University at Monterey Bay’s Seafloor Mapping Lab, Moss Landing Marine Laboratories Center for Habitat Studies, Fugro Pelagos, Pacific Gas and Electric Company, National Oceanic and Atmospheric Administration (NOAA, including National Ocean Service–Office of Coast Surveys, National Marine Sanctuaries, and National Marine Fisheries Service), U.S. Army Corps of Engineers, the Bureau of Ocean Energy Management, the National Park Service, and the U.S. Geological Survey. These web services for the Offshore of Monterey map area includes data layers that are associated to GIS and map sheets available from the USGS CSMP web page at https://walrus.wr.usgs.gov/mapping/csmp/index.html. Each published CSMP map area includes a data catalog of geographic information system (GIS) files; map sheets that contain explanatory text; and an associated descriptive pamphlet. This web service represents the available data layers for this map area. Data was combined from different sonar surveys to generate a comprehensive high-resolution bathymetry and acoustic-backscatter coverage of the map area. These data reveal a range of physiographic including exposed bedrock outcrops, large fields of sand waves, as well as many human impacts on the seafloor. To validate geological and biological interpretations of the sonar data, the U.S. Geological Survey towed a camera sled over specific offshore locations, collecting both video and photographic imagery; these “ground-truth” surveying data are available from the CSMP Video and Photograph Portal at https://doi.org/10.5066/F7J1015K. The “seafloor character” data layer shows classifications of the seafloor on the basis of depth, slope, rugosity (ruggedness), and backscatter intensity and which is further informed by the ground-truth-survey imagery. The “potential habitats” polygons are delineated on the basis of substrate type, geomorphology, seafloor process, or other attributes that may provide a habitat for a specific species or assemblage of organisms. Representative seismic-reflection profile data from the map area is also include and provides information on the subsurface stratigraphy and structure of the map area. The distribution and thickness of young sediment (deposited over the past about 21,000 years, during the most recent sea-level rise) is interpreted on the basis of the seismic-reflection data. The geologic polygons merge onshore geologic mapping (compiled from existing maps by the California Geological Survey) and new offshore geologic mapping that is based on integration of high-resolution bathymetry and backscatter imagery seafloor-sediment and rock samplesdigital camera and video imagery, and high-resolution seismic-reflection profiles. The information provided by the map sheets, pamphlet, and data catalog has a broad range of applications. High-resolution bathymetry, acoustic backscatter, ground-truth-surveying imagery, and habitat mapping all contribute to habitat characterization and ecosystem-based management by providing essential data for delineation of marine protected areas and ecosystem restoration. Many of the maps provide high-resolution baselines that will be critical for monitoring environmental change associated with climate change, coastal development, or other forcings. High-resolution bathymetry is a critical component for modeling coastal flooding caused by storms and tsunamis, as well as inundation associated with longer term sea-level rise. Seismic-reflection and bathymetric data help characterize earthquake and tsunami sources, critical for natural-hazard assessments of coastal zones. Information on sediment distribution and thickness is essential to the understanding of local and regional sediment transport, as well as the development of regional sediment-management plans. In addition, siting of any new offshore infrastructure (for example, pipelines, cables, or renewable-energy facilities) will depend on high-resolution mapping. Finally, this mapping will both stimulate and enable new scientific research and also raise public awareness of, and education about, coastal environments and issues. Web services were created using an ArcGIS service definition file. The ArcGIS REST service and OGC WMS service include all Offshore of Monterey map area data layers. Data layers are symbolized as shown on the associated map sheets.

In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ecosystems as part of the design and proposal process for the establishment of Marine Protected Areas. A focus of CSMP is to map California’s State Waters with consistent methods at a consistent scale. The CSMP approach is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar data (the undersea equivalent of satellite remote-sensing data in terrestrial mapping), acoustic backscatter, seafloor video, seafloor photography, high-resolution seismic-reflection profiles, and bottom-sediment sampling data. The map products display seafloor morphology and character, identify potential marine benthic habitats, and illustrate both the surficial seafloor geology and shallow (to about 100 m) subsurface geology. It is emphasized that the more interpretive habitat and geology data rely on the integration of multiple, new high-resolution datasets and that mapping at small scales would not be possible without such data. This approach and CSMP planning is based in part on recommendations of the Marine Mapping Planning Workshop (Kvitek and others, 2006), attended by coastal and marine managers and scientists from around the state. That workshop established geographic priorities for a coastal mapping project and identified the need for coverage of “lands” from the shore strand line (defined as Mean Higher High Water; MHHW) out to the 3-nautical-mile (5.6-km) limit of California’s State Waters. Unfortunately, surveying the zone from MHHW out to 10-m water depth is not consistently possible using ship-based surveying methods, owing to sea state (for example, waves, wind, or currents), kelp coverage, and shallow rock outcrops. Accordingly, some of the data presented in this series commonly do not cover the zone from the shore out to 10-m depth. These data are a part of a series of online U.S. Geological Survey (USGS) publications, each of which includes several map sheets, some explanatory text, and a descriptive pamphlet. Each map sheet is published as a PDF file. Geographic information system (GIS) files that contain both ESRI ArcGIS raster grids (for example, bathymetry, seafloor character) and geotiffs (for example, shaded relief) are also included for each publication. For those who do not own the full suite of ESRI GIS and mapping software, the data can be read using ESRI ArcReader, a free viewer that is available at http://www.esri.com/software/arcgis/arcreader/index.html (last accessed September 20, 2013). The California Seafloor Mapping Program is a collaborative venture between numerous different federal and state agencies, academia, and the private sector. CSMP partners include the California Coastal Conservancy, the California Ocean Protection Council, the California Department of Fish and Wildlife, the California Geological Survey, California State University at Monterey Bay’s Seafloor Mapping Lab, Moss Landing Marine Laboratories Center for Habitat Studies, Fugro Pelagos, Pacific Gas and Electric Company, National Oceanic and Atmospheric Administration (NOAA, including National Ocean Service–Office of Coast Surveys, National Marine Sanctuaries, and National Marine Fisheries Service), U.S. Army Corps of Engineers, the Bureau of Ocean Energy Management, the National Park Service, and the U.S. Geological Survey. These web services for the Offshore Pigeon Point map area includes data layers that are associated to GIS and map sheets available from the USGS CSMP web page at https://cmgds.marine.usgs.gov/data/csmp/OffshorePigeonPoint/data_catalog_OffshorePigeonPoint.html. Each published CSMP map area includes a data catalog of geographic information system (GIS) files; map sheets that contain explanatory text; and an associated descriptive pamphlet. This web service represents the available data layers for this map area. Data was combined from different sonar surveys to generate a comprehensive high-resolution bathymetry and acoustic-backscatter coverage of the map area. These data reveal a range of physiographic including exposed bedrock outcrops, large fields of sand waves, as well as many human impacts on the seafloor. To validate geological and biological interpretations of the sonar data, the U.S. Geological Survey towed a camera sled over specific offshore locations, collecting both video and photographic imagery; these “ground-truth” surveying data are available from the CSMP Video and Photograph Portal at https://doi.org/10.5066/F7J1015K. The “seafloor character” data layer shows classifications of the seafloor on the basis of depth, slope, rugosity (ruggedness), and backscatter intensity and which is further informed by the ground-truth-survey imagery. The “potential habitats” polygons are delineated on the basis of substrate type, geomorphology, seafloor process, or other attributes that may provide a habitat for a specific species or assemblage of organisms. Representative seismic-reflection profile data from the map area is also include and provides information on the subsurface stratigraphy and structure of the map area. The distribution and thickness of young sediment (deposited over the past about 21,000 years, during the most recent sea-level rise) is interpreted on the basis of the seismic-reflection data. The geologic polygons merge onshore geologic mapping (compiled from existing maps by the California Geological Survey) and new offshore geologic mapping that is based on integration of high-resolution bathymetry and backscatter imagery seafloor-sediment and rock samples, digital camera and video imagery, and high-resolution seismic-reflection profiles. The information provided by the map sheets, pamphlet, and data catalog has a broad range of applications. High-resolution bathymetry, acoustic backscatter, ground-truth-surveying imagery, and habitat mapping all contribute to habitat characterization and ecosystem-based management by providing essential data for delineation of marine protected areas and ecosystem restoration. Many of the maps provide high-resolution baselines that will be critical for monitoring environmental change associated with climate change, coastal development, or other forcings. High-resolution bathymetry is a critical component for modeling coastal flooding caused by storms and tsunamis, as well as inundation associated with longer term sea-level rise. Seismic-reflection and bathymetric data help characterize earthquake and tsunami sources, critical for natural-hazard assessments of coastal zones. Information on sediment distribution and thickness is essential to the understanding of local and regional sediment transport, as well as the development of regional sediment-management plans. In addition, siting of any new offshore infrastructure (for example, pipelines, cables, or renewable-energy facilities) will depend on high-resolution mapping. Finally, this mapping will both stimulate and enable new scientific research and also raise public awareness of, and education about, coastal environments and issues. Web services were created using an ArcGIS service definition file. The ArcGIS REST service and OGC WMS service include all Offshore Pigeon Point map area data layers. Data layers are symbolized as shown on the associated map sheets for USGS Open-File Report 2015-1232 (https://doi.org/10.3133/ofr20151232).

In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ecosystems as part of the design and proposal process for the establishment of Marine Protected Areas. A focus of CSMP is to map California’s State Waters with consistent methods at a consistent scale. The CSMP approach is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar data (the undersea equivalent of satellite remote-sensing data in terrestrial mapping), acoustic backscatter, seafloor video, seafloor photography, high-resolution seismic-reflection profiles, and bottom-sediment sampling data. The map products display seafloor morphology and character, identify potential marine benthic habitats, and illustrate both the surficial seafloor geology and shallow (to about 100 m) subsurface geology. It is emphasized that the more interpretive habitat and geology data rely on the integration of multiple, new high-resolution datasets and that mapping at small scales would not be possible without such data. This approach and CSMP planning is based in part on recommendations of the Marine Mapping Planning Workshop (Kvitek and others, 2006), attended by coastal and marine managers and scientists from around the state. That workshop established geographic priorities for a coastal mapping project and identified the need for coverage of “lands” from the shore strand line (defined as Mean Higher High Water; MHHW) out to the 3-nautical-mile (5.6-km) limit of California’s State Waters. Unfortunately, surveying the zone from MHHW out to 10-m water depth is not consistently possible using ship-based surveying methods, owing to sea state (for example, waves, wind, or currents), kelp coverage, and shallow rock outcrops. Accordingly, some of the data presented in this series commonly do not cover the zone from the shore out to 10-m depth. This data is part of a series of online U.S. Geological Survey (USGS) publications, each of which includes several map sheets, some explanatory text, and a descriptive pamphlet. Each map sheet is published as a PDF file. Geographic information system (GIS) files that contain both ESRI ArcGIS raster grids (for example, bathymetry, seafloor character) and geotiffs (for example, shaded relief) are also included for each publication. For those who do not own the full suite of ESRI GIS and mapping software, the data can be read using ESRI ArcReader, a free viewer that is available at http://www.esri.com/software/arcgis/arcreader/index.html (last accessed September 20, 2013). The California Seafloor Mapping Program is a collaborative venture between numerous different federal and state agencies, academia, and the private sector. CSMP partners include the California Coastal Conservancy, the California Ocean Protection Council, the California Department of Fish and Wildlife, the California Geological Survey, California State University at Monterey Bay’s Seafloor Mapping Lab, Moss Landing Marine Laboratories Center for Habitat Studies, Fugro Pelagos, Pacific Gas and Electric Company, National Oceanic and Atmospheric Administration (NOAA, including National Ocean Service–Office of Coast Surveys, National Marine Sanctuaries, and National Marine Fisheries Service), U.S. Army Corps of Engineers, the Bureau of Ocean Energy Management, the National Park Service, and the U.S. Geological Survey. These web services for the Point Conception to Hueneme Canyon map area includes data layers that are associated to GIS and map sheets available from the USGS CSMP web page at https://walrus.wr.usgs.gov/mapping/csmp/index.html. Each published CSMP map area includes a data catalog of geographic information system (GIS) files; map sheets that contain explanatory text; and an associated descriptive pamphlet. This web service represents the available data layers for this map area. Data was combined from different sonar surveys to generate a comprehensive high-resolution bathymetry and acoustic-backscatter coverage of the map area. These data reveal a range of physiographic including exposed bedrock outcrops, large fields of sand waves, as well as many human impacts on the seafloor. To validate geological and biological interpretations of the sonar data, the U.S. Geological Survey towed a camera sled over specific offshore locations, collecting both video and photographic imagery; these “ground-truth” surveying data are available from the CSMP Video and Photograph Portal at https://doi.org/10.5066/F7J1015K. The “seafloor character” data layer shows classifications of the seafloor on the basis of depth, slope, rugosity (ruggedness), and backscatter intensity and which is further informed by the ground-truth-survey imagery. The “potential habitats” polygons are delineated on the basis of substrate type, geomorphology, seafloor process, or other attributes that may provide a habitat for a specific species or assemblage of organisms. Representative seismic-reflection profile data from the map area is also include and provides information on the subsurface stratigraphy and structure of the map area. The distribution and thickness of young sediment (deposited over the past about 21,000 years, during the most recent sea-level rise) is interpreted on the basis of the seismic-reflection data. The geologic polygons merge onshore geologic mapping (compiled from existing maps by the California Geological Survey) and new offshore geologic mapping that is based on integration of high-resolution bathymetry and backscatter imagery seafloor-sediment and rock samplesdigital camera and video imagery, and high-resolution seismic-reflection profiles. The information provided by the map sheets, pamphlet, and data catalog has a broad range of applications. High-resolution bathymetry, acoustic backscatter, ground-truth-surveying imagery, and habitat mapping all contribute to habitat characterization and ecosystem-based management by providing essential data for delineation of marine protected areas and ecosystem restoration. Many of the maps provide high-resolution baselines that will be critical for monitoring environmental change associated with climate change, coastal development, or other forcings. High-resolution bathymetry is a critical component for modeling coastal flooding caused by storms and tsunamis, as well as inundation associated with longer term sea-level rise. Seismic-reflection and bathymetric data help characterize earthquake and tsunami sources, critical for natural-hazard assessments of coastal zones. Information on sediment distribution and thickness is essential to the understanding of local and regional sediment transport, as well as the development of regional sediment-management plans. In addition, siting of any new offshore infrastructure (for example, pipelines, cables, or renewable-energy facilities) will depend on high-resolution mapping. Finally, this mapping will both stimulate and enable new scientific research and also raise public awareness of, and education about, coastal environments and issues. Web services were created using an ArcGIS service definition file. The ArcGIS REST service and OGC WMS service include all Point Conception to Hueneme Canyon map area data layers. Data layers are symbolized as shown on the associated map sheets.

In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ecosystems as part of the design and proposal process for the establishment of Marine Protected Areas. A focus of CSMP is to map California’s State Waters with consistent methods at a consistent scale. The CSMP approach is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar data (the undersea equivalent of satellite remote-sensing data in terrestrial mapping), acoustic backscatter, seafloor video, seafloor photography, high-resolution seismic-reflection profiles, and bottom-sediment sampling data. The map products display seafloor morphology and character, identify potential marine benthic habitats, and illustrate both the surficial seafloor geology and shallow (to about 100 m) subsurface geology. It is emphasized that the more interpretive habitat and geology data rely on the integration of multiple, new high-resolution datasets and that mapping at small scales would not be possible without such data. This approach and CSMP planning is based in part on recommendations of the Marine Mapping Planning Workshop (Kvitek and others, 2006), attended by coastal and marine managers and scientists from around the state. That workshop established geographic priorities for a coastal mapping project and identified the need for coverage of “lands” from the shore strand line (defined as Mean Higher High Water; MHHW) out to the 3-nautical-mile (5.6-km) limit of California’s State Waters. Unfortunately, surveying the zone from MHHW out to 10-m water depth is not consistently possible using ship-based surveying methods, owing to sea state (for example, waves, wind, or currents), kelp coverage, and shallow rock outcrops. Accordingly, some of the data presented in this series commonly do not cover the zone from the shore out to 10-m depth. These data are a part of a series of online U.S. Geological Survey (USGS) publications, each of which includes several map sheets, some explanatory text, and a descriptive pamphlet. Each map sheet is published as a PDF file. Geographic information system (GIS) files that contain both ESRI ArcGIS raster grids (for example, bathymetry, seafloor character) and geotiffs (for example, shaded relief) are also included for each publication. For those who do not own the full suite of ESRI GIS and mapping software, the data can be read using ESRI ArcReader, a free viewer that is available at http://www.esri.com/software/arcgis/arcreader/index.html (last accessed September 20, 2013). The California Seafloor Mapping Program is a collaborative venture between numerous different federal and state agencies, academia, and the private sector. CSMP partners include the California Coastal Conservancy, the California Ocean Protection Council, the California Department of Fish and Wildlife, the California Geological Survey, California State University at Monterey Bay’s Seafloor Mapping Lab, Moss Landing Marine Laboratories Center for Habitat Studies, Fugro Pelagos, Pacific Gas and Electric Company, National Oceanic and Atmospheric Administration (NOAA, including National Ocean Service–Office of Coast Surveys, National Marine Sanctuaries, and National Marine Fisheries Service), U.S. Army Corps of Engineers, the Bureau of Ocean Energy Management, the National Park Service, and the U.S. Geological Survey. These web services for the Offshore Scott Creek map area includes data layers that are associated to GIS and map sheets available from the USGS CSMP web page at https://cmgds.marine.usgs.gov/data/csmp/OffshoreScottCreek/data_catalog_OffshoreScottCreek.html. Each published CSMP map area includes a data catalog of geographic information system (GIS) files; map sheets that contain explanatory text; and an associated descriptive pamphlet. This web service represents the available data layers for this map area. Data was combined from different sonar surveys to generate a comprehensive high-resolution bathymetry and acoustic-backscatter coverage of the map area. These data reveal a range of physiographic including exposed bedrock outcrops, large fields of sand waves, as well as many human impacts on the seafloor. To validate geological and biological interpretations of the sonar data, the U.S. Geological Survey towed a camera sled over specific offshore locations, collecting both video and photographic imagery; these “ground-truth” surveying data are available from the CSMP Video and Photograph Portal at https://doi.org/10.5066/F7J1015K. The “seafloor character” data layer shows classifications of the seafloor on the basis of depth, slope, rugosity (ruggedness), and backscatter intensity and which is further informed by the ground-truth-survey imagery. The “potential habitats” polygons are delineated on the basis of substrate type, geomorphology, seafloor process, or other attributes that may provide a habitat for a specific species or assemblage of organisms. Representative seismic-reflection profile data from the map area is also include and provides information on the subsurface stratigraphy and structure of the map area. The distribution and thickness of young sediment (deposited over the past about 21,000 years, during the most recent sea-level rise) is interpreted on the basis of the seismic-reflection data. The geologic polygons merge onshore geologic mapping (compiled from existing maps by the California Geological Survey) and new offshore geologic mapping that is based on integration of high-resolution bathymetry and backscatter imagery seafloor-sediment and rock samples, digital camera and video imagery, and high-resolution seismic-reflection profiles. The information provided by the map sheets, pamphlet, and data catalog has a broad range of applications. High-resolution bathymetry, acoustic backscatter, ground-truth-surveying imagery, and habitat mapping all contribute to habitat characterization and ecosystem-based management by providing essential data for delineation of marine protected areas and ecosystem restoration. Many of the maps provide high-resolution baselines that will be critical for monitoring environmental change associated with climate change, coastal development, or other forcings. High-resolution bathymetry is a critical component for modeling coastal flooding caused by storms and tsunamis, as well as inundation associated with longer term sea-level rise. Seismic-reflection and bathymetric data help characterize earthquake and tsunami sources, critical for natural-hazard assessments of coastal zones. Information on sediment distribution and thickness is essential to the understanding of local and regional sediment transport, as well as the development of regional sediment-management plans. In addition, siting of any new offshore infrastructure (for example, pipelines, cables, or renewable-energy facilities) will depend on high-resolution mapping. Finally, this mapping will both stimulate and enable new scientific research and also raise public awareness of, and education about, coastal environments and issues. Web services were created using an ArcGIS service definition file. The ArcGIS REST service and OGC WMS service include all Offshore Pigeon Point map area data layers. Data layers are symbolized as shown on the associated map sheets for USGS Open-File Report 2015-1232 (https://doi.org/10.3133/ofr20151232).

In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ecosystems as part of the design and proposal process for the establishment of Marine Protected Areas. A focus of CSMP is to map California’s State Waters with consistent methods at a consistent scale. The CSMP approach is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar data (the undersea equivalent of satellite remote-sensing data in terrestrial mapping), acoustic backscatter, seafloor video, seafloor photography, high-resolution seismic-reflection profiles, and bottom-sediment sampling data. The map products display seafloor morphology and character, identify potential marine benthic habitats, and illustrate both the surficial seafloor geology and shallow (to about 100 m) subsurface geology. It is emphasized that the more interpretive habitat and geology data rely on the integration of multiple, new high-resolution datasets and that mapping at small scales would not be possible without such data. This approach and CSMP planning is based in part on recommendations of the Marine Mapping Planning Workshop (Kvitek and others, 2006), attended by coastal and marine managers and scientists from around the state. That workshop established geographic priorities for a coastal mapping project and identified the need for coverage of “lands” from the shore strand line (defined as Mean Higher High Water; MHHW) out to the 3-nautical-mile (5.6-km) limit of California’s State Waters. Unfortunately, surveying the zone from MHHW out to 10-m water depth is not consistently possible using ship-based surveying methods, owing to sea state (for example, waves, wind, or currents), kelp coverage, and shallow rock outcrops. Accordingly, some of the data presented in this series commonly do not cover the zone from the shore out to 10-m depth. These data are a part of a series of online U.S. Geological Survey (USGS) publications, each of which includes several map sheets, some explanatory text, and a descriptive pamphlet. Each map sheet is published as a PDF file. Geographic information system (GIS) files that contain both ESRI ArcGIS raster grids (for example, bathymetry, seafloor character) and geotiffs (for example, shaded relief) are also included for each publication. For those who do not own the full suite of ESRI GIS and mapping software, the data can be read using ESRI ArcReader, a free viewer that is available at http://www.esri.com/software/arcgis/arcreader/index.html (last accessed September 20, 2013). The California Seafloor Mapping Program is a collaborative venture between numerous different federal and state agencies, academia, and the private sector. CSMP partners include the California Coastal Conservancy, the California Ocean Protection Council, the California Department of Fish and Wildlife, the California Geological Survey, California State University at Monterey Bay’s Seafloor Mapping Lab, Moss Landing Marine Laboratories Center for Habitat Studies, Fugro Pelagos, Pacific Gas and Electric Company, National Oceanic and Atmospheric Administration (NOAA, including National Ocean Service–Office of Coast Surveys, National Marine Sanctuaries, and National Marine Fisheries Service), U.S. Army Corps of Engineers, the Bureau of Ocean Energy Management, the National Park Service, and the U.S. Geological Survey. These web services for the Offshore Aptos map area includes data layers that are associated to GIS and map sheets available from the USGS CSMP web page at https://cmgds.marine.usgs.gov/data/csmp/OffshoreAptos/data_catalog_OffshoreAptos.html. Each published CSMP map area includes a data catalog of geographic information system (GIS) files; map sheets that contain explanatory text; and an associated descriptive pamphlet. This web service represents the available data layers for this map area. Data was combined from different sonar surveys to generate a comprehensive high-resolution bathymetry and acoustic-backscatter coverage of the map area. These data reveal a range of physiographic including exposed bedrock outcrops, large fields of sand waves, as well as many human impacts on the seafloor. To validate geological and biological interpretations of the sonar data, the U.S. Geological Survey towed a camera sled over specific offshore locations, collecting both video and photographic imagery; these “ground-truth” surveying data are available from the CSMP Video and Photograph Portal at https://doi.org/10.5066/F7J1015K. The “seafloor character” data layer shows classifications of the seafloor on the basis of depth, slope, rugosity (ruggedness), and backscatter intensity and which is further informed by the ground-truth-survey imagery. The “potential habitats” polygons are delineated on the basis of substrate type, geomorphology, seafloor process, or other attributes that may provide a habitat for a specific species or assemblage of organisms. Representative seismic-reflection profile data from the map area is also include and provides information on the subsurface stratigraphy and structure of the map area. The distribution and thickness of young sediment (deposited over the past about 21,000 years, during the most recent sea-level rise) is interpreted on the basis of the seismic-reflection data. The geologic polygons merge onshore geologic mapping (compiled from existing maps by the California Geological Survey) and new offshore geologic mapping that is based on integration of high-resolution bathymetry and backscatter imagery seafloor-sediment and rock samples, digital camera and video imagery, and high-resolution seismic-reflection profiles. The information provided by the map sheets, pamphlet, and data catalog has a broad range of applications. High-resolution bathymetry, acoustic backscatter, ground-truth-surveying imagery, and habitat mapping all contribute to habitat characterization and ecosystem-based management by providing essential data for delineation of marine protected areas and ecosystem restoration. Many of the maps provide high-resolution baselines that will be critical for monitoring environmental change associated with climate change, coastal development, or other forcings. High-resolution bathymetry is a critical component for modeling coastal flooding caused by storms and tsunamis, as well as inundation associated with longer term sea-level rise. Seismic-reflection and bathymetric data help characterize earthquake and tsunami sources, critical for natural-hazard assessments of coastal zones. Information on sediment distribution and thickness is essential to the understanding of local and regional sediment transport, as well as the development of regional sediment-management plans. In addition, siting of any new offshore infrastructure (for example, pipelines, cables, or renewable-energy facilities) will depend on high-resolution mapping. Finally, this mapping will both stimulate and enable new scientific research and also raise public awareness of, and education about, coastal environments and issues. Web services were created using an ArcGIS service definition file. The ArcGIS REST service and OGC WMS service include all Offshore Pigeon Point map area data layers. Data layers are symbolized as shown on the associated map sheets for USGS Open-File Report 2015-1232 (https://doi.org/10.3133/ofr20151232).

In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ecosystems as part of the design and proposal process for the establishment of Marine Protected Areas. A focus of CSMP is to map California’s State Waters with consistent methods at a consistent scale. The CSMP approach is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar data (the undersea equivalent of satellite remote-sensing data in terrestrial mapping), acoustic backscatter, seafloor video, seafloor photography, high-resolution seismic-reflection profiles, and bottom-sediment sampling data. The map products display seafloor morphology and character, identify potential marine benthic habitats, and illustrate both the surficial seafloor geology and shallow (to about 100 m) subsurface geology. It is emphasized that the more interpretive habitat and geology data rely on the integration of multiple, new high-resolution datasets and that mapping at small scales would not be possible without such data. This approach and CSMP planning is based in part on recommendations of the Marine Mapping Planning Workshop (Kvitek and others, 2006), attended by coastal and marine managers and scientists from around the state. That workshop established geographic priorities for a coastal mapping project and identified the need for coverage of “lands” from the shore strand line (defined as Mean Higher High Water; MHHW) out to the 3-nautical-mile (5.6-km) limit of California’s State Waters. Unfortunately, surveying the zone from MHHW out to 10-m water depth is not consistently possible using ship-based surveying methods, owing to sea state (for example, waves, wind, or currents), kelp coverage, and shallow rock outcrops. Accordingly, some of the data presented in this series commonly do not cover the zone from the shore out to 10-m depth. This data is part of a series of online U.S. Geological Survey (USGS) publications, each of which includes several map sheets, some explanatory text, and a descriptive pamphlet. Each map sheet is published as a PDF file. Geographic information system (GIS) files that contain both ESRI ArcGIS raster grids (for example, bathymetry, seafloor character) and geotiffs (for example, shaded relief) are also included for each publication. For those who do not own the full suite of ESRI GIS and mapping software, the data can be read using ESRI ArcReader, a free viewer that is available at http://www.esri.com/software/arcgis/arcreader/index.html (last accessed September 20, 2013). The California Seafloor Mapping Program is a collaborative venture between numerous different federal and state agencies, academia, and the private sector. CSMP partners include the California Coastal Conservancy, the California Ocean Protection Council, the California Department of Fish and Wildlife, the California Geological Survey, California State University at Monterey Bay’s Seafloor Mapping Lab, Moss Landing Marine Laboratories Center for Habitat Studies, Fugro Pelagos, Pacific Gas and Electric Company, National Oceanic and Atmospheric Administration (NOAA, including National Ocean Service–Office of Coast Surveys, National Marine Sanctuaries, and National Marine Fisheries Service), U.S. Army Corps of Engineers, the Bureau of Ocean Energy Management, the National Park Service, and the U.S. Geological Survey. These web services for the Pigeon Point to Monterey map area includes data layers that are associated to GIS and map sheets available from the USGS CSMP web page at https://walrus.wr.usgs.gov/mapping/csmp/index.html. Each published CSMP map area includes a data catalog of geographic information system (GIS) files; map sheets that contain explanatory text; and an associated descriptive pamphlet. This web service represents the available data layers for this map area. Data was combined from different sonar surveys to generate a comprehensive high-resolution bathymetry and acoustic-backscatter coverage of the map area. These data reveal a range of physiographic including exposed bedrock outcrops, large fields of sand waves, as well as many human impacts on the seafloor. To validate geological and biological interpretations of the sonar data, the U.S. Geological Survey towed a camera sled over specific offshore locations, collecting both video and photographic imagery; these “ground-truth” surveying data are available from the CSMP Video and Photograph Portal at https://doi.org/10.5066/F7J1015K. The “seafloor character” data layer shows classifications of the seafloor on the basis of depth, slope, rugosity (ruggedness), and backscatter intensity and which is further informed by the ground-truth-survey imagery. The “potential habitats” polygons are delineated on the basis of substrate type, geomorphology, seafloor process, or other attributes that may provide a habitat for a specific species or assemblage of organisms. Representative seismic-reflection profile data from the map area is also include and provides information on the subsurface stratigraphy and structure of the map area. The distribution and thickness of young sediment (deposited over the past about 21,000 years, during the most recent sea-level rise) is interpreted on the basis of the seismic-reflection data. The geologic polygons merge onshore geologic mapping (compiled from existing maps by the California Geological Survey) and new offshore geologic mapping that is based on integration of high-resolution bathymetry and backscatter imagery seafloor-sediment and rock samplesdigital camera and video imagery, and high-resolution seismic-reflection profiles. The information provided by the map sheets, pamphlet, and data catalog has a broad range of applications. High-resolution bathymetry, acoustic backscatter, ground-truth-surveying imagery, and habitat mapping all contribute to habitat characterization and ecosystem-based management by providing essential data for delineation of marine protected areas and ecosystem restoration. Many of the maps provide high-resolution baselines that will be critical for monitoring environmental change associated with climate change, coastal development, or other forcings. High-resolution bathymetry is a critical component for modeling coastal flooding caused by storms and tsunamis, as well as inundation associated with longer term sea-level rise. Seismic-reflection and bathymetric data help characterize earthquake and tsunami sources, critical for natural-hazard assessments of coastal zones. Information on sediment distribution and thickness is essential to the understanding of local and regional sediment transport, as well as the development of regional sediment-management plans. In addition, siting of any new offshore infrastructure (for example, pipelines, cables, or renewable-energy facilities) will depend on high-resolution mapping. Finally, this mapping will both stimulate and enable new scientific research and also raise public awareness of, and education about, coastal environments and issues. Web services were created using an ArcGIS service definition file. The ArcGIS REST service and OGC WMS service include all Pigeon Point to Monterey map area data layers. Data layers are symbolized as shown on the associated map sheets.

In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ecosystems as part of the design and proposal process for the establishment of Marine Protected Areas. A focus of CSMP is to map California’s State Waters with consistent methods at a consistent scale. The CSMP approach is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar data (the undersea equivalent of satellite remote-sensing data in terrestrial mapping), acoustic backscatter, seafloor video, seafloor photography, high-resolution seismic-reflection profiles, and bottom-sediment sampling data. The map products display seafloor morphology and character, identify potential marine benthic habitats, and illustrate both the surficial seafloor geology and shallow (to about 100 m) subsurface geology. It is emphasized that the more interpretive habitat and geology data rely on the integration of multiple, new high-resolution datasets and that mapping at small scales would not be possible without such data. This approach and CSMP planning is based in part on recommendations of the Marine Mapping Planning Workshop (Kvitek and others, 2006), attended by coastal and marine managers and scientists from around the state. That workshop established geographic priorities for a coastal mapping project and identified the need for coverage of “lands” from the shore strand line (defined as Mean Higher High Water; MHHW) out to the 3-nautical-mile (5.6-km) limit of California’s State Waters. Unfortunately, surveying the zone from MHHW out to 10-m water depth is not consistently possible using ship-based surveying methods, owing to sea state (for example, waves, wind, or currents), kelp coverage, and shallow rock outcrops. Accordingly, some of the data presented in this series commonly do not cover the zone from the shore out to 10-m depth. This data is part of a series of online U.S. Geological Survey (USGS) publications, each of which includes several map sheets, some explanatory text, and a descriptive pamphlet. Each map sheet is published as a PDF file. Geographic information system (GIS) files that contain both ESRI ArcGIS raster grids (for example, bathymetry, seafloor character) and geotiffs (for example, shaded relief) are also included for each publication. For those who do not own the full suite of ESRI GIS and mapping software, the data can be read using ESRI ArcReader, a free viewer that is available at http://www.esri.com/software/arcgis/arcreader/index.html (last accessed September 20, 2013). The California Seafloor Mapping Program is a collaborative venture between numerous different federal and state agencies, academia, and the private sector. CSMP partners include the California Coastal Conservancy, the California Ocean Protection Council, the California Department of Fish and Wildlife, the California Geological Survey, California State University at Monterey Bay’s Seafloor Mapping Lab, Moss Landing Marine Laboratories Center for Habitat Studies, Fugro Pelagos, Pacific Gas and Electric Company, National Oceanic and Atmospheric Administration (NOAA, including National Ocean Service–Office of Coast Surveys, National Marine Sanctuaries, and National Marine Fisheries Service), U.S. Army Corps of Engineers, the Bureau of Ocean Energy Management, the National Park Service, and the U.S. Geological Survey. These web services for the Offshore of Point Conception map area includes data layers that are associated to GIS and map sheets available from the USGS CSMP web page at https://walrus.wr.usgs.gov/mapping/csmp/index.html. Each published CSMP map area includes a data catalog of geographic information system (GIS) files; map sheets that contain explanatory text; and an associated descriptive pamphlet. This web service represents the available data layers for this map area. Data was combined from different sonar surveys to generate a comprehensive high-resolution bathymetry and acoustic-backscatter coverage of the map area. These data reveal a range of physiographic including exposed bedrock outcrops, large fields of sand waves, as well as many human impacts on the seafloor. To validate geological and biological interpretations of the sonar data, the U.S. Geological Survey towed a camera sled over specific offshore locations, collecting both video and photographic imagery; these “ground-truth” surveying data are available from the CSMP Video and Photograph Portal at https://doi.org/10.5066/F7J1015K. The “seafloor character” data layer shows classifications of the seafloor on the basis of depth, slope, rugosity (ruggedness), and backscatter intensity and which is further informed by the ground-truth-survey imagery. The “potential habitats” polygons are delineated on the basis of substrate type, geomorphology, seafloor process, or other attributes that may provide a habitat for a specific species or assemblage of organisms. Representative seismic-reflection profile data from the map area is also include and provides information on the subsurface stratigraphy and structure of the map area. The distribution and thickness of young sediment (deposited over the past about 21,000 years, during the most recent sea-level rise) is interpreted on the basis of the seismic-reflection data. The geologic polygons merge onshore geologic mapping (compiled from existing maps by the California Geological Survey) and new offshore geologic mapping that is based on integration of high-resolution bathymetry and backscatter imagery seafloor-sediment and rock samplesdigital camera and video imagery, and high-resolution seismic-reflection profiles. The information provided by the map sheets, pamphlet, and data catalog has a broad range of applications. High-resolution bathymetry, acoustic backscatter, ground-truth-surveying imagery, and habitat mapping all contribute to habitat characterization and ecosystem-based management by providing essential data for delineation of marine protected areas and ecosystem restoration. Many of the maps provide high-resolution baselines that will be critical for monitoring environmental change associated with climate change, coastal development, or other forcings. High-resolution bathymetry is a critical component for modeling coastal flooding caused by storms and tsunamis, as well as inundation associated with longer term sea-level rise. Seismic-reflection and bathymetric data help characterize earthquake and tsunami sources, critical for natural-hazard assessments of coastal zones. Information on sediment distribution and thickness is essential to the understanding of local and regional sediment transport, as well as the development of regional sediment-management plans. In addition, siting of any new offshore infrastructure (for example, pipelines, cables, or renewable-energy facilities) will depend on high-resolution mapping. Finally, this mapping will both stimulate and enable new scientific research and also raise public awareness of, and education about, coastal environments and issues. Web services were created using an ArcGIS service definition file. The ArcGIS REST service and OGC WMS service include all Offshore of Point Conception map area data layers. Data layers are symbolized as shown on the associated map sheets.

In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ecosystems as part of the design and proposal process for the establishment of Marine Protected Areas. A focus of CSMP is to map California’s State Waters with consistent methods at a consistent scale. The CSMP approach is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar data (the undersea equivalent of satellite remote-sensing data in terrestrial mapping), acoustic backscatter, seafloor video, seafloor photography, high-resolution seismic-reflection profiles, and bottom-sediment sampling data. The map products display seafloor morphology and character, identify potential marine benthic habitats, and illustrate both the surficial seafloor geology and shallow (to about 100 m) subsurface geology. It is emphasized that the more interpretive habitat and geology data rely on the integration of multiple, new high-resolution datasets and that mapping at small scales would not be possible without such data. This approach and CSMP planning is based in part on recommendations of the Marine Mapping Planning Workshop (Kvitek and others, 2006), attended by coastal and marine managers and scientists from around the state. That workshop established geographic priorities for a coastal mapping project and identified the need for coverage of “lands” from the shore strand line (defined as Mean Higher High Water; MHHW) out to the 3-nautical-mile (5.6-km) limit of California’s State Waters. Unfortunately, surveying the zone from MHHW out to 10-m water depth is not consistently possible using ship-based surveying methods, owing to sea state (for example, waves, wind, or currents), kelp coverage, and shallow rock outcrops. Accordingly, some of the data presented in this series commonly do not cover the zone from the shore out to 10-m depth. This data is part of a series of online U.S. Geological Survey (USGS) publications, each of which includes several map sheets, some explanatory text, and a descriptive pamphlet. Each map sheet is published as a PDF file. Geographic information system (GIS) files that contain both ESRI ArcGIS raster grids (for example, bathymetry, seafloor character) and geotiffs (for example, shaded relief) are also included for each publication. For those who do not own the full suite of ESRI GIS and mapping software, the data can be read using ESRI ArcReader, a free viewer that is available at http://www.esri.com/software/arcgis/arcreader/index.html (last accessed September 20, 2013). The California Seafloor Mapping Program is a collaborative venture between numerous different federal and state agencies, academia, and the private sector. CSMP partners include the California Coastal Conservancy, the California Ocean Protection Council, the California Department of Fish and Wildlife, the California Geological Survey, California State University at Monterey Bay’s Seafloor Mapping Lab, Moss Landing Marine Laboratories Center for Habitat Studies, Fugro Pelagos, Pacific Gas and Electric Company, National Oceanic and Atmospheric Administration (NOAA, including National Ocean Service–Office of Coast Surveys, National Marine Sanctuaries, and National Marine Fisheries Service), U.S. Army Corps of Engineers, the Bureau of Ocean Energy Management, the National Park Service, and the U.S. Geological Survey. These web services for the Offshore of Gaviota map area includes data layers that are associated to GIS and map sheets available from the USGS CSMP web page at https://walrus.wr.usgs.gov/mapping/csmp/index.html. Each published CSMP map area includes a data catalog of geographic information system (GIS) files; map sheets that contain explanatory text; and an associated descriptive pamphlet. This web service represents the available data layers for this map area. Data was combined from different sonar surveys to generate a comprehensive high-resolution bathymetry and acoustic-backscatter coverage of the map area. These data reveal a range of physiographic including exposed bedrock outcrops, large fields of sand waves, as well as many human impacts on the seafloor. To validate geological and biological interpretations of the sonar data, the U.S. Geological Survey towed a camera sled over specific offshore locations, collecting both video and photographic imagery; these “ground-truth” surveying data are available from the CSMP Video and Photograph Portal at https://doi.org/10.5066/F7J1015K. The “seafloor character” data layer shows classifications of the seafloor on the basis of depth, slope, rugosity (ruggedness), and backscatter intensity and which is further informed by the ground-truth-survey imagery. The “potential habitats” polygons are delineated on the basis of substrate type, geomorphology, seafloor process, or other attributes that may provide a habitat for a specific species or assemblage of organisms. Representative seismic-reflection profile data from the map area is also include and provides information on the subsurface stratigraphy and structure of the map area. The distribution and thickness of young sediment (deposited over the past about 21,000 years, during the most recent sea-level rise) is interpreted on the basis of the seismic-reflection data. The geologic polygons merge onshore geologic mapping (compiled from existing maps by the California Geological Survey) and new offshore geologic mapping that is based on integration of high-resolution bathymetry and backscatter imagery seafloor-sediment and rock samples, digital camera and video imagery, and high-resolution seismic-reflection profiles. The information provided by the map sheets, pamphlet, and data catalog has a broad range of applications. High-resolution bathymetry, acoustic backscatter, ground-truth-surveying imagery, and habitat mapping all contribute to habitat characterization and ecosystem-based management by providing essential data for delineation of marine protected areas and ecosystem restoration. Many of the maps provide high-resolution baselines that will be critical for monitoring environmental change associated with climate change, coastal development, or other forcings. High-resolution bathymetry is a critical component for modeling coastal flooding caused by storms and tsunamis, as well as inundation associated with longer term sea-level rise. Seismic-reflection and bathymetric data help characterize earthquake and tsunami sources, critical for natural-hazard assessments of coastal zones. Information on sediment distribution and thickness is essential to the understanding of local and regional sediment transport, as well as the development of regional sediment-management plans. In addition, siting of any new offshore infrastructure (for example, pipelines, cables, or renewable-energy facilities) will depend on high-resolution mapping. Finally, this mapping will both stimulate and enable new scientific research and also raise public awareness of, and education about, coastal environments and issues. Web services were created using an ArcGIS service definition file. The ArcGIS REST service and OGC WMS service include all Offshore of Gaviota map area data layers. Data layers are symbolized as shown on the associated map sheets.

In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ecosystems as part of the design and proposal process for the establishment of Marine Protected Areas. A focus of CSMP is to map California’s State Waters with consistent methods at a consistent scale. The CSMP approach is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar data (the undersea equivalent of satellite remote-sensing data in terrestrial mapping), acoustic backscatter, seafloor video, seafloor photography, high-resolution seismic-reflection profiles, and bottom-sediment sampling data. The map products display seafloor morphology and character, identify potential marine benthic habitats, and illustrate both the surficial seafloor geology and shallow (to about 100 m) subsurface geology. It is emphasized that the more interpretive habitat and geology data rely on the integration of multiple, new high-resolution datasets and that mapping at small scales would not be possible without such data. This approach and CSMP planning is based in part on recommendations of the Marine Mapping Planning Workshop (Kvitek and others, 2006), attended by coastal and marine managers and scientists from around the state. That workshop established geographic priorities for a coastal mapping project and identified the need for coverage of “lands” from the shore strand line (defined as Mean Higher High Water; MHHW) out to the 3-nautical-mile (5.6-km) limit of California’s State Waters. Unfortunately, surveying the zone from MHHW out to 10-m water depth is not consistently possible using ship-based surveying methods, owing to sea state (for example, waves, wind, or currents), kelp coverage, and shallow rock outcrops. Accordingly, some of the data presented in this series commonly do not cover the zone from the shore out to 10-m depth. This data is part of a series of online U.S. Geological Survey (USGS) publications, each of which includes several map sheets, some explanatory text, and a descriptive pamphlet. Each map sheet is published as a PDF file. Geographic information system (GIS) files that contain both ESRI ArcGIS raster grids (for example, bathymetry, seafloor character) and geotiffs (for example, shaded relief) are also included for each publication. For those who do not own the full suite of ESRI GIS and mapping software, the data can be read using ESRI ArcReader, a free viewer that is available at http://www.esri.com/software/arcgis/arcreader/index.html (last accessed September 20, 2013). The California Seafloor Mapping Program is a collaborative venture between numerous different federal and state agencies, academia, and the private sector. CSMP partners include the California Coastal Conservancy, the California Ocean Protection Council, the California Department of Fish and Wildlife, the California Geological Survey, California State University at Monterey Bay’s Seafloor Mapping Lab, Moss Landing Marine Laboratories Center for Habitat Studies, Fugro Pelagos, Pacific Gas and Electric Company, National Oceanic and Atmospheric Administration (NOAA, including National Ocean Service–Office of Coast Surveys, National Marine Sanctuaries, and National Marine Fisheries Service), U.S. Army Corps of Engineers, the Bureau of Ocean Energy Management, the National Park Service, and the U.S. Geological Survey. These web services for the Offshore of Ventura map area includes data layers that are associated to GIS and map sheets available from the USGS CSMP web page at https://walrus.wr.usgs.gov/mapping/csmp/index.html. Each published CSMP map area includes a data catalog of geographic information system (GIS) files; map sheets that contain explanatory text; and an associated descriptive pamphlet. This web service represents the available data layers for this map area. Data was combined from different sonar surveys to generate a comprehensive high-resolution bathymetry and acoustic-backscatter coverage of the map area. These data reveal a range of physiographic including exposed bedrock outcrops, large fields of sand waves, as well as many human impacts on the seafloor. To validate geological and biological interpretations of the sonar data, the U.S. Geological Survey towed a camera sled over specific offshore locations, collecting both video and photographic imagery; these “ground-truth” surveying data are available from the CSMP Video and Photograph Portal at https://doi.org/10.5066/F7J1015K. The “seafloor character” data layer shows classifications of the seafloor on the basis of depth, slope, rugosity (ruggedness), and backscatter intensity and which is further informed by the ground-truth-survey imagery. The “potential habitats” polygons are delineated on the basis of substrate type, geomorphology, seafloor process, or other attributes that may provide a habitat for a specific species or assemblage of organisms. Representative seismic-reflection profile data from the map area is also include and provides information on the subsurface stratigraphy and structure of the map area. The distribution and thickness of young sediment (deposited over the past about 21,000 years, during the most recent sea-level rise) is interpreted on the basis of the seismic-reflection data. The geologic polygons merge onshore geologic mapping (compiled from existing maps by the California Geological Survey) and new offshore geologic mapping that is based on integration of high-resolution bathymetry and backscatter imagery, seafloor-sediment and rock samples, digital camera and video imagery, and high-resolution seismic-reflection profiles. The information provided by the map sheets, pamphlet, and data catalog has a broad range of applications. High-resolution bathymetry, acoustic backscatter, ground-truth-surveying imagery, and habitat mapping all contribute to habitat characterization and ecosystem-based management by providing essential data for delineation of marine protected areas and ecosystem restoration. Many of the maps provide high-resolution baselines that will be critical for monitoring environmental change associated with climate change, coastal development, or other forcings. High-resolution bathymetry is a critical component for modeling coastal flooding caused by storms and tsunamis, as well as inundation associated with longer term sea-level rise. Seismic-reflection and bathymetric data help characterize earthquake and tsunami sources, critical for natural-hazard assessments of coastal zones. Information on sediment distribution and thickness is essential to the understanding of local and regional sediment transport, as well as the development of regional sediment-management plans. In addition, siting of any new offshore infrastructure (for example, pipelines, cables, or renewable-energy facilities) will depend on high-resolution mapping. Finally, this mapping will both stimulate and enable new scientific research and also raise public awareness of, and education about, coastal environments and issues. Web services were created using an ArcGIS service definition file. The ArcGIS REST service and OGC WMS service include all Monterey Canyon and Vicinity map area data layers. Data layers are symbolized as shown on the associated map sheets.

In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ecosystems as part of the design and proposal process for the establishment of Marine Protected Areas. A focus of CSMP is to map California’s State Waters with consistent methods at a consistent scale. The CSMP approach is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar data (the undersea equivalent of satellite remote-sensing data in terrestrial mapping), acoustic backscatter, seafloor video, seafloor photography, high-resolution seismic-reflection profiles, and bottom-sediment sampling data. The map products display seafloor morphology and character, identify potential marine benthic habitats, and illustrate both the surficial seafloor geology and shallow (to about 100 m) subsurface geology. It is emphasized that the more interpretive habitat and geology data rely on the integration of multiple, new high-resolution datasets and that mapping at small scales would not be possible without such data. This approach and CSMP planning is based in part on recommendations of the Marine Mapping Planning Workshop (Kvitek and others, 2006), attended by coastal and marine managers and scientists from around the state. That workshop established geographic priorities for a coastal mapping project and identified the need for coverage of “lands” from the shore strand line (defined as Mean Higher High Water; MHHW) out to the 3-nautical-mile (5.6-km) limit of California’s State Waters. Unfortunately, surveying the zone from MHHW out to 10-m water depth is not consistently possible using ship-based surveying methods, owing to sea state (for example, waves, wind, or currents), kelp coverage, and shallow rock outcrops. Accordingly, some of the data presented in this series commonly do not cover the zone from the shore out to 10-m depth. This data is part of a series of online U.S. Geological Survey (USGS) publications, each of which includes several map sheets, some explanatory text, and a descriptive pamphlet. Each map sheet is published as a PDF file. Geographic information system (GIS) files that contain both ESRI ArcGIS raster grids (for example, bathymetry, seafloor character) and geotiffs (for example, shaded relief) are also included for each publication. For those who do not own the full suite of ESRI GIS and mapping software, the data can be read using ESRI ArcReader, a free viewer that is available at http://www.esri.com/software/arcgis/arcreader/index.html (last accessed September 20, 2013). The California Seafloor Mapping Program is a collaborative venture between numerous different federal and state agencies, academia, and the private sector. CSMP partners include the California Coastal Conservancy, the California Ocean Protection Council, the California Department of Fish and Wildlife, the California Geological Survey, California State University at Monterey Bay’s Seafloor Mapping Lab, Moss Landing Marine Laboratories Center for Habitat Studies, Fugro Pelagos, Pacific Gas and Electric Company, National Oceanic and Atmospheric Administration (NOAA, including National Ocean Service–Office of Coast Surveys, National Marine Sanctuaries, and National Marine Fisheries Service), U.S. Army Corps of Engineers, the Bureau of Ocean Energy Management, the National Park Service, and the U.S. Geological Survey. These web services for the Point Sur to Point Arguello map area includes data layers that are associated to GIS and map sheets available from the USGS CSMP web page at https://walrus.wr.usgs.gov/mapping/csmp/index.html. Each published CSMP map area includes a data catalog of geographic information system (GIS) files; map sheets that contain explanatory text; and an associated descriptive pamphlet. This web service represents the available data layers for this map area. Data was combined from different sonar surveys to generate a comprehensive high-resolution bathymetry and acoustic-backscatter coverage of the map area. These data reveal a range of physiographic including exposed bedrock outcrops, large fields of sand waves, as well as many human impacts on the seafloor. To validate geological and biological interpretations of the sonar data, the U.S. Geological Survey towed a camera sled over specific offshore locations, collecting both video and photographic imagery; these “ground-truth” surveying data are available from the CSMP Video and Photograph Portal at https://doi.org/10.5066/F7J1015K. The “seafloor character” data layer shows classifications of the seafloor on the basis of depth, slope, rugosity (ruggedness), and backscatter intensity and which is further informed by the ground-truth-survey imagery. The “potential habitats” polygons are delineated on the basis of substrate type, geomorphology, seafloor process, or other attributes that may provide a habitat for a specific species or assemblage of organisms. Representative seismic-reflection profile data from the map area is also include and provides information on the subsurface stratigraphy and structure of the map area. The distribution and thickness of young sediment (deposited over the past about 21,000 years, during the most recent sea-level rise) is interpreted on the basis of the seismic-reflection data. The geologic polygons merge onshore geologic mapping (compiled from existing maps by the California Geological Survey) and new offshore geologic mapping that is based on integration of high-resolution bathymetry and backscatter imagery seafloor-sediment and rock samplesdigital camera and video imagery, and high-resolution seismic-reflection profiles. The information provided by the map sheets, pamphlet, and data catalog has a broad range of applications. High-resolution bathymetry, acoustic backscatter, ground-truth-surveying imagery, and habitat mapping all contribute to habitat characterization and ecosystem-based management by providing essential data for delineation of marine protected areas and ecosystem restoration. Many of the maps provide high-resolution baselines that will be critical for monitoring environmental change associated with climate change, coastal development, or other forcings. High-resolution bathymetry is a critical component for modeling coastal flooding caused by storms and tsunamis, as well as inundation associated with longer term sea-level rise. Seismic-reflection and bathymetric data help characterize earthquake and tsunami sources, critical for natural-hazard assessments of coastal zones. Information on sediment distribution and thickness is essential to the understanding of local and regional sediment transport, as well as the development of regional sediment-management plans. In addition, siting of any new offshore infrastructure (for example, pipelines, cables, or renewable-energy facilities) will depend on high-resolution mapping. Finally, this mapping will both stimulate and enable new scientific research and also raise public awareness of, and education about, coastal environments and issues. Web services were created using an ArcGIS service definition file. The ArcGIS REST service and OGC WMS service include all Point Sur to Point Arguello map area data layers. Data layers are symbolized as shown on the associated map sheets.

In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ecosystems as part of the design and proposal process for the establishment of Marine Protected Areas. A focus of CSMP is to map California’s State Waters with consistent methods at a consistent scale. The CSMP approach is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar data (the undersea equivalent of satellite remote-sensing data in terrestrial mapping), acoustic backscatter, seafloor video, seafloor photography, high-resolution seismic-reflection profiles, and bottom-sediment sampling data. The map products display seafloor morphology and character, identify potential marine benthic habitats, and illustrate both the surficial seafloor geology and shallow (to about 100 m) subsurface geology. It is emphasized that the more interpretive habitat and geology data rely on the integration of multiple, new high-resolution datasets and that mapping at small scales would not be possible without such data. This approach and CSMP planning is based in part on recommendations of the Marine Mapping Planning Workshop (Kvitek and others, 2006), attended by coastal and marine managers and scientists from around the state. That workshop established geographic priorities for a coastal mapping project and identified the need for coverage of “lands” from the shore strand line (defined as Mean Higher High Water; MHHW) out to the 3-nautical-mile (5.6-km) limit of California’s State Waters. Unfortunately, surveying the zone from MHHW out to 10-m water depth is not consistently possible using ship-based surveying methods, owing to sea state (for example, waves, wind, or currents), kelp coverage, and shallow rock outcrops. Accordingly, some of the data presented in this series commonly do not cover the zone from the shore out to 10-m depth. This data is part of a series of online U.S. Geological Survey (USGS) publications, each of which includes several map sheets, some explanatory text, and a descriptive pamphlet. Each map sheet is published as a PDF file. Geographic information system (GIS) files that contain both ESRI ArcGIS raster grids (for example, bathymetry, seafloor character) and geotiffs (for example, shaded relief) are also included for each publication. For those who do not own the full suite of ESRI GIS and mapping software, the data can be read using ESRI ArcReader, a free viewer that is available at http://www.esri.com/software/arcgis/arcreader/index.html (last accessed September 20, 2013). The California Seafloor Mapping Program is a collaborative venture between numerous different federal and state agencies, academia, and the private sector. CSMP partners include the California Coastal Conservancy, the California Ocean Protection Council, the California Department of Fish and Wildlife, the California Geological Survey, California State University at Monterey Bay’s Seafloor Mapping Lab, Moss Landing Marine Laboratories Center for Habitat Studies, Fugro Pelagos, Pacific Gas and Electric Company, National Oceanic and Atmospheric Administration (NOAA, including National Ocean Service–Office of Coast Surveys, National Marine Sanctuaries, and National Marine Fisheries Service), U.S. Army Corps of Engineers, the Bureau of Ocean Energy Management, the National Park Service, and the U.S. Geological Survey. These web services for the Punta Gorda to Point Arena map area includes data layers that are associated to GIS and map sheets available from the USGS CSMP web page at https://walrus.wr.usgs.gov/mapping/csmp/index.html. Each published CSMP map area includes a data catalog of geographic information system (GIS) files; map sheets that contain explanatory text; and an associated descriptive pamphlet. This web service represents the available data layers for this map area. Data was combined from different sonar surveys to generate a comprehensive high-resolution bathymetry and acoustic-backscatter coverage of the map area. These data reveal a range of physiographic including exposed bedrock outcrops, large fields of sand waves, as well as many human impacts on the seafloor. To validate geological and biological interpretations of the sonar data, the U.S. Geological Survey towed a camera sled over specific offshore locations, collecting both video and photographic imagery; these “ground-truth” surveying data are available from the CSMP Video and Photograph Portal at https://doi.org/10.5066/F7J1015K. The “seafloor character” data layer shows classifications of the seafloor on the basis of depth, slope, rugosity (ruggedness), and backscatter intensity and which is further informed by the ground-truth-survey imagery. The “potential habitats” polygons are delineated on the basis of substrate type, geomorphology, seafloor process, or other attributes that may provide a habitat for a specific species or assemblage of organisms. Representative seismic-reflection profile data from the map area is also include and provides information on the subsurface stratigraphy and structure of the map area. The distribution and thickness of young sediment (deposited over the past about 21,000 years, during the most recent sea-level rise) is interpreted on the basis of the seismic-reflection data. The geologic polygons merge onshore geologic mapping (compiled from existing maps by the California Geological Survey) and new offshore geologic mapping that is based on integration of high-resolution bathymetry and backscatter imagery seafloor-sediment and rock samplesdigital camera and video imagery, and high-resolution seismic-reflection profiles. The information provided by the map sheets, pamphlet, and data catalog has a broad range of applications. High-resolution bathymetry, acoustic backscatter, ground-truth-surveying imagery, and habitat mapping all contribute to habitat characterization and ecosystem-based management by providing essential data for delineation of marine protected areas and ecosystem restoration. Many of the maps provide high-resolution baselines that will be critical for monitoring environmental change associated with climate change, coastal development, or other forcings. High-resolution bathymetry is a critical component for modeling coastal flooding caused by storms and tsunamis, as well as inundation associated with longer term sea-level rise. Seismic-reflection and bathymetric data help characterize earthquake and tsunami sources, critical for natural-hazard assessments of coastal zones. Information on sediment distribution and thickness is essential to the understanding of local and regional sediment transport, as well as the development of regional sediment-management plans. In addition, siting of any new offshore infrastructure (for example, pipelines, cables, or renewable-energy facilities) will depend on high-resolution mapping. Finally, this mapping will both stimulate and enable new scientific research and also raise public awareness of, and education about, coastal environments and issues. Web services were created using an ArcGIS service definition file. The ArcGIS REST service and OGC WMS service include all Punta Gorda to Point Arena map area data layers. Data layers are symbolized as shown on the associated map sheets.

In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ecosystems as part of the design and proposal process for the establishment of Marine Protected Areas. A focus of CSMP is to map California’s State Waters with consistent methods at a consistent scale. The CSMP approach is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar data (the undersea equivalent of satellite remote-sensing data in terrestrial mapping), acoustic backscatter, seafloor video, seafloor photography, high-resolution seismic-reflection profiles, and bottom-sediment sampling data. The map products display seafloor morphology and character, identify potential marine benthic habitats, and illustrate both the surficial seafloor geology and shallow (to about 100 m) subsurface geology. It is emphasized that the more interpretive habitat and geology data rely on the integration of multiple, new high-resolution datasets and that mapping at small scales would not be possible without such data. This approach and CSMP planning is based in part on recommendations of the Marine Mapping Planning Workshop (Kvitek and others, 2006), attended by coastal and marine managers and scientists from around the state. That workshop established geographic priorities for a coastal mapping project and identified the need for coverage of “lands” from the shore strand line (defined as Mean Higher High Water; MHHW) out to the 3-nautical-mile (5.6-km) limit of California’s State Waters. Unfortunately, surveying the zone from MHHW out to 10-m water depth is not consistently possible using ship-based surveying methods, owing to sea state (for example, waves, wind, or currents), kelp coverage, and shallow rock outcrops. Accordingly, some of the data presented in this series commonly do not cover the zone from the shore out to 10-m depth. This data is part of a series of online U.S. Geological Survey (USGS) publications, each of which includes several map sheets, some explanatory text, and a descriptive pamphlet. Each map sheet is published as a PDF file. Geographic information system (GIS) files that contain both ESRI ArcGIS raster grids (for example, bathymetry, seafloor character) and geotiffs (for example, shaded relief) are also included for each publication. For those who do not own the full suite of ESRI GIS and mapping software, the data can be read using ESRI ArcReader, a free viewer that is available at http://www.esri.com/software/arcgis/arcreader/index.html (last accessed September 20, 2013). The California Seafloor Mapping Program is a collaborative venture between numerous different federal and state agencies, academia, and the private sector. CSMP partners include the California Coastal Conservancy, the California Ocean Protection Council, the California Department of Fish and Wildlife, the California Geological Survey, California State University at Monterey Bay’s Seafloor Mapping Lab, Moss Landing Marine Laboratories Center for Habitat Studies, Fugro Pelagos, Pacific Gas and Electric Company, National Oceanic and Atmospheric Administration (NOAA, including National Ocean Service–Office of Coast Surveys, National Marine Sanctuaries, and National Marine Fisheries Service), U.S. Army Corps of Engineers, the Bureau of Ocean Energy Management, the National Park Service, and the U.S. Geological Survey. These web services for the Offshore of Bodega Head map area includes data layers that are associated to GIS and map sheets available from the USGS CSMP web page at https://walrus.wr.usgs.gov/mapping/csmp/index.html. Each published CSMP map area includes a data catalog of geographic information system (GIS) files; map sheets that contain explanatory text; and an associated descriptive pamphlet. This web service represents the available data layers for this map area. Data was combined from different sonar surveys to generate a comprehensive high-resolution bathymetry and acoustic-backscatter coverage of the map area. These data reveal a range of physiographic including exposed bedrock outcrops, large fields of sand waves, as well as many human impacts on the seafloor. To validate geological and biological interpretations of the sonar data, the U.S. Geological Survey towed a camera sled over specific offshore locations, collecting both video and photographic imagery; these “ground-truth” surveying data are available from the CSMP Video and Photograph Portal at https://doi.org/10.5066/F7J1015K. The “seafloor character” data layer shows classifications of the seafloor on the basis of depth, slope, rugosity (ruggedness), and backscatter intensity and which is further informed by the ground-truth-survey imagery. The “potential habitats” polygons are delineated on the basis of substrate type, geomorphology, seafloor process, or other attributes that may provide a habitat for a specific species or assemblage of organisms. Representative seismic-reflection profile data from the map area is also include and provides information on the subsurface stratigraphy and structure of the map area. The distribution and thickness of young sediment (deposited over the past about 21,000 years, during the most recent sea-level rise) is interpreted on the basis of the seismic-reflection data. The geologic polygons merge onshore geologic mapping (compiled from existing maps by the California Geological Survey) and new offshore geologic mapping that is based on integration of high-resolution bathymetry and backscatter imagery seafloor-sediment and rock samplesdigital camera and video imagery, and high-resolution seismic-reflection profiles. The information provided by the map sheets, pamphlet, and data catalog has a broad range of applications. High-resolution bathymetry, acoustic backscatter, ground-truth-surveying imagery, and habitat mapping all contribute to habitat characterization and ecosystem-based management by providing essential data for delineation of marine protected areas and ecosystem restoration. Many of the maps provide high-resolution baselines that will be critical for monitoring environmental change associated with climate change, coastal development, or other forcings. High-resolution bathymetry is a critical component for modeling coastal flooding caused by storms and tsunamis, as well as inundation associated with longer term sea-level rise. Seismic-reflection and bathymetric data help characterize earthquake and tsunami sources, critical for natural-hazard assessments of coastal zones. Information on sediment distribution and thickness is essential to the understanding of local and regional sediment transport, as well as the development of regional sediment-management plans. In addition, siting of any new offshore infrastructure (for example, pipelines, cables, or renewable-energy facilities) will depend on high-resolution mapping. Finally, this mapping will both stimulate and enable new scientific research and also raise public awareness of, and education about, coastal environments and issues. Web services were created using an ArcGIS service definition file. The ArcGIS REST service and OGC WMS service include all Offshore of Bodega Head map area data layers. Data layers are symbolized as shown on the associated map sheets.

In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ecosystems as part of the design and proposal process for the establishment of Marine Protected Areas. A focus of CSMP is to map California’s State Waters with consistent methods at a consistent scale. The CSMP approach is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar data (the undersea equivalent of satellite remote-sensing data in terrestrial mapping), acoustic backscatter, seafloor video, seafloor photography, high-resolution seismic-reflection profiles, and bottom-sediment sampling data. The map products display seafloor morphology and character, identify potential marine benthic habitats, and illustrate both the surficial seafloor geology and shallow (to about 100 m) subsurface geology. It is emphasized that the more interpretive habitat and geology data rely on the integration of multiple, new high-resolution datasets and that mapping at small scales would not be possible without such data. This approach and CSMP planning is based in part on recommendations of the Marine Mapping Planning Workshop (Kvitek and others, 2006), attended by coastal and marine managers and scientists from around the state. That workshop established geographic priorities for a coastal mapping project and identified the need for coverage of “lands” from the shore strand line (defined as Mean Higher High Water; MHHW) out to the 3-nautical-mile (5.6-km) limit of California’s State Waters. Unfortunately, surveying the zone from MHHW out to 10-m water depth is not consistently possible using ship-based surveying methods, owing to sea state (for example, waves, wind, or currents), kelp coverage, and shallow rock outcrops. Accordingly, some of the data presented in this series commonly do not cover the zone from the shore out to 10-m depth. This data is part of a series of online U.S. Geological Survey (USGS) publications, each of which includes several map sheets, some explanatory text, and a descriptive pamphlet. Each map sheet is published as a PDF file. Geographic information system (GIS) files that contain both ESRI ArcGIS raster grids (for example, bathymetry, seafloor character) and geotiffs (for example, shaded relief) are also included for each publication. For those who do not own the full suite of ESRI GIS and mapping software, the data can be read using ESRI ArcReader, a free viewer that is available at http://www.esri.com/software/arcgis/arcreader/index.html (last accessed September 20, 2013). The California Seafloor Mapping Program is a collaborative venture between numerous different federal and state agencies, academia, and the private sector. CSMP partners include the California Coastal Conservancy, the California Ocean Protection Council, the California Department of Fish and Wildlife, the California Geological Survey, California State University at Monterey Bay’s Seafloor Mapping Lab, Moss Landing Marine Laboratories Center for Habitat Studies, Fugro Pelagos, Pacific Gas and Electric Company, National Oceanic and Atmospheric Administration (NOAA, including National Ocean Service–Office of Coast Surveys, National Marine Sanctuaries, and National Marine Fisheries Service), U.S. Army Corps of Engineers, the Bureau of Ocean Energy Management, the National Park Service, and the U.S. Geological Survey. These web services for the Bolinas to Pescadero Region includes data layers that are associated to GIS and map sheets available from the USGS CSMP web page at https://walrus.wr.usgs.gov/mapping/csmp/index.html. Each published CSMP map area includes a data catalog of geographic information system (GIS) files; map sheets that contain explanatory text; and an associated descriptive pamphlet. This web service represents the available data layers for this map area. Data was combined from different sonar surveys to generate a comprehensive high-resolution bathymetry and acoustic-backscatter coverage of the map area. These data reveal a range of physiographic including exposed bedrock outcrops, large fields of sand waves, as well as many human impacts on the seafloor. To validate geological and biological interpretations of the sonar data, the U.S. Geological Survey towed a camera sled over specific offshore locations, collecting both video and photographic imagery; these “ground-truth” surveying data are available from the CSMP Video and Photograph Portal at https://doi.org/10.5066/F7J1015K. The “seafloor character” data layer shows classifications of the seafloor on the basis of depth, slope, rugosity (ruggedness), and backscatter intensity and which is further informed by the ground-truth-survey imagery. The “potential habitats” polygons are delineated on the basis of substrate type, geomorphology, seafloor process, or other attributes that may provide a habitat for a specific species or assemblage of organisms. Representative seismic-reflection profile data from the map area is also include and provides information on the subsurface stratigraphy and structure of the map area. The distribution and thickness of young sediment (deposited over the past about 21,000 years, during the most recent sea-level rise) is interpreted on the basis of the seismic-reflection data. The geologic polygons merge onshore geologic mapping (compiled from existing maps by the California Geological Survey) and new offshore geologic mapping that is based on integration of high-resolution bathymetry and backscatter imagery seafloor-sediment and rock samplesdigital camera and video imagery, and high-resolution seismic-reflection profiles. The information provided by the map sheets, pamphlet, and data catalog has a broad range of applications. High-resolution bathymetry, acoustic backscatter, ground-truth-surveying imagery, and habitat mapping all contribute to habitat characterization and ecosystem-based management by providing essential data for delineation of marine protected areas and ecosystem restoration. Many of the maps provide high-resolution baselines that will be critical for monitoring environmental change associated with climate change, coastal development, or other forcings. High-resolution bathymetry is a critical component for modeling coastal flooding caused by storms and tsunamis, as well as inundation associated with longer term sea-level rise. Seismic-reflection and bathymetric data help characterize earthquake and tsunami sources, critical for natural-hazard assessments of coastal zones. Information on sediment distribution and thickness is essential to the understanding of local and regional sediment transport, as well as the development of regional sediment-management plans. In addition, siting of any new offshore infrastructure (for example, pipelines, cables, or renewable-energy facilities) will depend on high-resolution mapping. Finally, this mapping will both stimulate and enable new scientific research and also raise public awareness of, and education about, coastal environments and issues. Web services were created using an ArcGIS service definition file. The ArcGIS REST service and OGC WMS service include all Bolinas to Pescadero Region data layers. Data layers are symbolized as shown on the associated map sheets.

In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ecosystems as part of the design and proposal process for the establishment of Marine Protected Areas. A focus of CSMP is to map California’s State Waters with consistent methods at a consistent scale. The CSMP approach is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar data (the undersea equivalent of satellite remote-sensing data in terrestrial mapping), acoustic backscatter, seafloor video, seafloor photography, high-resolution seismic-reflection profiles, and bottom-sediment sampling data. The map products display seafloor morphology and character, identify potential marine benthic habitats, and illustrate both the surficial seafloor geology and shallow (to about 100 m) subsurface geology. It is emphasized that the more interpretive habitat and geology data rely on the integration of multiple, new high-resolution datasets and that mapping at small scales would not be possible without such data. This approach and CSMP planning is based in part on recommendations of the Marine Mapping Planning Workshop (Kvitek and others, 2006), attended by coastal and marine managers and scientists from around the state. That workshop established geographic priorities for a coastal mapping project and identified the need for coverage of “lands” from the shore strand line (defined as Mean Higher High Water; MHHW) out to the 3-nautical-mile (5.6-km) limit of California’s State Waters. Unfortunately, surveying the zone from MHHW out to 10-m water depth is not consistently possible using ship-based surveying methods, owing to sea state (for example, waves, wind, or currents), kelp coverage, and shallow rock outcrops. Accordingly, some of the data presented in this series commonly do not cover the zone from the shore out to 10-m depth. This data is part of a series of online U.S. Geological Survey (USGS) publications, each of which includes several map sheets, some explanatory text, and a descriptive pamphlet. Each map sheet is published as a PDF file. Geographic information system (GIS) files that contain both ESRI ArcGIS raster grids (for example, bathymetry, seafloor character) and geotiffs (for example, shaded relief) are also included for each publication. For those who do not own the full suite of ESRI GIS and mapping software, the data can be read using ESRI ArcReader, a free viewer that is available at http://www.esri.com/software/arcgis/arcreader/index.html (last accessed September 20, 2013). The California Seafloor Mapping Program is a collaborative venture between numerous different federal and state agencies, academia, and the private sector. CSMP partners include the California Coastal Conservancy, the California Ocean Protection Council, the California Department of Fish and Wildlife, the California Geological Survey, California State University at Monterey Bay’s Seafloor Mapping Lab, Moss Landing Marine Laboratories Center for Habitat Studies, Fugro Pelagos, Pacific Gas and Electric Company, National Oceanic and Atmospheric Administration (NOAA, including National Ocean Service–Office of Coast Surveys, National Marine Sanctuaries, and National Marine Fisheries Service), U.S. Army Corps of Engineers, the Bureau of Ocean Energy Management, the National Park Service, and the U.S. Geological Survey. These web services for the Offshore of Bolinas map area includes data layers that are associated to GIS and map sheets available from the USGS CSMP web page at https://walrus.wr.usgs.gov/mapping/csmp/index.html. Each published CSMP map area includes a data catalog of geographic information system (GIS) files; map sheets that contain explanatory text; and an associated descriptive pamphlet. This web service represents the available data layers for this map area. Data was combined from different sonar surveys to generate a comprehensive high-resolution bathymetry and acoustic-backscatter coverage of the map area. These data reveal a range of physiographic including exposed bedrock outcrops, large fields of sand waves, as well as many human impacts on the seafloor. To validate geological and biological interpretations of the sonar data, the U.S. Geological Survey towed a camera sled over specific offshore locations, collecting both video and photographic imagery; these “ground-truth” surveying data are available from the CSMP Video and Photograph Portal at https://doi.org/10.5066/F7J1015K. The “seafloor character” data layer shows classifications of the seafloor on the basis of depth, slope, rugosity (ruggedness), and backscatter intensity and which is further informed by the ground-truth-survey imagery. The “potential habitats” polygons are delineated on the basis of substrate type, geomorphology, seafloor process, or other attributes that may provide a habitat for a specific species or assemblage of organisms. Representative seismic-reflection profile data from the map area is also include and provides information on the subsurface stratigraphy and structure of the map area. The distribution and thickness of young sediment (deposited over the past about 21,000 years, during the most recent sea-level rise) is interpreted on the basis of the seismic-reflection data. The geologic polygons merge onshore geologic mapping (compiled from existing maps by the California Geological Survey) and new offshore geologic mapping that is based on integration of high-resolution bathymetry and backscatter imagery seafloor-sediment and rock samplesdigital camera and video imagery, and high-resolution seismic-reflection profiles. The information provided by the map sheets, pamphlet, and data catalog has a broad range of applications. High-resolution bathymetry, acoustic backscatter, ground-truth-surveying imagery, and habitat mapping all contribute to habitat characterization and ecosystem-based management by providing essential data for delineation of marine protected areas and ecosystem restoration. Many of the maps provide high-resolution baselines that will be critical for monitoring environmental change associated with climate change, coastal development, or other forcings. High-resolution bathymetry is a critical component for modeling coastal flooding caused by storms and tsunamis, as well as inundation associated with longer term sea-level rise. Seismic-reflection and bathymetric data help characterize earthquake and tsunami sources, critical for natural-hazard assessments of coastal zones. Information on sediment distribution and thickness is essential to the understanding of local and regional sediment transport, as well as the development of regional sediment-management plans. In addition, siting of any new offshore infrastructure (for example, pipelines, cables, or renewable-energy facilities) will depend on high-resolution mapping. Finally, this mapping will both stimulate and enable new scientific research and also raise public awareness of, and education about, coastal environments and issues. Web services were created using an ArcGIS service definition file. The ArcGIS REST service and OGC WMS service include all Offshore of Bolinas map area data layers. Data layers are symbolized as shown on the associated map sheets.

In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ecosystems as part of the design and proposal process for the establishment of Marine Protected Areas. A focus of CSMP is to map California’s State Waters with consistent methods at a consistent scale. The CSMP approach is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar data (the undersea equivalent of satellite remote-sensing data in terrestrial mapping), acoustic backscatter, seafloor video, seafloor photography, high-resolution seismic-reflection profiles, and bottom-sediment sampling data. The map products display seafloor morphology and character, identify potential marine benthic habitats, and illustrate both the surficial seafloor geology and shallow (to about 100 m) subsurface geology. It is emphasized that the more interpretive habitat and geology data rely on the integration of multiple, new high-resolution datasets and that mapping at small scales would not be possible without such data. This approach and CSMP planning is based in part on recommendations of the Marine Mapping Planning Workshop (Kvitek and others, 2006), attended by coastal and marine managers and scientists from around the state. That workshop established geographic priorities for a coastal mapping project and identified the need for coverage of “lands” from the shore strand line (defined as Mean Higher High Water; MHHW) out to the 3-nautical-mile (5.6-km) limit of California’s State Waters. Unfortunately, surveying the zone from MHHW out to 10-m water depth is not consistently possible using ship-based surveying methods, owing to sea state (for example, waves, wind, or currents), kelp coverage, and shallow rock outcrops. Accordingly, some of the data presented in this series commonly do not cover the zone from the shore out to 10-m depth. This data is part of a series of online U.S. Geological Survey (USGS) publications, each of which includes several map sheets, some explanatory text, and a descriptive pamphlet. Each map sheet is published as a PDF file. Geographic information system (GIS) files that contain both ESRI ArcGIS raster grids (for example, bathymetry, seafloor character) and geotiffs (for example, shaded relief) are also included for each publication. For those who do not own the full suite of ESRI GIS and mapping software, the data can be read using ESRI ArcReader, a free viewer that is available at http://www.esri.com/software/arcgis/arcreader/index.html (last accessed September 20, 2013). The California Seafloor Mapping Program is a collaborative venture between numerous different federal and state agencies, academia, and the private sector. CSMP partners include the California Coastal Conservancy, the California Ocean Protection Council, the California Department of Fish and Wildlife, the California Geological Survey, California State University at Monterey Bay’s Seafloor Mapping Lab, Moss Landing Marine Laboratories Center for Habitat Studies, Fugro Pelagos, Pacific Gas and Electric Company, National Oceanic and Atmospheric Administration (NOAA, including National Ocean Service–Office of Coast Surveys, National Marine Sanctuaries, and National Marine Fisheries Service), U.S. Army Corps of Engineers, the Bureau of Ocean Energy Management, the National Park Service, and the U.S. Geological Survey. These web services for the Offshore of Carpinteria map area includes data layers that are associated to GIS and map sheets available from the USGS CSMP web page at https://walrus.wr.usgs.gov/mapping/csmp/index.html. Each published CSMP map area includes a data catalog of geographic information system (GIS) files; map sheets that contain explanatory text; and an associated descriptive pamphlet. This web service represents the available data layers for this map area. Data was combined from different sonar surveys to generate a comprehensive high-resolution bathymetry and acoustic-backscatter coverage of the map area. These data reveal a range of physiographic including exposed bedrock outcrops, large fields of sand waves, as well as many human impacts on the seafloor. To validate geological and biological interpretations of the sonar data, the U.S. Geological Survey towed a camera sled over specific offshore locations, collecting both video and photographic imagery; these “ground-truth” surveying data are available from the CSMP Video and Photograph Portal at https://doi.org/10.5066/F7J1015K. The “seafloor character” data layer shows classifications of the seafloor on the basis of depth, slope, rugosity (ruggedness), and backscatter intensity and which is further informed by the ground-truth-survey imagery. The “potential habitats” polygons are delineated on the basis of substrate type, geomorphology, seafloor process, or other attributes that may provide a habitat for a specific species or assemblage of organisms. Representative seismic-reflection profile data from the map area is also include and provides information on the subsurface stratigraphy and structure of the map area. The distribution and thickness of young sediment (deposited over the past about 21,000 years, during the most recent sea-level rise) is interpreted on the basis of the seismic-reflection data. The geologic polygons merge onshore geologic mapping (compiled from existing maps by the California Geological Survey) and new offshore geologic mapping that is based on integration of high-resolution bathymetry and backscatter imagery seafloor-sediment and rock samplesdigital camera and video imagery, and high-resolution seismic-reflection profiles. The information provided by the map sheets, pamphlet, and data catalog has a broad range of applications. High-resolution bathymetry, acoustic backscatter, ground-truth-surveying imagery, and habitat mapping all contribute to habitat characterization and ecosystem-based management by providing essential data for delineation of marine protected areas and ecosystem restoration. Many of the maps provide high-resolution baselines that will be critical for monitoring environmental change associated with climate change, coastal development, or other forcings. High-resolution bathymetry is a critical component for modeling coastal flooding caused by storms and tsunamis, as well as inundation associated with longer term sea-level rise. Seismic-reflection and bathymetric data help characterize earthquake and tsunami sources, critical for natural-hazard assessments of coastal zones. Information on sediment distribution and thickness is essential to the understanding of local and regional sediment transport, as well as the development of regional sediment-management plans. In addition, siting of any new offshore infrastructure (for example, pipelines, cables, or renewable-energy facilities) will depend on high-resolution mapping. Finally, this mapping will both stimulate and enable new scientific research and also raise public awareness of, and education about, coastal environments and issues. Web services were created using an ArcGIS service definition file. The ArcGIS REST service and OGC WMS service include all Offshore of Carpinteria map area data layers. Data layers are symbolized as shown on the associated map sheets.

In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ecosystems as part of the design and proposal process for the establishment of Marine Protected Areas. A focus of CSMP is to map California’s State Waters with consistent methods at a consistent scale. The CSMP approach is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar data (the undersea equivalent of satellite remote-sensing data in terrestrial mapping), acoustic backscatter, seafloor video, seafloor photography, high-resolution seismic-reflection profiles, and bottom-sediment sampling data. The map products display seafloor morphology and character, identify potential marine benthic habitats, and illustrate both the surficial seafloor geology and shallow (to about 100 m) subsurface geology. It is emphasized that the more interpretive habitat and geology data rely on the integration of multiple, new high-resolution datasets and that mapping at small scales would not be possible without such data. This approach and CSMP planning is based in part on recommendations of the Marine Mapping Planning Workshop (Kvitek and others, 2006), attended by coastal and marine managers and scientists from around the state. That workshop established geographic priorities for a coastal mapping project and identified the need for coverage of “lands” from the shore strand line (defined as Mean Higher High Water; MHHW) out to the 3-nautical-mile (5.6-km) limit of California’s State Waters. Unfortunately, surveying the zone from MHHW out to 10-m water depth is not consistently possible using ship-based surveying methods, owing to sea state (for example, waves, wind, or currents), kelp coverage, and shallow rock outcrops. Accordingly, some of the data presented in this series commonly do not cover the zone from the shore out to 10-m depth. This data is part of a series of online U.S. Geological Survey (USGS) publications, each of which includes several map sheets, some explanatory text, and a descriptive pamphlet. Each map sheet is published as a PDF file. Geographic information system (GIS) files that contain both ESRI ArcGIS raster grids (for example, bathymetry, seafloor character) and geotiffs (for example, shaded relief) are also included for each publication. For those who do not own the full suite of ESRI GIS and mapping software, the data can be read using ESRI ArcReader, a free viewer that is available at http://www.esri.com/software/arcgis/arcreader/index.html (last accessed September 20, 2013). The California Seafloor Mapping Program is a collaborative venture between numerous different federal and state agencies, academia, and the private sector. CSMP partners include the California Coastal Conservancy, the California Ocean Protection Council, the California Department of Fish and Wildlife, the California Geological Survey, California State University at Monterey Bay’s Seafloor Mapping Lab, Moss Landing Marine Laboratories Center for Habitat Studies, Fugro Pelagos, Pacific Gas and Electric Company, National Oceanic and Atmospheric Administration (NOAA, including National Ocean Service–Office of Coast Surveys, National Marine Sanctuaries, and National Marine Fisheries Service), U.S. Army Corps of Engineers, the Bureau of Ocean Energy Management, the National Park Service, and the U.S. Geological Survey. These web services for the Offshore of Coal Oil Point map area includes data layers that are associated to GIS and map sheets available from the USGS CSMP web page at https://walrus.wr.usgs.gov/mapping/csmp/index.html. Each published CSMP map area includes a data catalog of geographic information system (GIS) files; map sheets that contain explanatory text; and an associated descriptive pamphlet. This web service represents the available data layers for this map area. Data was combined from different sonar surveys to generate a comprehensive high-resolution bathymetry and acoustic-backscatter coverage of the map area. These data reveal a range of physiographic including exposed bedrock outcrops, large fields of sand waves, as well as many human impacts on the seafloor. To validate geological and biological interpretations of the sonar data, the U.S. Geological Survey towed a camera sled over specific offshore locations, collecting both video and photographic imagery; these “ground-truth” surveying data are available from the CSMP Video and Photograph Portal at https://doi.org/10.5066/F7J1015K. The “seafloor character” data layer shows classifications of the seafloor on the basis of depth, slope, rugosity (ruggedness), and backscatter intensity and which is further informed by the ground-truth-survey imagery. The “potential habitats” polygons are delineated on the basis of substrate type, geomorphology, seafloor process, or other attributes that may provide a habitat for a specific species or assemblage of organisms. Representative seismic-reflection profile data from the map area is also include and provides information on the subsurface stratigraphy and structure of the map area. The distribution and thickness of young sediment (deposited over the past about 21,000 years, during the most recent sea-level rise) is interpreted on the basis of the seismic-reflection data. The geologic polygons merge onshore geologic mapping (compiled from existing maps by the California Geological Survey) and new offshore geologic mapping that is based on integration of high-resolution bathymetry and backscatter imagery seafloor-sediment and rock samplesdigital camera and video imagery, and high-resolution seismic-reflection profiles. The information provided by the map sheets, pamphlet, and data catalog has a broad range of applications. High-resolution bathymetry, acoustic backscatter, ground-truth-surveying imagery, and habitat mapping all contribute to habitat characterization and ecosystem-based management by providing essential data for delineation of marine protected areas and ecosystem restoration. Many of the maps provide high-resolution baselines that will be critical for monitoring environmental change associated with climate change, coastal development, or other forcings. High-resolution bathymetry is a critical component for modeling coastal flooding caused by storms and tsunamis, as well as inundation associated with longer term sea-level rise. Seismic-reflection and bathymetric data help characterize earthquake and tsunami sources, critical for natural-hazard assessments of coastal zones. Information on sediment distribution and thickness is essential to the understanding of local and regional sediment transport, as well as the development of regional sediment-management plans. In addition, siting of any new offshore infrastructure (for example, pipelines, cables, or renewable-energy facilities) will depend on high-resolution mapping. Finally, this mapping will both stimulate and enable new scientific research and also raise public awareness of, and education about, coastal environments and issues. Web services were created using an ArcGIS service definition file. The ArcGIS REST service and OGC WMS service include all Offshore Coal Oil Point map area data layers. Data layers are symbolized as shown on the associated map sheets.

In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ecosystems as part of the design and proposal process for the establishment of Marine Protected Areas. A focus of CSMP is to map California’s State Waters with consistent methods at a consistent scale. The CSMP approach is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar data (the undersea equivalent of satellite remote-sensing data in terrestrial mapping), acoustic backscatter, seafloor video, seafloor photography, high-resolution seismic-reflection profiles, and bottom-sediment sampling data. The map products display seafloor morphology and character, identify potential marine benthic habitats, and illustrate both the surficial seafloor geology and shallow (to about 100 m) subsurface geology. It is emphasized that the more interpretive habitat and geology data rely on the integration of multiple, new high-resolution datasets and that mapping at small scales would not be possible without such data. This approach and CSMP planning is based in part on recommendations of the Marine Mapping Planning Workshop (Kvitek and others, 2006), attended by coastal and marine managers and scientists from around the state. That workshop established geographic priorities for a coastal mapping project and identified the need for coverage of “lands” from the shore strand line (defined as Mean Higher High Water; MHHW) out to the 3-nautical-mile (5.6-km) limit of California’s State Waters. Unfortunately, surveying the zone from MHHW out to 10-m water depth is not consistently possible using ship-based surveying methods, owing to sea state (for example, waves, wind, or currents), kelp coverage, and shallow rock outcrops. Accordingly, some of the data presented in this series commonly do not cover the zone from the shore out to 10-m depth. This data is part of a series of online U.S. Geological Survey (USGS) publications, each of which includes several map sheets, some explanatory text, and a descriptive pamphlet. Each map sheet is published as a PDF file. Geographic information system (GIS) files that contain both ESRI ArcGIS raster grids (for example, bathymetry, seafloor character) and geotiffs (for example, shaded relief) are also included for each publication. For those who do not own the full suite of ESRI GIS and mapping software, the data can be read using ESRI ArcReader, a free viewer that is available at http://www.esri.com/software/arcgis/arcreader/index.html (last accessed September 20, 2013). The California Seafloor Mapping Program is a collaborative venture between numerous different federal and state agencies, academia, and the private sector. CSMP partners include the California Coastal Conservancy, the California Ocean Protection Council, the California Department of Fish and Wildlife, the California Geological Survey, California State University at Monterey Bay’s Seafloor Mapping Lab, Moss Landing Marine Laboratories Center for Habitat Studies, Fugro Pelagos, Pacific Gas and Electric Company, National Oceanic and Atmospheric Administration (NOAA, including National Ocean Service–Office of Coast Surveys, National Marine Sanctuaries, and National Marine Fisheries Service), U.S. Army Corps of Engineers, the Bureau of Ocean Energy Management, the National Park Service, and the U.S. Geological Survey. These web services for the Drakes Bay map area includes data layers that are associated to GIS and map sheets available from the USGS CSMP web page at https://walrus.wr.usgs.gov/mapping/csmp/index.html. Each published CSMP map area includes a data catalog of geographic information system (GIS) files; map sheets that contain explanatory text; and an associated descriptive pamphlet. This web service represents the available data layers for this map area. Data was combined from different sonar surveys to generate a comprehensive high-resolution bathymetry and acoustic-backscatter coverage of the map area. These data reveal a range of physiographic including exposed bedrock outcrops, large fields of sand waves, as well as many human impacts on the seafloor. To validate geological and biological interpretations of the sonar data, the U.S. Geological Survey towed a camera sled over specific offshore locations, collecting both video and photographic imagery; these “ground-truth” surveying data are available from the CSMP Video and Photograph Portal at https://doi.org/10.5066/F7J1015K. The “seafloor character” data layer shows classifications of the seafloor on the basis of depth, slope, rugosity (ruggedness), and backscatter intensity and which is further informed by the ground-truth-survey imagery. The “potential habitats” polygons are delineated on the basis of substrate type, geomorphology, seafloor process, or other attributes that may provide a habitat for a specific species or assemblage of organisms. Representative seismic-reflection profile data from the map area is also include and provides information on the subsurface stratigraphy and structure of the map area. The distribution and thickness of young sediment (deposited over the past about 21,000 years, during the most recent sea-level rise) is interpreted on the basis of the seismic-reflection data. The geologic polygons merge onshore geologic mapping (compiled from existing maps by the California Geological Survey) and new offshore geologic mapping that is based on integration of high-resolution bathymetry and backscatter imagery seafloor-sediment and rock samplesdigital camera and video imagery, and high-resolution seismic-reflection profiles. The information provided by the map sheets, pamphlet, and data catalog has a broad range of applications. High-resolution bathymetry, acoustic backscatter, ground-truth-surveying imagery, and habitat mapping all contribute to habitat characterization and ecosystem-based management by providing essential data for delineation of marine protected areas and ecosystem restoration. Many of the maps provide high-resolution baselines that will be critical for monitoring environmental change associated with climate change, coastal development, or other forcings. High-resolution bathymetry is a critical component for modeling coastal flooding caused by storms and tsunamis, as well as inundation associated with longer term sea-level rise. Seismic-reflection and bathymetric data help characterize earthquake and tsunami sources, critical for natural-hazard assessments of coastal zones. Information on sediment distribution and thickness is essential to the understanding of local and regional sediment transport, as well as the development of regional sediment-management plans. In addition, siting of any new offshore infrastructure (for example, pipelines, cables, or renewable-energy facilities) will depend on high-resolution mapping. Finally, this mapping will both stimulate and enable new scientific research and also raise public awareness of, and education about, coastal environments and issues. Web services were created using an ArcGIS service definition file. The ArcGIS REST service and OGC WMS service include all Drakes Bay map area data layers. Data layers are symbolized as shown on the associated map sheets.

In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ecosystems as part of the design and proposal process for the establishment of Marine Protected Areas. A focus of CSMP is to map California’s State Waters with consistent methods at a consistent scale. The CSMP approach is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar data (the undersea equivalent of satellite remote-sensing data in terrestrial mapping), acoustic backscatter, seafloor video, seafloor photography, high-resolution seismic-reflection profiles, and bottom-sediment sampling data. The map products display seafloor morphology and character, identify potential marine benthic habitats, and illustrate both the surficial seafloor geology and shallow (to about 100 m) subsurface geology. It is emphasized that the more interpretive habitat and geology data rely on the integration of multiple, new high-resolution datasets and that mapping at small scales would not be possible without such data. This approach and CSMP planning is based in part on recommendations of the Marine Mapping Planning Workshop (Kvitek and others, 2006), attended by coastal and marine managers and scientists from around the state. That workshop established geographic priorities for a coastal mapping project and identified the need for coverage of “lands” from the shore strand line (defined as Mean Higher High Water; MHHW) out to the 3-nautical-mile (5.6-km) limit of California’s State Waters. Unfortunately, surveying the zone from MHHW out to 10-m water depth is not consistently possible using ship-based surveying methods, owing to sea state (for example, waves, wind, or currents), kelp coverage, and shallow rock outcrops. Accordingly, some of the data presented in this series commonly do not cover the zone from the shore out to 10-m depth. This data is part of a series of online U.S. Geological Survey (USGS) publications, each of which includes several map sheets, some explanatory text, and a descriptive pamphlet. Each map sheet is published as a PDF file. Geographic information system (GIS) files that contain both ESRI ArcGIS raster grids (for example, bathymetry, seafloor character) and geotiffs (for example, shaded relief) are also included for each publication. For those who do not own the full suite of ESRI GIS and mapping software, the data can be read using ESRI ArcReader, a free viewer that is available at http://www.esri.com/software/arcgis/arcreader/index.html (last accessed September 20, 2013). The California Seafloor Mapping Program is a collaborative venture between numerous different federal and state agencies, academia, and the private sector. CSMP partners include the California Coastal Conservancy, the California Ocean Protection Council, the California Department of Fish and Wildlife, the California Geological Survey, California State University at Monterey Bay’s Seafloor Mapping Lab, Moss Landing Marine Laboratories Center for Habitat Studies, Fugro Pelagos, Pacific Gas and Electric Company, National Oceanic and Atmospheric Administration (NOAA, including National Ocean Service–Office of Coast Surveys, National Marine Sanctuaries, and National Marine Fisheries Service), U.S. Army Corps of Engineers, the Bureau of Ocean Energy Management, the National Park Service, and the U.S. Geological Survey. These web services for the Offshore Fort Ross map area includes data layers that are associated to GIS and map sheets available from the USGS CSMP web page at https://walrus.wr.usgs.gov/mapping/csmp/index.html. Each published CSMP map area includes a data catalog of geographic information system (GIS) files; map sheets that contain explanatory text; and an associated descriptive pamphlet. This web service represents the available data layers for this map area. Data was combined from different sonar surveys to generate a comprehensive high-resolution bathymetry and acoustic-backscatter coverage of the map area. These data reveal a range of physiographic including exposed bedrock outcrops, large fields of sand waves, as well as many human impacts on the seafloor. To validate geological and biological interpretations of the sonar data, the U.S. Geological Survey towed a camera sled over specific offshore locations, collecting both video and photographic imagery; these “ground-truth” surveying data are available from the CSMP Video and Photograph Portal at https://doi.org/10.5066/F7J1015K. The “seafloor character” data layer shows classifications of the seafloor on the basis of depth, slope, rugosity (ruggedness), and backscatter intensity and which is further informed by the ground-truth-survey imagery. The “potential habitats” polygons are delineated on the basis of substrate type, geomorphology, seafloor process, or other attributes that may provide a habitat for a specific species or assemblage of organisms. Representative seismic-reflection profile data from the map area is also include and provides information on the subsurface stratigraphy and structure of the map area. The distribution and thickness of young sediment (deposited over the past about 21,000 years, during the most recent sea-level rise) is interpreted on the basis of the seismic-reflection data. The geologic polygons merge onshore geologic mapping (compiled from existing maps by the California Geological Survey) and new offshore geologic mapping that is based on integration of high-resolution bathymetry and backscatter imagery seafloor-sediment and rock samplesdigital camera and video imagery, and high-resolution seismic-reflection profiles. The information provided by the map sheets, pamphlet, and data catalog has a broad range of applications. High-resolution bathymetry, acoustic backscatter, ground-truth-surveying imagery, and habitat mapping all contribute to habitat characterization and ecosystem-based management by providing essential data for delineation of marine protected areas and ecosystem restoration. Many of the maps provide high-resolution baselines that will be critical for monitoring environmental change associated with climate change, coastal development, or other forcings. High-resolution bathymetry is a critical component for modeling coastal flooding caused by storms and tsunamis, as well as inundation associated with longer term sea-level rise. Seismic-reflection and bathymetric data help characterize earthquake and tsunami sources, critical for natural-hazard assessments of coastal zones. Information on sediment distribution and thickness is essential to the understanding of local and regional sediment transport, as well as the development of regional sediment-management plans. In addition, siting of any new offshore infrastructure (for example, pipelines, cables, or renewable-energy facilities) will depend on high-resolution mapping. Finally, this mapping will both stimulate and enable new scientific research and also raise public awareness of, and education about, coastal environments and issues. Web services were created using an ArcGIS service definition file. The ArcGIS REST service and OGC WMS service include all Offshore Fort Ross map area data layers. Data layers are symbolized as shown on the associated map sheets.

In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ecosystems as part of the design and proposal process for the establishment of Marine Protected Areas. A focus of CSMP is to map California’s State Waters with consistent methods at a consistent scale. The CSMP approach is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar data (the undersea equivalent of satellite remote-sensing data in terrestrial mapping), acoustic backscatter, seafloor video, seafloor photography, high-resolution seismic-reflection profiles, and bottom-sediment sampling data. The map products display seafloor morphology and character, identify potential marine benthic habitats, and illustrate both the surficial seafloor geology and shallow (to about 100 m) subsurface geology. It is emphasized that the more interpretive habitat and geology data rely on the integration of multiple, new high-resolution datasets and that mapping at small scales would not be possible without such data. This approach and CSMP planning is based in part on recommendations of the Marine Mapping Planning Workshop (Kvitek and others, 2006), attended by coastal and marine managers and scientists from around the state. That workshop established geographic priorities for a coastal mapping project and identified the need for coverage of “lands” from the shore strand line (defined as Mean Higher High Water; MHHW) out to the 3-nautical-mile (5.6-km) limit of California’s State Waters. Unfortunately, surveying the zone from MHHW out to 10-m water depth is not consistently possible using ship-based surveying methods, owing to sea state (for example, waves, wind, or currents), kelp coverage, and shallow rock outcrops. Accordingly, some of the data presented in this series commonly do not cover the zone from the shore out to 10-m depth. This data is part of a series of online U.S. Geological Survey (USGS) publications, each of which includes several map sheets, some explanatory text, and a descriptive pamphlet. Each map sheet is published as a PDF file. Geographic information system (GIS) files that contain both ESRI ArcGIS raster grids (for example, bathymetry, seafloor character) and geotiffs (for example, shaded relief) are also included for each publication. For those who do not own the full suite of ESRI GIS and mapping software, the data can be read using ESRI ArcReader, a free viewer that is available at http://www.esri.com/software/arcgis/arcreader/index.html (last accessed September 20, 2013). The California Seafloor Mapping Program is a collaborative venture between numerous different federal and state agencies, academia, and the private sector. CSMP partners include the California Coastal Conservancy, the California Ocean Protection Council, the California Department of Fish and Wildlife, the California Geological Survey, California State University at Monterey Bay’s Seafloor Mapping Lab, Moss Landing Marine Laboratories Center for Habitat Studies, Fugro Pelagos, Pacific Gas and Electric Company, National Oceanic and Atmospheric Administration (NOAA, including National Ocean Service–Office of Coast Surveys, National Marine Sanctuaries, and National Marine Fisheries Service), U.S. Army Corps of Engineers, the Bureau of Ocean Energy Management, the National Park Service, and the U.S. Geological Survey. These web services for the Offshore of Half Moon Bay map area includes data layers that are associated to GIS and map sheets available from the USGS CSMP web page at https://walrus.wr.usgs.gov/mapping/csmp/index.html. Each published CSMP map area includes a data catalog of geographic information system (GIS) files; map sheets that contain explanatory text; and an associated descriptive pamphlet. This web service represents the available data layers for this map area. Data was combined from different sonar surveys to generate a comprehensive high-resolution bathymetry and acoustic-backscatter coverage of the map area. These data reveal a range of physiographic including exposed bedrock outcrops, large fields of sand waves, as well as many human impacts on the seafloor. To validate geological and biological interpretations of the sonar data, the U.S. Geological Survey towed a camera sled over specific offshore locations, collecting both video and photographic imagery; these “ground-truth” surveying data are available from the CSMP Video and Photograph Portal at https://doi.org/10.5066/F7J1015K. The “seafloor character” data layer shows classifications of the seafloor on the basis of depth, slope, rugosity (ruggedness), and backscatter intensity and which is further informed by the ground-truth-survey imagery. The “potential habitats” polygons are delineated on the basis of substrate type, geomorphology, seafloor process, or other attributes that may provide a habitat for a specific species or assemblage of organisms. Representative seismic-reflection profile data from the map area is also include and provides information on the subsurface stratigraphy and structure of the map area. The distribution and thickness of young sediment (deposited over the past about 21,000 years, during the most recent sea-level rise) is interpreted on the basis of the seismic-reflection data. The geologic polygons merge onshore geologic mapping (compiled from existing maps by the California Geological Survey) and new offshore geologic mapping that is based on integration of high-resolution bathymetry and backscatter imagery seafloor-sediment and rock samplesdigital camera and video imagery, and high-resolution seismic-reflection profiles. The information provided by the map sheets, pamphlet, and data catalog has a broad range of applications. High-resolution bathymetry, acoustic backscatter, ground-truth-surveying imagery, and habitat mapping all contribute to habitat characterization and ecosystem-based management by providing essential data for delineation of marine protected areas and ecosystem restoration. Many of the maps provide high-resolution baselines that will be critical for monitoring environmental change associated with climate change, coastal development, or other forcings. High-resolution bathymetry is a critical component for modeling coastal flooding caused by storms and tsunamis, as well as inundation associated with longer term sea-level rise. Seismic-reflection and bathymetric data help characterize earthquake and tsunami sources, critical for natural-hazard assessments of coastal zones. Information on sediment distribution and thickness is essential to the understanding of local and regional sediment transport, as well as the development of regional sediment-management plans. In addition, siting of any new offshore infrastructure (for example, pipelines, cables, or renewable-energy facilities) will depend on high-resolution mapping. Finally, this mapping will both stimulate and enable new scientific research and also raise public awareness of, and education about, coastal environments and issues. Web services were created using an ArcGIS service definition file. The ArcGIS REST service and OGC WMS service include all Offshore of Half Moon Bay map area data layers. Data layers are symbolized as shown on the associated map sheets.

In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ecosystems as part of the design and proposal process for the establishment of Marine Protected Areas. A focus of CSMP is to map California’s State Waters with consistent methods at a consistent scale. The CSMP approach is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar data (the undersea equivalent of satellite remote-sensing data in terrestrial mapping), acoustic backscatter, seafloor video, seafloor photography, high-resolution seismic-reflection profiles, and bottom-sediment sampling data. The map products display seafloor morphology and character, identify potential marine benthic habitats, and illustrate both the surficial seafloor geology and shallow (to about 100 m) subsurface geology. It is emphasized that the more interpretive habitat and geology data rely on the integration of multiple, new high-resolution datasets and that mapping at small scales would not be possible without such data. This approach and CSMP planning is based in part on recommendations of the Marine Mapping Planning Workshop (Kvitek and others, 2006), attended by coastal and marine managers and scientists from around the state. That workshop established geographic priorities for a coastal mapping project and identified the need for coverage of “lands” from the shore strand line (defined as Mean Higher High Water; MHHW) out to the 3-nautical-mile (5.6-km) limit of California’s State Waters. Unfortunately, surveying the zone from MHHW out to 10-m water depth is not consistently possible using ship-based surveying methods, owing to sea state (for example, waves, wind, or currents), kelp coverage, and shallow rock outcrops. Accordingly, some of the data presented in this series commonly do not cover the zone from the shore out to 10-m depth. This data is part of a series of online U.S. Geological Survey (USGS) publications, each of which includes several map sheets, some explanatory text, and a descriptive pamphlet. Each map sheet is published as a PDF file. Geographic information system (GIS) files that contain both ESRI ArcGIS raster grids (for example, bathymetry, seafloor character) and geotiffs (for example, shaded relief) are also included for each publication. For those who do not own the full suite of ESRI GIS and mapping software, the data can be read using ESRI ArcReader, a free viewer that is available at http://www.esri.com/software/arcgis/arcreader/index.html (last accessed September 20, 2013). The California Seafloor Mapping Program is a collaborative venture between numerous different federal and state agencies, academia, and the private sector. CSMP partners include the California Coastal Conservancy, the California Ocean Protection Council, the California Department of Fish and Wildlife, the California Geological Survey, California State University at Monterey Bay’s Seafloor Mapping Lab, Moss Landing Marine Laboratories Center for Habitat Studies, Fugro Pelagos, Pacific Gas and Electric Company, National Oceanic and Atmospheric Administration (NOAA, including National Ocean Service–Office of Coast Surveys, National Marine Sanctuaries, and National Marine Fisheries Service), U.S. Army Corps of Engineers, the Bureau of Ocean Energy Management, the National Park Service, and the U.S. Geological Survey. These web services for the Hueneme Canyon map area includes data layers that are associated to GIS and map sheets available from the USGS CSMP web page at https://walrus.wr.usgs.gov/mapping/csmp/index.html. Each published CSMP map area includes a data catalog of geographic information system (GIS) files; map sheets that contain explanatory text; and an associated descriptive pamphlet. This web service represents the available data layers for this map area. Data was combined from different sonar surveys to generate a comprehensive high-resolution bathymetry and acoustic-backscatter coverage of the map area. These data reveal a range of physiographic including exposed bedrock outcrops, large fields of sand waves, as well as many human impacts on the seafloor. To validate geological and biological interpretations of the sonar data, the U.S. Geological Survey towed a camera sled over specific offshore locations, collecting both video and photographic imagery; these “ground-truth” surveying data are available from the CSMP Video and Photograph Portal at https://doi.org/10.5066/F7J1015K. The “seafloor character” data layer shows classifications of the seafloor on the basis of depth, slope, rugosity (ruggedness), and backscatter intensity and which is further informed by the ground-truth-survey imagery. The “potential habitats” polygons are delineated on the basis of substrate type, geomorphology, seafloor process, or other attributes that may provide a habitat for a specific species or assemblage of organisms. Representative seismic-reflection profile data from the map area is also include and provides information on the subsurface stratigraphy and structure of the map area. The distribution and thickness of young sediment (deposited over the past about 21,000 years, during the most recent sea-level rise) is interpreted on the basis of the seismic-reflection data. The geologic polygons merge onshore geologic mapping (compiled from existing maps by the California Geological Survey) and new offshore geologic mapping that is based on integration of high-resolution bathymetry and backscatter imagery seafloor-sediment and rock samplesdigital camera and video imagery, and high-resolution seismic-reflection profiles. The information provided by the map sheets, pamphlet, and data catalog has a broad range of applications. High-resolution bathymetry, acoustic backscatter, ground-truth-surveying imagery, and habitat mapping all contribute to habitat characterization and ecosystem-based management by providing essential data for delineation of marine protected areas and ecosystem restoration. Many of the maps provide high-resolution baselines that will be critical for monitoring environmental change associated with climate change, coastal development, or other forcings. High-resolution bathymetry is a critical component for modeling coastal flooding caused by storms and tsunamis, as well as inundation associated with longer term sea-level rise. Seismic-reflection and bathymetric data help characterize earthquake and tsunami sources, critical for natural-hazard assessments of coastal zones. Information on sediment distribution and thickness is essential to the understanding of local and regional sediment transport, as well as the development of regional sediment-management plans. In addition, siting of any new offshore infrastructure (for example, pipelines, cables, or renewable-energy facilities) will depend on high-resolution mapping. Finally, this mapping will both stimulate and enable new scientific research and also raise public awareness of, and education about, coastal environments and issues. Web services were created using an ArcGIS service definition file. The ArcGIS REST service and OGC WMS service include all Hueneme Canyon map area data layers. Data layers are symbolized as shown on the associated map sheets.

In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ecosystems as part of the design and proposal process for the establishment of Marine Protected Areas. A focus of CSMP is to map California’s State Waters with consistent methods at a consistent scale. The CSMP approach is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar data (the undersea equivalent of satellite remote-sensing data in terrestrial mapping), acoustic backscatter, seafloor video, seafloor photography, high-resolution seismic-reflection profiles, and bottom-sediment sampling data. The map products display seafloor morphology and character, identify potential marine benthic habitats, and illustrate both the surficial seafloor geology and shallow (to about 100 m) subsurface geology. It is emphasized that the more interpretive habitat and geology data rely on the integration of multiple, new high-resolution datasets and that mapping at small scales would not be possible without such data. This approach and CSMP planning is based in part on recommendations of the Marine Mapping Planning Workshop (Kvitek and others, 2006), attended by coastal and marine managers and scientists from around the state. That workshop established geographic priorities for a coastal mapping project and identified the need for coverage of “lands” from the shore strand line (defined as Mean Higher High Water; MHHW) out to the 3-nautical-mile (5.6-km) limit of California’s State Waters. Unfortunately, surveying the zone from MHHW out to 10-m water depth is not consistently possible using ship-based surveying methods, owing to sea state (for example, waves, wind, or currents), kelp coverage, and shallow rock outcrops. Accordingly, some of the data presented in this series commonly do not cover the zone from the shore out to 10-m depth. This data is part of a series of online U.S. Geological Survey (USGS) publications, each of which includes several map sheets, some explanatory text, and a descriptive pamphlet. Each map sheet is published as a PDF file. Geographic information system (GIS) files that contain both ESRI ArcGIS raster grids (for example, bathymetry, seafloor character) and geotiffs (for example, shaded relief) are also included for each publication. For those who do not own the full suite of ESRI GIS and mapping software, the data can be read using ESRI ArcReader, a free viewer that is available at http://www.esri.com/software/arcgis/arcreader/index.html (last accessed September 20, 2013). The California Seafloor Mapping Program is a collaborative venture between numerous different federal and state agencies, academia, and the private sector. CSMP partners include the California Coastal Conservancy, the California Ocean Protection Council, the California Department of Fish and Wildlife, the California Geological Survey, California State University at Monterey Bay’s Seafloor Mapping Lab, Moss Landing Marine Laboratories Center for Habitat Studies, Fugro Pelagos, Pacific Gas and Electric Company, National Oceanic and Atmospheric Administration (NOAA, including National Ocean Service–Office of Coast Surveys, National Marine Sanctuaries, and National Marine Fisheries Service), U.S. Army Corps of Engineers, the Bureau of Ocean Energy Management, the National Park Service, and the U.S. Geological Survey. These web services for the Offshore Pacifica map area includes data layers that are associated to GIS and map sheets available from the USGS CSMP web page at https://walrus.wr.usgs.gov/mapping/csmp/index.html. Each published CSMP map area includes a data catalog of geographic information system (GIS) files; map sheets that contain explanatory text; and an associated descriptive pamphlet. This web service represents the available data layers for this map area. Data was combined from different sonar surveys to generate a comprehensive high-resolution bathymetry and acoustic-backscatter coverage of the map area. These data reveal a range of physiographic including exposed bedrock outcrops, large fields of sand waves, as well as many human impacts on the seafloor. To validate geological and biological interpretations of the sonar data, the U.S. Geological Survey towed a camera sled over specific offshore locations, collecting both video and photographic imagery; these “ground-truth” surveying data are available from the CSMP Video and Photograph Portal at https://doi.org/10.5066/F7J1015K. The “seafloor character” data layer shows classifications of the seafloor on the basis of depth, slope, rugosity (ruggedness), and backscatter intensity and which is further informed by the ground-truth-survey imagery. The “potential habitats” polygons are delineated on the basis of substrate type, geomorphology, seafloor process, or other attributes that may provide a habitat for a specific species or assemblage of organisms. Representative seismic-reflection profile data from the map area is also include and provides information on the subsurface stratigraphy and structure of the map area. The distribution and thickness of young sediment (deposited over the past about 21,000 years, during the most recent sea-level rise) is interpreted on the basis of the seismic-reflection data. The geologic polygons merge onshore geologic mapping (compiled from existing maps by the California Geological Survey) and new offshore geologic mapping that is based on integration of high-resolution bathymetry and backscatter imagery seafloor-sediment and rock samplesdigital camera and video imagery, and high-resolution seismic-reflection profiles. The information provided by the map sheets, pamphlet, and data catalog has a broad range of applications. High-resolution bathymetry, acoustic backscatter, ground-truth-surveying imagery, and habitat mapping all contribute to habitat characterization and ecosystem-based management by providing essential data for delineation of marine protected areas and ecosystem restoration. Many of the maps provide high-resolution baselines that will be critical for monitoring environmental change associated with climate change, coastal development, or other forcings. High-resolution bathymetry is a critical component for modeling coastal flooding caused by storms and tsunamis, as well as inundation associated with longer term sea-level rise. Seismic-reflection and bathymetric data help characterize earthquake and tsunami sources, critical for natural-hazard assessments of coastal zones. Information on sediment distribution and thickness is essential to the understanding of local and regional sediment transport, as well as the development of regional sediment-management plans. In addition, siting of any new offshore infrastructure (for example, pipelines, cables, or renewable-energy facilities) will depend on high-resolution mapping. Finally, this mapping will both stimulate and enable new scientific research and also raise public awareness of, and education about, coastal environments and issues. Web services were created using an ArcGIS service definition file. The ArcGIS REST service and OGC WMS service include all Offshore Pacifica map area data layers. Data layers are symbolized as shown on the associated map sheets.

In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ecosystems as part of the design and proposal process for the establishment of Marine Protected Areas. A focus of CSMP is to map California’s State Waters with consistent methods at a consistent scale. The CSMP approach is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar data (the undersea equivalent of satellite remote-sensing data in terrestrial mapping), acoustic backscatter, seafloor video, seafloor photography, high-resolution seismic-reflection profiles, and bottom-sediment sampling data. The map products display seafloor morphology and character, identify potential marine benthic habitats, and illustrate both the surficial seafloor geology and shallow (to about 100 m) subsurface geology. It is emphasized that the more interpretive habitat and geology data rely on the integration of multiple, new high-resolution datasets and that mapping at small scales would not be possible without such data. This approach and CSMP planning is based in part on recommendations of the Marine Mapping Planning Workshop (Kvitek and others, 2006), attended by coastal and marine managers and scientists from around the state. That workshop established geographic priorities for a coastal mapping project and identified the need for coverage of “lands” from the shore strand line (defined as Mean Higher High Water; MHHW) out to the 3-nautical-mile (5.6-km) limit of California’s State Waters. Unfortunately, surveying the zone from MHHW out to 10-m water depth is not consistently possible using ship-based surveying methods, owing to sea state (for example, waves, wind, or currents), kelp coverage, and shallow rock outcrops. Accordingly, some of the data presented in this series commonly do not cover the zone from the shore out to 10-m depth. This data is part of a series of online U.S. Geological Survey (USGS) publications, each of which includes several map sheets, some explanatory text, and a descriptive pamphlet. Each map sheet is published as a PDF file. Geographic information system (GIS) files that contain both ESRI ArcGIS raster grids (for example, bathymetry, seafloor character) and geotiffs (for example, shaded relief) are also included for each publication. For those who do not own the full suite of ESRI GIS and mapping software, the data can be read using ESRI ArcReader, a free viewer that is available at http://www.esri.com/software/arcgis/arcreader/index.html (last accessed September 20, 2013). The California Seafloor Mapping Program is a collaborative venture between numerous different federal and state agencies, academia, and the private sector. CSMP partners include the California Coastal Conservancy, the California Ocean Protection Council, the California Department of Fish and Wildlife, the California Geological Survey, California State University at Monterey Bay’s Seafloor Mapping Lab, Moss Landing Marine Laboratories Center for Habitat Studies, Fugro Pelagos, Pacific Gas and Electric Company, National Oceanic and Atmospheric Administration (NOAA, including National Ocean Service–Office of Coast Surveys, National Marine Sanctuaries, and National Marine Fisheries Service), U.S. Army Corps of Engineers, the Bureau of Ocean Energy Management, the National Park Service, and the U.S. Geological Survey. These web services for the Offshore of Point Reyes map area includes data layers that are associated to GIS and map sheets available from the USGS CSMP web page at https://walrus.wr.usgs.gov/mapping/csmp/index.html. Each published CSMP map area includes a data catalog of geographic information system (GIS) files; map sheets that contain explanatory text; and an associated descriptive pamphlet. This web service represents the available data layers for this map area. Data was combined from different sonar surveys to generate a comprehensive high-resolution bathymetry and acoustic-backscatter coverage of the map area. These data reveal a range of physiographic including exposed bedrock outcrops, large fields of sand waves, as well as many human impacts on the seafloor. To validate geological and biological interpretations of the sonar data, the U.S. Geological Survey towed a camera sled over specific offshore locations, collecting both video and photographic imagery; these “ground-truth” surveying data are available from the CSMP Video and Photograph Portal at https://doi.org/10.5066/F7J1015K. The “seafloor character” data layer shows classifications of the seafloor on the basis of depth, slope, rugosity (ruggedness), and backscatter intensity and which is further informed by the ground-truth-survey imagery. The “potential habitats” polygons are delineated on the basis of substrate type, geomorphology, seafloor process, or other attributes that may provide a habitat for a specific species or assemblage of organisms. Representative seismic-reflection profile data from the map area is also include and provides information on the subsurface stratigraphy and structure of the map area. The distribution and thickness of young sediment (deposited over the past about 21,000 years, during the most recent sea-level rise) is interpreted on the basis of the seismic-reflection data. The geologic polygons merge onshore geologic mapping (compiled from existing maps by the California Geological Survey) and new offshore geologic mapping that is based on integration of high-resolution bathymetry and backscatter imagery seafloor-sediment and rock samplesdigital camera and video imagery, and high-resolution seismic-reflection profiles. The information provided by the map sheets, pamphlet, and data catalog has a broad range of applications. High-resolution bathymetry, acoustic backscatter, ground-truth-surveying imagery, and habitat mapping all contribute to habitat characterization and ecosystem-based management by providing essential data for delineation of marine protected areas and ecosystem restoration. Many of the maps provide high-resolution baselines that will be critical for monitoring environmental change associated with climate change, coastal development, or other forcings. High-resolution bathymetry is a critical component for modeling coastal flooding caused by storms and tsunamis, as well as inundation associated with longer term sea-level rise. Seismic-reflection and bathymetric data help characterize earthquake and tsunami sources, critical for natural-hazard assessments of coastal zones. Information on sediment distribution and thickness is essential to the understanding of local and regional sediment transport, as well as the development of regional sediment-management plans. In addition, siting of any new offshore infrastructure (for example, pipelines, cables, or renewable-energy facilities) will depend on high-resolution mapping. Finally, this mapping will both stimulate and enable new scientific research and also raise public awareness of, and education about, coastal environments and issues. Web services were created using an ArcGIS service definition file. The ArcGIS REST service and OGC WMS service include all Offshore of Point Reyes map area data layers. Data layers are symbolized as shown on the associated map sheets.

In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ecosystems as part of the design and proposal process for the establishment of Marine Protected Areas. A focus of CSMP is to map California’s State Waters with consistent methods at a consistent scale. The CSMP approach is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar data (the undersea equivalent of satellite remote-sensing data in terrestrial mapping), acoustic backscatter, seafloor video, seafloor photography, high-resolution seismic-reflection profiles, and bottom-sediment sampling data. The map products display seafloor morphology and character, identify potential marine benthic habitats, and illustrate both the surficial seafloor geology and shallow (to about 100 m) subsurface geology. It is emphasized that the more interpretive habitat and geology data rely on the integration of multiple, new high-resolution datasets and that mapping at small scales would not be possible without such data. This approach and CSMP planning is based in part on recommendations of the Marine Mapping Planning Workshop (Kvitek and others, 2006), attended by coastal and marine managers and scientists from around the state. That workshop established geographic priorities for a coastal mapping project and identified the need for coverage of “lands” from the shore strand line (defined as Mean Higher High Water; MHHW) out to the 3-nautical-mile (5.6-km) limit of California’s State Waters. Unfortunately, surveying the zone from MHHW out to 10-m water depth is not consistently possible using ship-based surveying methods, owing to sea state (for example, waves, wind, or currents), kelp coverage, and shallow rock outcrops. Accordingly, some of the data presented in this series commonly do not cover the zone from the shore out to 10-m depth. This data is part of a series of online U.S. Geological Survey (USGS) publications, each of which includes several map sheets, some explanatory text, and a descriptive pamphlet. Each map sheet is published as a PDF file. Geographic information system (GIS) files that contain both ESRI ArcGIS raster grids (for example, bathymetry, seafloor character) and geotiffs (for example, shaded relief) are also included for each publication. For those who do not own the full suite of ESRI GIS and mapping software, the data can be read using ESRI ArcReader, a free viewer that is available at http://www.esri.com/software/arcgis/arcreader/index.html (last accessed September 20, 2013). The California Seafloor Mapping Program is a collaborative venture between numerous different federal and state agencies, academia, and the private sector. CSMP partners include the California Coastal Conservancy, the California Ocean Protection Council, the California Department of Fish and Wildlife, the California Geological Survey, California State University at Monterey Bay’s Seafloor Mapping Lab, Moss Landing Marine Laboratories Center for Habitat Studies, Fugro Pelagos, Pacific Gas and Electric Company, National Oceanic and Atmospheric Administration (NOAA, including National Ocean Service–Office of Coast Surveys, National Marine Sanctuaries, and National Marine Fisheries Service), U.S. Army Corps of Engineers, the Bureau of Ocean Energy Management, the National Park Service, and the U.S. Geological Survey. These web services for the Offshore of Refugio Beach map area includes data layers that are associated to GIS and map sheets available from the USGS CSMP web page at https://walrus.wr.usgs.gov/mapping/csmp/index.html. Each published CSMP map area includes a data catalog of geographic information system (GIS) files; map sheets that contain explanatory text; and an associated descriptive pamphlet. This web service represents the available data layers for this map area. Data was combined from different sonar surveys to generate a comprehensive high-resolution bathymetry and acoustic-backscatter coverage of the map area. These data reveal a range of physiographic including exposed bedrock outcrops, large fields of sand waves, as well as many human impacts on the seafloor. To validate geological and biological interpretations of the sonar data, the U.S. Geological Survey towed a camera sled over specific offshore locations, collecting both video and photographic imagery; these “ground-truth” surveying data are available from the CSMP Video and Photograph Portal at https://doi.org/10.5066/F7J1015K. The “seafloor character” data layer shows classifications of the seafloor on the basis of depth, slope, rugosity (ruggedness), and backscatter intensity and which is further informed by the ground-truth-survey imagery. The “potential habitats” polygons are delineated on the basis of substrate type, geomorphology, seafloor process, or other attributes that may provide a habitat for a specific species or assemblage of organisms. Representative seismic-reflection profile data from the map area is also include and provides information on the subsurface stratigraphy and structure of the map area. The distribution and thickness of young sediment (deposited over the past about 21,000 years, during the most recent sea-level rise) is interpreted on the basis of the seismic-reflection data. The geologic polygons merge onshore geologic mapping (compiled from existing maps by the California Geological Survey) and new offshore geologic mapping that is based on integration of high-resolution bathymetry and backscatter imagery seafloor-sediment and rock samplesdigital camera and video imagery, and high-resolution seismic-reflection profiles. The information provided by the map sheets, pamphlet, and data catalog has a broad range of applications. High-resolution bathymetry, acoustic backscatter, ground-truth-surveying imagery, and habitat mapping all contribute to habitat characterization and ecosystem-based management by providing essential data for delineation of marine protected areas and ecosystem restoration. Many of the maps provide high-resolution baselines that will be critical for monitoring environmental change associated with climate change, coastal development, or other forcings. High-resolution bathymetry is a critical component for modeling coastal flooding caused by storms and tsunamis, as well as inundation associated with longer term sea-level rise. Seismic-reflection and bathymetric data help characterize earthquake and tsunami sources, critical for natural-hazard assessments of coastal zones. Information on sediment distribution and thickness is essential to the understanding of local and regional sediment transport, as well as the development of regional sediment-management plans. In addition, siting of any new offshore infrastructure (for example, pipelines, cables, or renewable-energy facilities) will depend on high-resolution mapping. Finally, this mapping will both stimulate and enable new scientific research and also raise public awareness of, and education about, coastal environments and issues. Web services were created using an ArcGIS service definition file. The ArcGIS REST service and OGC WMS service include all Offshore of Refugio Beach map area data layers. Data layers are symbolized as shown on the associated map sheets.

In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ecosystems as part of the design and proposal process for the establishment of Marine Protected Areas. A focus of CSMP is to map California’s State Waters with consistent methods at a consistent scale. The CSMP approach is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar data (the undersea equivalent of satellite remote-sensing data in terrestrial mapping), acoustic backscatter, seafloor video, seafloor photography, high-resolution seismic-reflection profiles, and bottom-sediment sampling data. The map products display seafloor morphology and character, identify potential marine benthic habitats, and illustrate both the surficial seafloor geology and shallow (to about 100 m) subsurface geology. It is emphasized that the more interpretive habitat and geology data rely on the integration of multiple, new high-resolution datasets and that mapping at small scales would not be possible without such data. This approach and CSMP planning is based in part on recommendations of the Marine Mapping Planning Workshop (Kvitek and others, 2006), attended by coastal and marine managers and scientists from around the state. That workshop established geographic priorities for a coastal mapping project and identified the need for coverage of “lands” from the shore strand line (defined as Mean Higher High Water; MHHW) out to the 3-nautical-mile (5.6-km) limit of California’s State Waters. Unfortunately, surveying the zone from MHHW out to 10-m water depth is not consistently possible using ship-based surveying methods, owing to sea state (for example, waves, wind, or currents), kelp coverage, and shallow rock outcrops. Accordingly, some of the data presented in this series commonly do not cover the zone from the shore out to 10-m depth. This data is part of a series of online U.S. Geological Survey (USGS) publications, each of which includes several map sheets, some explanatory text, and a descriptive pamphlet. Each map sheet is published as a PDF file. Geographic information system (GIS) files that contain both ESRI ArcGIS raster grids (for example, bathymetry, seafloor character) and geotiffs (for example, shaded relief) are also included for each publication. For those who do not own the full suite of ESRI GIS and mapping software, the data can be read using ESRI ArcReader, a free viewer that is available at http://www.esri.com/software/arcgis/arcreader/index.html (last accessed September 20, 2013). The California Seafloor Mapping Program is a collaborative venture between numerous different federal and state agencies, academia, and the private sector. CSMP partners include the California Coastal Conservancy, the California Ocean Protection Council, the California Department of Fish and Wildlife, the California Geological Survey, California State University at Monterey Bay’s Seafloor Mapping Lab, Moss Landing Marine Laboratories Center for Habitat Studies, Fugro Pelagos, Pacific Gas and Electric Company, National Oceanic and Atmospheric Administration (NOAA, including National Ocean Service–Office of Coast Surveys, National Marine Sanctuaries, and National Marine Fisheries Service), U.S. Army Corps of Engineers, the Bureau of Ocean Energy Management, the National Park Service, and the U.S. Geological Survey. These web services for the Salt Point to Drakes Bay map area includes data layers that are associated to GIS and map sheets available from the USGS CSMP web page at https://walrus.wr.usgs.gov/mapping/csmp/index.html. Each published CSMP map area includes a data catalog of geographic information system (GIS) files; map sheets that contain explanatory text; and an associated descriptive pamphlet. This web service represents the available data layers for this map area. Data was combined from different sonar surveys to generate a comprehensive high-resolution bathymetry and acoustic-backscatter coverage of the map area. These data reveal a range of physiographic including exposed bedrock outcrops, large fields of sand waves, as well as many human impacts on the seafloor. To validate geological and biological interpretations of the sonar data, the U.S. Geological Survey towed a camera sled over specific offshore locations, collecting both video and photographic imagery; these “ground-truth” surveying data are available from the CSMP Video and Photograph Portal at https://doi.org/10.5066/F7J1015K. The “seafloor character” data layer shows classifications of the seafloor on the basis of depth, slope, rugosity (ruggedness), and backscatter intensity and which is further informed by the ground-truth-survey imagery. The “potential habitats” polygons are delineated on the basis of substrate type, geomorphology, seafloor process, or other attributes that may provide a habitat for a specific species or assemblage of organisms. Representative seismic-reflection profile data from the map area is also include and provides information on the subsurface stratigraphy and structure of the map area. The distribution and thickness of young sediment (deposited over the past about 21,000 years, during the most recent sea-level rise) is interpreted on the basis of the seismic-reflection data. The geologic polygons merge onshore geologic mapping (compiled from existing maps by the California Geological Survey) and new offshore geologic mapping that is based on integration of high-resolution bathymetry and backscatter imagery seafloor-sediment and rock samplesdigital camera and video imagery, and high-resolution seismic-reflection profiles. The information provided by the map sheets, pamphlet, and data catalog has a broad range of applications. High-resolution bathymetry, acoustic backscatter, ground-truth-surveying imagery, and habitat mapping all contribute to habitat characterization and ecosystem-based management by providing essential data for delineation of marine protected areas and ecosystem restoration. Many of the maps provide high-resolution baselines that will be critical for monitoring environmental change associated with climate change, coastal development, or other forcings. High-resolution bathymetry is a critical component for modeling coastal flooding caused by storms and tsunamis, as well as inundation associated with longer term sea-level rise. Seismic-reflection and bathymetric data help characterize earthquake and tsunami sources, critical for natural-hazard assessments of coastal zones. Information on sediment distribution and thickness is essential to the understanding of local and regional sediment transport, as well as the development of regional sediment-management plans. In addition, siting of any new offshore infrastructure (for example, pipelines, cables, or renewable-energy facilities) will depend on high-resolution mapping. Finally, this mapping will both stimulate and enable new scientific research and also raise public awareness of, and education about, coastal environments and issues. Web services were created using an ArcGIS service definition file. The ArcGIS REST service and OGC WMS service include all Salt Point to Drakes Bay map area data layers. Data layers are symbolized as shown on the associated map sheets.

In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ecosystems as part of the design and proposal process for the establishment of Marine Protected Areas. A focus of CSMP is to map California’s State Waters with consistent methods at a consistent scale. The CSMP approach is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar data (the undersea equivalent of satellite remote-sensing data in terrestrial mapping), acoustic backscatter, seafloor video, seafloor photography, high-resolution seismic-reflection profiles, and bottom-sediment sampling data. The map products display seafloor morphology and character, identify potential marine benthic habitats, and illustrate both the surficial seafloor geology and shallow (to about 100 m) subsurface geology. It is emphasized that the more interpretive habitat and geology data rely on the integration of multiple, new high-resolution datasets and that mapping at small scales would not be possible without such data. This approach and CSMP planning is based in part on recommendations of the Marine Mapping Planning Workshop (Kvitek and others, 2006), attended by coastal and marine managers and scientists from around the state. That workshop established geographic priorities for a coastal mapping project and identified the need for coverage of “lands” from the shore strand line (defined as Mean Higher High Water; MHHW) out to the 3-nautical-mile (5.6-km) limit of California’s State Waters. Unfortunately, surveying the zone from MHHW out to 10-m water depth is not consistently possible using ship-based surveying methods, owing to sea state (for example, waves, wind, or currents), kelp coverage, and shallow rock outcrops. Accordingly, some of the data presented in this series commonly do not cover the zone from the shore out to 10-m depth. This data is part of a series of online U.S. Geological Survey (USGS) publications, each of which includes several map sheets, some explanatory text, and a descriptive pamphlet. Each map sheet is published as a PDF file. Geographic information system (GIS) files that contain both ESRI ArcGIS raster grids (for example, bathymetry, seafloor character) and geotiffs (for example, shaded relief) are also included for each publication. For those who do not own the full suite of ESRI GIS and mapping software, the data can be read using ESRI ArcReader, a free viewer that is available at http://www.esri.com/software/arcgis/arcreader/index.html (last accessed September 20, 2013). The California Seafloor Mapping Program is a collaborative venture between numerous different federal and state agencies, academia, and the private sector. CSMP partners include the California Coastal Conservancy, the California Ocean Protection Council, the California Department of Fish and Wildlife, the California Geological Survey, California State University at Monterey Bay’s Seafloor Mapping Lab, Moss Landing Marine Laboratories Center for Habitat Studies, Fugro Pelagos, Pacific Gas and Electric Company, National Oceanic and Atmospheric Administration (NOAA, including National Ocean Service–Office of Coast Surveys, National Marine Sanctuaries, and National Marine Fisheries Service), U.S. Army Corps of Engineers, the Bureau of Ocean Energy Management, the National Park Service, and the U.S. Geological Survey. These web services for the Offshore of Salt Point map area includes data layers that are associated to GIS and map sheets available from the USGS CSMP web page at https://walrus.wr.usgs.gov/mapping/csmp/index.html. Each published CSMP map area includes a data catalog of geographic information system (GIS) files; map sheets that contain explanatory text; and an associated descriptive pamphlet. This web service represents the available data layers for this map area. Data was combined from different sonar surveys to generate a comprehensive high-resolution bathymetry and acoustic-backscatter coverage of the map area. These data reveal a range of physiographic including exposed bedrock outcrops, large fields of sand waves, as well as many human impacts on the seafloor. To validate geological and biological interpretations of the sonar data, the U.S. Geological Survey towed a camera sled over specific offshore locations, collecting both video and photographic imagery; these “ground-truth” surveying data are available from the CSMP Video and Photograph Portal at https://doi.org/10.5066/F7J1015K. The “seafloor character” data layer shows classifications of the seafloor on the basis of depth, slope, rugosity (ruggedness), and backscatter intensity and which is further informed by the ground-truth-survey imagery. The “potential habitats” polygons are delineated on the basis of substrate type, geomorphology, seafloor process, or other attributes that may provide a habitat for a specific species or assemblage of organisms. Representative seismic-reflection profile data from the map area is also include and provides information on the subsurface stratigraphy and structure of the map area. The distribution and thickness of young sediment (deposited over the past about 21,000 years, during the most recent sea-level rise) is interpreted on the basis of the seismic-reflection data. The geologic polygons merge onshore geologic mapping (compiled from existing maps by the California Geological Survey) and new offshore geologic mapping that is based on integration of high-resolution bathymetry and backscatter imagery seafloor-sediment and rock samplesdigital camera and video imagery, and high-resolution seismic-reflection profiles. The information provided by the map sheets, pamphlet, and data catalog has a broad range of applications. High-resolution bathymetry, acoustic backscatter, ground-truth-surveying imagery, and habitat mapping all contribute to habitat characterization and ecosystem-based management by providing essential data for delineation of marine protected areas and ecosystem restoration. Many of the maps provide high-resolution baselines that will be critical for monitoring environmental change associated with climate change, coastal development, or other forcings. High-resolution bathymetry is a critical component for modeling coastal flooding caused by storms and tsunamis, as well as inundation associated with longer term sea-level rise. Seismic-reflection and bathymetric data help characterize earthquake and tsunami sources, critical for natural-hazard assessments of coastal zones. Information on sediment distribution and thickness is essential to the understanding of local and regional sediment transport, as well as the development of regional sediment-management plans. In addition, siting of any new offshore infrastructure (for example, pipelines, cables, or renewable-energy facilities) will depend on high-resolution mapping. Finally, this mapping will both stimulate and enable new scientific research and also raise public awareness of, and education about, coastal environments and issues. Web services were created using an ArcGIS service definition file. The ArcGIS REST service and OGC WMS service include all Offshore of Salt Point map area data layers. Data layers are symbolized as shown on the associated map sheets.

In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ecosystems as part of the design and proposal process for the establishment of Marine Protected Areas. A focus of CSMP is to map California’s State Waters with consistent methods at a consistent scale. The CSMP approach is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar data (the undersea equivalent of satellite remote-sensing data in terrestrial mapping), acoustic backscatter, seafloor video, seafloor photography, high-resolution seismic-reflection profiles, and bottom-sediment sampling data. The map products display seafloor morphology and character, identify potential marine benthic habitats, and illustrate both the surficial seafloor geology and shallow (to about 100 m) subsurface geology. It is emphasized that the more interpretive habitat and geology data rely on the integration of multiple, new high-resolution datasets and that mapping at small scales would not be possible without such data. This approach and CSMP planning is based in part on recommendations of the Marine Mapping Planning Workshop (Kvitek and others, 2006), attended by coastal and marine managers and scientists from around the state. That workshop established geographic priorities for a coastal mapping project and identified the need for coverage of “lands” from the shore strand line (defined as Mean Higher High Water; MHHW) out to the 3-nautical-mile (5.6-km) limit of California’s State Waters. Unfortunately, surveying the zone from MHHW out to 10-m water depth is not consistently possible using ship-based surveying methods, owing to sea state (for example, waves, wind, or currents), kelp coverage, and shallow rock outcrops. Accordingly, some of the data presented in this series commonly do not cover the zone from the shore out to 10-m depth. This data is part of a series of online U.S. Geological Survey (USGS) publications, each of which includes several map sheets, some explanatory text, and a descriptive pamphlet. Each map sheet is published as a PDF file. Geographic information system (GIS) files that contain both ESRI ArcGIS raster grids (for example, bathymetry, seafloor character) and geotiffs (for example, shaded relief) are also included for each publication. For those who do not own the full suite of ESRI GIS and mapping software, the data can be read using ESRI ArcReader, a free viewer that is available at http://www.esri.com/software/arcgis/arcreader/index.html (last accessed September 20, 2013). The California Seafloor Mapping Program is a collaborative venture between numerous different federal and state agencies, academia, and the private sector. CSMP partners include the California Coastal Conservancy, the California Ocean Protection Council, the California Department of Fish and Wildlife, the California Geological Survey, California State University at Monterey Bay’s Seafloor Mapping Lab, Moss Landing Marine Laboratories Center for Habitat Studies, Fugro Pelagos, Pacific Gas and Electric Company, National Oceanic and Atmospheric Administration (NOAA, including National Ocean Service–Office of Coast Surveys, National Marine Sanctuaries, and National Marine Fisheries Service), U.S. Army Corps of Engineers, the Bureau of Ocean Energy Management, the National Park Service, and the U.S. Geological Survey. These web services for the Offshore of San Francisco map area includes data layers that are associated to GIS and map sheets available from the USGS CSMP web page at https://walrus.wr.usgs.gov/mapping/csmp/index.html. Each published CSMP map area includes a data catalog of geographic information system (GIS) files; map sheets that contain explanatory text; and an associated descriptive pamphlet. This web service represents the available data layers for this map area. Data was combined from different sonar surveys to generate a comprehensive high-resolution bathymetry and acoustic-backscatter coverage of the map area. These data reveal a range of physiographic including exposed bedrock outcrops, large fields of sand waves, as well as many human impacts on the seafloor. To validate geological and biological interpretations of the sonar data, the U.S. Geological Survey towed a camera sled over specific offshore locations, collecting both video and photographic imagery; these “ground-truth” surveying data are available from the CSMP Video and Photograph Portal at https://doi.org/10.5066/F7J1015K. The “seafloor character” data layer shows classifications of the seafloor on the basis of depth, slope, rugosity (ruggedness), and backscatter intensity and which is further informed by the ground-truth-survey imagery. The “potential habitats” polygons are delineated on the basis of substrate type, geomorphology, seafloor process, or other attributes that may provide a habitat for a specific species or assemblage of organisms. Representative seismic-reflection profile data from the map area is also include and provides information on the subsurface stratigraphy and structure of the map area. The distribution and thickness of young sediment (deposited over the past about 21,000 years, during the most recent sea-level rise) is interpreted on the basis of the seismic-reflection data. The geologic polygons merge onshore geologic mapping (compiled from existing maps by the California Geological Survey) and new offshore geologic mapping that is based on integration of high-resolution bathymetry and backscatter imagery seafloor-sediment and rock samplesdigital camera and video imagery, and high-resolution seismic-reflection profiles. The information provided by the map sheets, pamphlet, and data catalog has a broad range of applications. High-resolution bathymetry, acoustic backscatter, ground-truth-surveying imagery, and habitat mapping all contribute to habitat characterization and ecosystem-based management by providing essential data for delineation of marine protected areas and ecosystem restoration. Many of the maps provide high-resolution baselines that will be critical for monitoring environmental change associated with climate change, coastal development, or other forcings. High-resolution bathymetry is a critical component for modeling coastal flooding caused by storms and tsunamis, as well as inundation associated with longer term sea-level rise. Seismic-reflection and bathymetric data help characterize earthquake and tsunami sources, critical for natural-hazard assessments of coastal zones. Information on sediment distribution and thickness is essential to the understanding of local and regional sediment transport, as well as the development of regional sediment-management plans. In addition, siting of any new offshore infrastructure (for example, pipelines, cables, or renewable-energy facilities) will depend on high-resolution mapping. Finally, this mapping will both stimulate and enable new scientific research and also raise public awareness of, and education about, coastal environments and issues. Web services were created using an ArcGIS service definition file. The ArcGIS REST service and OGC WMS service include all Offshore of San Francisco map area data layers. Data layers are symbolized as shown on the associated map sheets.

In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ecosystems as part of the design and proposal process for the establishment of Marine Protected Areas. A focus of CSMP is to map California’s State Waters with consistent methods at a consistent scale. The CSMP approach is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar data (the undersea equivalent of satellite remote-sensing data in terrestrial mapping), acoustic backscatter, seafloor video, seafloor photography, high-resolution seismic-reflection profiles, and bottom-sediment sampling data. The map products display seafloor morphology and character, identify potential marine benthic habitats, and illustrate both the surficial seafloor geology and shallow (to about 100 m) subsurface geology. It is emphasized that the more interpretive habitat and geology data rely on the integration of multiple, new high-resolution datasets and that mapping at small scales would not be possible without such data. This approach and CSMP planning is based in part on recommendations of the Marine Mapping Planning Workshop (Kvitek and others, 2006), attended by coastal and marine managers and scientists from around the state. That workshop established geographic priorities for a coastal mapping project and identified the need for coverage of “lands” from the shore strand line (defined as Mean Higher High Water; MHHW) out to the 3-nautical-mile (5.6-km) limit of California’s State Waters. Unfortunately, surveying the zone from MHHW out to 10-m water depth is not consistently possible using ship-based surveying methods, owing to sea state (for example, waves, wind, or currents), kelp coverage, and shallow rock outcrops. Accordingly, some of the data presented in this series commonly do not cover the zone from the shore out to 10-m depth. This data is part of a series of online U.S. Geological Survey (USGS) publications, each of which includes several map sheets, some explanatory text, and a descriptive pamphlet. Each map sheet is published as a PDF file. Geographic information system (GIS) files that contain both ESRI ArcGIS raster grids (for example, bathymetry, seafloor character) and geotiffs (for example, shaded relief) are also included for each publication. For those who do not own the full suite of ESRI GIS and mapping software, the data can be read using ESRI ArcReader, a free viewer that is available at http://www.esri.com/software/arcgis/arcreader/index.html (last accessed September 20, 2013). The California Seafloor Mapping Program is a collaborative venture between numerous different federal and state agencies, academia, and the private sector. CSMP partners include the California Coastal Conservancy, the California Ocean Protection Council, the California Department of Fish and Wildlife, the California Geological Survey, California State University at Monterey Bay’s Seafloor Mapping Lab, Moss Landing Marine Laboratories Center for Habitat Studies, Fugro Pelagos, Pacific Gas and Electric Company, National Oceanic and Atmospheric Administration (NOAA, including National Ocean Service–Office of Coast Surveys, National Marine Sanctuaries, and National Marine Fisheries Service), U.S. Army Corps of Engineers, the Bureau of Ocean Energy Management, the National Park Service, and the U.S. Geological Survey. These web services for the Santa Barbara Channel map area includes data layers that are associated to GIS and map sheets available from the USGS CSMP web page at https://walrus.wr.usgs.gov/mapping/csmp/index.html. Each published CSMP map area includes a data catalog of geographic information system (GIS) files; map sheets that contain explanatory text; and an associated descriptive pamphlet. This web service represents the available data layers for this map area. Data was combined from different sonar surveys to generate a comprehensive high-resolution bathymetry and acoustic-backscatter coverage of the map area. These data reveal a range of physiographic including exposed bedrock outcrops, large fields of sand waves, as well as many human impacts on the seafloor. To validate geological and biological interpretations of the sonar data, the U.S. Geological Survey towed a camera sled over specific offshore locations, collecting both video and photographic imagery; these “ground-truth” surveying data are available from the CSMP Video and Photograph Portal at https://doi.org/10.5066/F7J1015K. The “seafloor character” data layer shows classifications of the seafloor on the basis of depth, slope, rugosity (ruggedness), and backscatter intensity and which is further informed by the ground-truth-survey imagery. The “potential habitats” polygons are delineated on the basis of substrate type, geomorphology, seafloor process, or other attributes that may provide a habitat for a specific species or assemblage of organisms. Representative seismic-reflection profile data from the map area is also include and provides information on the subsurface stratigraphy and structure of the map area. The distribution and thickness of young sediment (deposited over the past about 21,000 years, during the most recent sea-level rise) is interpreted on the basis of the seismic-reflection data. The geologic polygons merge onshore geologic mapping (compiled from existing maps by the California Geological Survey) and new offshore geologic mapping that is based on integration of high-resolution bathymetry and backscatter imagery seafloor-sediment and rock samplesdigital camera and video imagery, and high-resolution seismic-reflection profiles. The information provided by the map sheets, pamphlet, and data catalog has a broad range of applications. High-resolution bathymetry, acoustic backscatter, ground-truth-surveying imagery, and habitat mapping all contribute to habitat characterization and ecosystem-based management by providing essential data for delineation of marine protected areas and ecosystem restoration. Many of the maps provide high-resolution baselines that will be critical for monitoring environmental change associated with climate change, coastal development, or other forcings. High-resolution bathymetry is a critical component for modeling coastal flooding caused by storms and tsunamis, as well as inundation associated with longer term sea-level rise. Seismic-reflection and bathymetric data help characterize earthquake and tsunami sources, critical for natural-hazard assessments of coastal zones. Information on sediment distribution and thickness is essential to the understanding of local and regional sediment transport, as well as the development of regional sediment-management plans. In addition, siting of any new offshore infrastructure (for example, pipelines, cables, or renewable-energy facilities) will depend on high-resolution mapping. Finally, this mapping will both stimulate and enable new scientific research and also raise public awareness of, and education about, coastal environments and issues. Web services were created using an ArcGIS service definition file. The ArcGIS REST service and OGC WMS service include all Santa Barbara Channel map area data layers. Data layers are symbolized as shown on the associated map sheets.

In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ecosystems as part of the design and proposal process for the establishment of Marine Protected Areas. A focus of CSMP is to map California’s State Waters with consistent methods at a consistent scale. The CSMP approach is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar data (the undersea equivalent of satellite remote-sensing data in terrestrial mapping), acoustic backscatter, seafloor video, seafloor photography, high-resolution seismic-reflection profiles, and bottom-sediment sampling data. The map products display seafloor morphology and character, identify potential marine benthic habitats, and illustrate both the surficial seafloor geology and shallow (to about 100 m) subsurface geology. It is emphasized that the more interpretive habitat and geology data rely on the integration of multiple, new high-resolution datasets and that mapping at small scales would not be possible without such data. This approach and CSMP planning is based in part on recommendations of the Marine Mapping Planning Workshop (Kvitek and others, 2006), attended by coastal and marine managers and scientists from around the state. That workshop established geographic priorities for a coastal mapping project and identified the need for coverage of “lands” from the shore strand line (defined as Mean Higher High Water; MHHW) out to the 3-nautical-mile (5.6-km) limit of California’s State Waters. Unfortunately, surveying the zone from MHHW out to 10-m water depth is not consistently possible using ship-based surveying methods, owing to sea state (for example, waves, wind, or currents), kelp coverage, and shallow rock outcrops. Accordingly, some of the data presented in this series commonly do not cover the zone from the shore out to 10-m depth. This data is part of a series of online U.S. Geological Survey (USGS) publications, each of which includes several map sheets, some explanatory text, and a descriptive pamphlet. Each map sheet is published as a PDF file. Geographic information system (GIS) files that contain both ESRI ArcGIS raster grids (for example, bathymetry, seafloor character) and geotiffs (for example, shaded relief) are also included for each publication. For those who do not own the full suite of ESRI GIS and mapping software, the data can be read using ESRI ArcReader, a free viewer that is available at http://www.esri.com/software/arcgis/arcreader/index.html (last accessed September 20, 2013). The California Seafloor Mapping Program is a collaborative venture between numerous different federal and state agencies, academia, and the private sector. CSMP partners include the California Coastal Conservancy, the California Ocean Protection Council, the California Department of Fish and Wildlife, the California Geological Survey, California State University at Monterey Bay’s Seafloor Mapping Lab, Moss Landing Marine Laboratories Center for Habitat Studies, Fugro Pelagos, Pacific Gas and Electric Company, National Oceanic and Atmospheric Administration (NOAA, including National Ocean Service–Office of Coast Surveys, National Marine Sanctuaries, and National Marine Fisheries Service), U.S. Army Corps of Engineers, the Bureau of Ocean Energy Management, the National Park Service, and the U.S. Geological Survey. These web services for the Offshore of Santa Barbara map area includes data layers that are associated to GIS and map sheets available from the USGS CSMP web page at https://walrus.wr.usgs.gov/mapping/csmp/index.html. Each published CSMP map area includes a data catalog of geographic information system (GIS) files; map sheets that contain explanatory text; and an associated descriptive pamphlet. This web service represents the available data layers for this map area. Data was combined from different sonar surveys to generate a comprehensive high-resolution bathymetry and acoustic-backscatter coverage of the map area. These data reveal a range of physiographic including exposed bedrock outcrops, large fields of sand waves, as well as many human impacts on the seafloor. To validate geological and biological interpretations of the sonar data, the U.S. Geological Survey towed a camera sled over specific offshore locations, collecting both video and photographic imagery; these “ground-truth” surveying data are available from the CSMP Video and Photograph Portal at https://doi.org/10.5066/F7J1015K. The “seafloor character” data layer shows classifications of the seafloor on the basis of depth, slope, rugosity (ruggedness), and backscatter intensity and which is further informed by the ground-truth-survey imagery. The “potential habitats” polygons are delineated on the basis of substrate type, geomorphology, seafloor process, or other attributes that may provide a habitat for a specific species or assemblage of organisms. Representative seismic-reflection profile data from the map area is also include and provides information on the subsurface stratigraphy and structure of the map area. The distribution and thickness of young sediment (deposited over the past about 21,000 years, during the most recent sea-level rise) is interpreted on the basis of the seismic-reflection data. The geologic polygons merge onshore geologic mapping (compiled from existing maps by the California Geological Survey) and new offshore geologic mapping that is based on integration of high-resolution bathymetry and backscatter imagery seafloor-sediment and rock samplesdigital camera and video imagery, and high-resolution seismic-reflection profiles. The information provided by the map sheets, pamphlet, and data catalog has a broad range of applications. High-resolution bathymetry, acoustic backscatter, ground-truth-surveying imagery, and habitat mapping all contribute to habitat characterization and ecosystem-based management by providing essential data for delineation of marine protected areas and ecosystem restoration. Many of the maps provide high-resolution baselines that will be critical for monitoring environmental change associated with climate change, coastal development, or other forcings. High-resolution bathymetry is a critical component for modeling coastal flooding caused by storms and tsunamis, as well as inundation associated with longer term sea-level rise. Seismic-reflection and bathymetric data help characterize earthquake and tsunami sources, critical for natural-hazard assessments of coastal zones. Information on sediment distribution and thickness is essential to the understanding of local and regional sediment transport, as well as the development of regional sediment-management plans. In addition, siting of any new offshore infrastructure (for example, pipelines, cables, or renewable-energy facilities) will depend on high-resolution mapping. Finally, this mapping will both stimulate and enable new scientific research and also raise public awareness of, and education about, coastal environments and issues. Web services were created using an ArcGIS service definition file. The ArcGIS REST service and OGC WMS service include all Offshore of Santa Barbara to Pescadero Region data layers. Data layers are symbolized as shown on the associated map sheets.

In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ecosystems as part of the design and proposal process for the establishment of Marine Protected Areas. A focus of CSMP is to map California’s State Waters with consistent methods at a consistent scale. The CSMP approach is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar data (the undersea equivalent of satellite remote-sensing data in terrestrial mapping), acoustic backscatter, seafloor video, seafloor photography, high-resolution seismic-reflection profiles, and bottom-sediment sampling data. The map products display seafloor morphology and character, identify potential marine benthic habitats, and illustrate both the surficial seafloor geology and shallow (to about 100 m) subsurface geology. It is emphasized that the more interpretive habitat and geology data rely on the integration of multiple, new high-resolution datasets and that mapping at small scales would not be possible without such data. This approach and CSMP planning is based in part on recommendations of the Marine Mapping Planning Workshop (Kvitek and others, 2006), attended by coastal and marine managers and scientists from around the state. That workshop established geographic priorities for a coastal mapping project and identified the need for coverage of “lands” from the shore strand line (defined as Mean Higher High Water; MHHW) out to the 3-nautical-mile (5.6-km) limit of California’s State Waters. Unfortunately, surveying the zone from MHHW out to 10-m water depth is not consistently possible using ship-based surveying methods, owing to sea state (for example, waves, wind, or currents), kelp coverage, and shallow rock outcrops. Accordingly, some of the data presented in this series commonly do not cover the zone from the shore out to 10-m depth. This data is part of a series of online U.S. Geological Survey (USGS) publications, each of which includes several map sheets, some explanatory text, and a descriptive pamphlet. Each map sheet is published as a PDF file. Geographic information system (GIS) files that contain both ESRI ArcGIS raster grids (for example, bathymetry, seafloor character) and geotiffs (for example, shaded relief) are also included for each publication. For those who do not own the full suite of ESRI GIS and mapping software, the data can be read using ESRI ArcReader, a free viewer that is available at http://www.esri.com/software/arcgis/arcreader/index.html (last accessed September 20, 2013). The California Seafloor Mapping Program is a collaborative venture between numerous different federal and state agencies, academia, and the private sector. CSMP partners include the California Coastal Conservancy, the California Ocean Protection Council, the California Department of Fish and Wildlife, the California Geological Survey, California State University at Monterey Bay’s Seafloor Mapping Lab, Moss Landing Marine Laboratories Center for Habitat Studies, Fugro Pelagos, Pacific Gas and Electric Company, National Oceanic and Atmospheric Administration (NOAA, including National Ocean Service–Office of Coast Surveys, National Marine Sanctuaries, and National Marine Fisheries Service), U.S. Army Corps of Engineers, the Bureau of Ocean Energy Management, the National Park Service, and the U.S. Geological Survey. These web services for the Offshore of Tomales Point map area includes data layers that are associated to GIS and map sheets available from the USGS CSMP web page at https://walrus.wr.usgs.gov/mapping/csmp/index.html. Each published CSMP map area includes a data catalog of geographic information system (GIS) files; map sheets that contain explanatory text; and an associated descriptive pamphlet. This web service represents the available data layers for this map area. Data was combined from different sonar surveys to generate a comprehensive high-resolution bathymetry and acoustic-backscatter coverage of the map area. These data reveal a range of physiographic including exposed bedrock outcrops, large fields of sand waves, as well as many human impacts on the seafloor. To validate geological and biological interpretations of the sonar data, the U.S. Geological Survey towed a camera sled over specific offshore locations, collecting both video and photographic imagery; these “ground-truth” surveying data are available from the CSMP Video and Photograph Portal at https://doi.org/10.5066/F7J1015K. The “seafloor character” data layer shows classifications of the seafloor on the basis of depth, slope, rugosity (ruggedness), and backscatter intensity and which is further informed by the ground-truth-survey imagery. The “potential habitats” polygons are delineated on the basis of substrate type, geomorphology, seafloor process, or other attributes that may provide a habitat for a specific species or assemblage of organisms. Representative seismic-reflection profile data from the map area is also include and provides information on the subsurface stratigraphy and structure of the map area. The distribution and thickness of young sediment (deposited over the past about 21,000 years, during the most recent sea-level rise) is interpreted on the basis of the seismic-reflection data. The geologic polygons merge onshore geologic mapping (compiled from existing maps by the California Geological Survey) and new offshore geologic mapping that is based on integration of high-resolution bathymetry and backscatter imagery seafloor-sediment and rock samplesdigital camera and video imagery, and high-resolution seismic-reflection profiles. The information provided by the map sheets, pamphlet, and data catalog has a broad range of applications. High-resolution bathymetry, acoustic backscatter, ground-truth-surveying imagery, and habitat mapping all contribute to habitat characterization and ecosystem-based management by providing essential data for delineation of marine protected areas and ecosystem restoration. Many of the maps provide high-resolution baselines that will be critical for monitoring environmental change associated with climate change, coastal development, or other forcings. High-resolution bathymetry is a critical component for modeling coastal flooding caused by storms and tsunamis, as well as inundation associated with longer term sea-level rise. Seismic-reflection and bathymetric data help characterize earthquake and tsunami sources, critical for natural-hazard assessments of coastal zones. Information on sediment distribution and thickness is essential to the understanding of local and regional sediment transport, as well as the development of regional sediment-management plans. In addition, siting of any new offshore infrastructure (for example, pipelines, cables, or renewable-energy facilities) will depend on high-resolution mapping. Finally, this mapping will both stimulate and enable new scientific research and also raise public awareness of, and education about, coastal environments and issues. Web services were created using an ArcGIS service definition file. The ArcGIS REST service and OGC WMS service include all Offshore of Tomales Point map area data layers. Data layers are symbolized as shown on the associated map sheets.

In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ecosystems as part of the design and proposal process for the establishment of Marine Protected Areas. A focus of CSMP is to map California’s State Waters with consistent methods at a consistent scale. The CSMP approach is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar data (the undersea equivalent of satellite remote-sensing data in terrestrial mapping), acoustic backscatter, seafloor video, seafloor photography, high-resolution seismic-reflection profiles, and bottom-sediment sampling data. The map products display seafloor morphology and character, identify potential marine benthic habitats, and illustrate both the surficial seafloor geology and shallow (to about 100 m) subsurface geology. It is emphasized that the more interpretive habitat and geology data rely on the integration of multiple, new high-resolution datasets and that mapping at small scales would not be possible without such data. This approach and CSMP planning is based in part on recommendations of the Marine Mapping Planning Workshop (Kvitek and others, 2006), attended by coastal and marine managers and scientists from around the state. That workshop established geographic priorities for a coastal mapping project and identified the need for coverage of “lands” from the shore strand line (defined as Mean Higher High Water; MHHW) out to the 3-nautical-mile (5.6-km) limit of California’s State Waters. Unfortunately, surveying the zone from MHHW out to 10-m water depth is not consistently possible using ship-based surveying methods, owing to sea state (for example, waves, wind, or currents), kelp coverage, and shallow rock outcrops. Accordingly, some of the data presented in this series commonly do not cover the zone from the shore out to 10-m depth. This data is part of a series of online U.S. Geological Survey (USGS) publications, each of which includes several map sheets, some explanatory text, and a descriptive pamphlet. Each map sheet is published as a PDF file. Geographic information system (GIS) files that contain both ESRI ArcGIS raster grids (for example, bathymetry, seafloor character) and geotiffs (for example, shaded relief) are also included for each publication. For those who do not own the full suite of ESRI GIS and mapping software, the data can be read using ESRI ArcReader, a free viewer that is available at http://www.esri.com/software/arcgis/arcreader/index.html (last accessed September 20, 2013). The California Seafloor Mapping Program is a collaborative venture between numerous different federal and state agencies, academia, and the private sector. CSMP partners include the California Coastal Conservancy, the California Ocean Protection Council, the California Department of Fish and Wildlife, the California Geological Survey, California State University at Monterey Bay’s Seafloor Mapping Lab, Moss Landing Marine Laboratories Center for Habitat Studies, Fugro Pelagos, Pacific Gas and Electric Company, National Oceanic and Atmospheric Administration (NOAA, including National Ocean Service–Office of Coast Surveys, National Marine Sanctuaries, and National Marine Fisheries Service), U.S. Army Corps of Engineers, the Bureau of Ocean Energy Management, the National Park Service, and the U.S. Geological Survey. These web services for the Offshore of Ventura map area includes data layers that are associated to GIS and map sheets available from the USGS CSMP web page at https://walrus.wr.usgs.gov/mapping/csmp/index.html. Each published CSMP map area includes a data catalog of geographic information system (GIS) files; map sheets that contain explanatory text; and an associated descriptive pamphlet. This web service represents the available data layers for this map area. Data was combined from different sonar surveys to generate a comprehensive high-resolution bathymetry and acoustic-backscatter coverage of the map area. These data reveal a range of physiographic including exposed bedrock outcrops, large fields of sand waves, as well as many human impacts on the seafloor. To validate geological and biological interpretations of the sonar data, the U.S. Geological Survey towed a camera sled over specific offshore locations, collecting both video and photographic imagery; these “ground-truth” surveying data are available from the CSMP Video and Photograph Portal at https://doi.org/10.5066/F7J1015K. The “seafloor character” data layer shows classifications of the seafloor on the basis of depth, slope, rugosity (ruggedness), and backscatter intensity and which is further informed by the ground-truth-survey imagery. The “potential habitats” polygons are delineated on the basis of substrate type, geomorphology, seafloor process, or other attributes that may provide a habitat for a specific species or assemblage of organisms. Representative seismic-reflection profile data from the map area is also include and provides information on the subsurface stratigraphy and structure of the map area. The distribution and thickness of young sediment (deposited over the past about 21,000 years, during the most recent sea-level rise) is interpreted on the basis of the seismic-reflection data. The geologic polygons merge onshore geologic mapping (compiled from existing maps by the California Geological Survey) and new offshore geologic mapping that is based on integration of high-resolution bathymetry and backscatter imagery seafloor-sediment and rock samplesdigital camera and video imagery, and high-resolution seismic-reflection profiles. The information provided by the map sheets, pamphlet, and data catalog has a broad range of applications. High-resolution bathymetry, acoustic backscatter, ground-truth-surveying imagery, and habitat mapping all contribute to habitat characterization and ecosystem-based management by providing essential data for delineation of marine protected areas and ecosystem restoration. Many of the maps provide high-resolution baselines that will be critical for monitoring environmental change associated with climate change, coastal development, or other forcings. High-resolution bathymetry is a critical component for modeling coastal flooding caused by storms and tsunamis, as well as inundation associated with longer term sea-level rise. Seismic-reflection and bathymetric data help characterize earthquake and tsunami sources, critical for natural-hazard assessments of coastal zones. Information on sediment distribution and thickness is essential to the understanding of local and regional sediment transport, as well as the development of regional sediment-management plans. In addition, siting of any new offshore infrastructure (for example, pipelines, cables, or renewable-energy facilities) will depend on high-resolution mapping. Finally, this mapping will both stimulate and enable new scientific research and also raise public awareness of, and education about, coastal environments and issues. Web services were created using an ArcGIS service definition file. The ArcGIS REST service and OGC WMS service include all Offshore of Ventura map area data layers. Data layers are symbolized as shown on the associated map sheets.

Profiles of salinity, temperature, turbidity, and particle size distribution were collected by the U.S. Geological Survey (USGS) Pacific Coastal and Marine Science Center in South San Francisco Bay. Data were collected at depth intervals ranging between 0.5 and 2 m (depending on total water depth); sensors remained at each depth for 1-2 minutes. Each profile was collected from surface to bed, and the near-surface region was sampled again at the end of the profile to check steady-state conditions. Profiles were collected on 4 days: June 22, July 21, and December 3 of 2021, and on January 4, 2022 (UTC). Data files are grouped by season (summer or winter) and by instrument (CTD or LISST). No LISST data were collected in the winter. Users are advised to assess data quality carefully.

This part of DS 781 presents data for the map showing the predicted distribution of brittle stars in the Santa Barbara Channel, California, region. The raster data file is included in "BrittleStars_SantaBarbaraChannel.zip," which is accessible from https://pubs.usgs.gov/ds/781/SantaBarbaraChannel/data_catalog_SantaBarbaraChannel.html. Presence-absence data of benthic macro-invertebrates and associated habitat (that is, sediment type and depth) were collected using a towed camera sled in selected areas along the coast off southern California during a ground-truth observation cruise conducted by the U.S. Geological Survey and NOAA National Marine Fisheries Service for the California Seafloor Mapping Program. Benthic community structure was determined from 35 video towed-camera transects within California's State Waters 3-nautical-mile limit in the Santa Barbara Channel. These transects produced a total of 923 10-second observations from the Offshore of Refugio Beach map area (34.5 degrees N., 120.1 degrees W.) to the Hueneme Canyon and vicinity map area (34.1 degrees N., 119.2 degrees W.). Presence-absence data were collected for 29 benthic, structure-forming nonmobile taxa. Using this information, generalized linear models (GLMs) were developed to predict the probability of occurrence of five commonly observed taxa (cup corals, hydroids, short and tall sea pens, and brittle stars in the sediment) in five map areas within the Santa Barbara Channel (SBC). A sixth map area (Offshore of Carpinteria) was not modeled owing to insufficient data. The analysis demonstrates that the community structure for the five map areas can be divided into three statistically distinct groups: (1) the Hueneme Canyon and vicinity and the Offshore of Ventura map areas; (2) the Offshore of Santa Barbara and the Offshore of Coal Oil Point map areas; and (3) the Offshore of Refugio Beach map area. These three distinct groups are the main reason that the probability for each taxa can be so dramatically different within one predictive-distribution map area. The five most frequently observed benthic macro-invertebrate taxa were selected for these predictive-distribution grids. Presence-absence data for each selected invertebrate were fit to specific generalized linear models using geographic location, depth, and seafloor character as covariates. Data for the covariates were informed by the bathymetry, seafloor character, and other ground-truth data from the different map areas of the Santa Barbara Channel region that are part of the California State Waters Map Series DS 781. Observations based on depth were limited by the capability of the towed camera sled; as a result, no predictions were made below depths of 150 m (in other words, on the continental slope or in Hueneme Canyon). Cup corals and hydroids had high predicted probabilities of occurrence in areas of hard substrata, whereas short and tall sea pens were predicted to occur in parts of the SBC that had unconsolidated and mixed sediment. Our model predicted that brittle stars would occur throughout the entire SBC on various bottom types.

This part of DS 781 presents data for the map showing the predicted distribution of cup corals in the Santa Barbara Channel, California, region. The raster data file is included in "CupCorals_SantaBarbaraChannel.zip," which is accessible from https://pubs.usgs.gov/ds/781/SantaBarbaraChannel/data_catalog_SantaBarbaraChannel.html. Presence-absence data of benthic macro-invertebrates and associated habitat (that is, sediment type and depth) were collected using a towed camera sled in selected areas along the coast off southern California during a ground-truth observation cruise conducted by the U.S. Geological Survey and NOAA National Marine Fisheries Service for the California Seafloor Mapping Program. Benthic community structure was determined from 35 video towed-camera transects within California's State Waters 3-nautical-mile limit in the Santa Barbara Channel. These transects produced a total of 923 10-second observations from the Offshore of Refugio Beach map area (34.5 degrees N., 120.1 degrees W.) to the Hueneme Canyon and vicinity map area (34.1 degrees N., 119.2 degrees W.). Presence-absence data were collected for 29 benthic, structure-forming nonmobile taxa. Using this information, generalized linear models (GLMs) were developed to predict the probability of occurrence of five commonly observed taxa (cup corals, hydroids, short and tall sea pens, and brittle stars in the sediment) in five map areas within the Santa Barbara Channel (SBC). A sixth map area (Offshore of Carpinteria) was not modeled owing to insufficient data. The analysis demonstrates that the community structure for the five map areas can be divided into three statistically distinct groups: (1) the Hueneme Canyon and vicinity and the Offshore of Ventura map areas; (2) the Offshore of Santa Barbara and the Offshore of Coal Oil Point map areas; and (3) the Offshore of Refugio Beach map area. These three distinct groups are the main reason that the probability for each taxa can be so dramatically different within one predictive-distribution map area. The five most frequently observed benthic macro-invertebrate taxa were selected for these predictive-distribution grids. Presence-absence data for each selected invertebrate were fit to specific generalized linear models using geographic location, depth, and seafloor character as covariates. Data for the covariates were informed by the bathymetry, seafloor character, and other ground-truth data from the different map areas of the Santa Barbara Channel region that are part of the California State Waters Map Series DS 781. Observations based on depth were limited by the capability of the towed camera sled; as a result, no predictions were made below depths of 150 m (in other words, on the continental slope or in Hueneme Canyon). Cup corals and hydroids had high predicted probabilities of occurrence in areas of hard substrata, whereas short and tall sea pens were predicted to occur in parts of the SBC that had unconsolidated and mixed sediment. Our model predicted that brittle stars would occur throughout the entire SBC on various bottom types.

This part of DS 781 presents data for the map showing the predicted distribution of hydroids in the Santa Barbara Channel, California, region. The raster data file is included in "Hydroids_SantaBarbaraChannel.zip," which is accessible from https://pubs.usgs.gov/ds/781/SantaBarbaraChannel/data_catalog_SantaBarbaraChannel.html. Presence-absence data of benthic macro-invertebrates and associated habitat (that is, sediment type and depth) were collected using a towed camera sled in selected areas along the coast off southern California during a ground-truth observation cruise conducted by the U.S. Geological Survey and NOAA National Marine Fisheries Service for the California Seafloor Mapping Program. Benthic community structure was determined from 35 video towed-camera transects within California's State Waters 3-nautical-mile limit in the Santa Barbara Channel. These transects produced a total of 923 10-second observations from the Offshore of Refugio Beach map area (34.5 degrees N., 120.1 degrees W.) to the Hueneme Canyon and vicinity map area (34.1 degrees N., 119.2 degrees W.). Presence-absence data were collected for 29 benthic, structure-forming nonmobile taxa. Using this information, generalized linear models (GLMs) were developed to predict the probability of occurrence of five commonly observed taxa (cup corals, hydroids, short and tall sea pens, and brittle stars in the sediment) in five map areas within the Santa Barbara Channel (SBC). A sixth map area (Offshore of Carpinteria) was not modeled owing to insufficient data. The analysis demonstrates that the community structure for the five map areas can be divided into three statistically distinct groups: (1) the Hueneme Canyon and vicinity and the Offshore of Ventura map areas; (2) the Offshore of Santa Barbara and the Offshore of Coal Oil Point map areas; and (3) the Offshore of Refugio Beach map area. These three distinct groups are the main reason that the probability for each taxa can be so dramatically different within one predictive-distribution map area. The five most frequently observed benthic macro-invertebrate taxa were selected for these predictive-distribution grids. Presence-absence data for each selected invertebrate were fit to specific generalized linear models using geographic location, depth, and seafloor character as covariates. Data for the covariates were informed by the bathymetry, seafloor character, and other ground-truth data from the different map areas of the Santa Barbara Channel region that are part of the California State Waters Map Series DS 781. Observations based on depth were limited by the capability of the towed camera sled; as a result, no predictions were made below depths of 150 m (in other words, on the continental slope or in Hueneme Canyon). Cup corals and hydroids had high predicted probabilities of occurrence in areas of hard substrata, whereas short and tall sea pens were predicted to occur in parts of the SBC that had unconsolidated and mixed sediment. Our model predicted that brittle stars would occur throughout the entire SBC on various bottom types.

This part of DS 781 presents data for the map showing the predicted distribution of short sea pens in the Santa Barbara Channel, California, region. The raster data file is included in "ShortSeaPens_SantaBarbaraChannel.zip," which is accessible from https://pubs.usgs.gov/ds/781/SantaBarbaraChannel/data_catalog_SantaBarbaraChannel.html. Presence-absence data of benthic macro-invertebrates and associated habitat (that is, sediment type and depth) were collected using a towed camera sled in selected areas along the coast off southern California during a ground-truth observation cruise conducted by the U.S. Geological Survey and NOAA National Marine Fisheries Service for the California Seafloor Mapping Program. Benthic community structure was determined from 35 video towed-camera transects within California's State Waters 3-nautical-mile limit in the Santa Barbara Channel. These transects produced a total of 923 10-second observations from the Offshore of Refugio Beach map area (34.5 degrees N., 120.1 degrees W.) to the Hueneme Canyon and vicinity map area (34.1 degrees N., 119.2 degrees W.). Presence-absence data were collected for 29 benthic, structure-forming nonmobile taxa. Using this information, generalized linear models (GLMs) were developed to predict the probability of occurrence of five commonly observed taxa (cup corals, hydroids, short and tall sea pens, and brittle stars in the sediment) in five map areas within the Santa Barbara Channel (SBC). A sixth map area (Offshore of Carpinteria) was not modeled owing to insufficient data. The analysis demonstrates that the community structure for the five map areas can be divided into three statistically distinct groups: (1) the Hueneme Canyon and vicinity and the Offshore of Ventura map areas; (2) the Offshore of Santa Barbara and the Offshore of Coal Oil Point map areas; and (3) the Offshore of Refugio Beach map area. These three distinct groups are the main reason that the probability for each taxa can be so dramatically different within one predictive-distribution map area. The five most frequently observed benthic macro-invertebrate taxa were selected for these predictive-distribution grids. Presence-absence data for each selected invertebrate were fit to specific generalized linear models using geographic location, depth, and seafloor character as covariates. Data for the covariates were informed by the bathymetry, seafloor character, and other ground-truth data from the different map areas of the Santa Barbara Channel region that are part of the California State Waters Map Series DS 781. Observations based on depth were limited by the capability of the towed camera sled; as a result, no predictions were made below depths of 150 m (in other words, on the continental slope or in Hueneme Canyon). Cup corals and hydroids had high predicted probabilities of occurrence in areas of hard substrata, whereas short and tall sea pens were predicted to occur in parts of the SBC that had unconsolidated and mixed sediment. Our model predicted that brittle stars would occur throughout the entire SBC on various bottom types.

This part of DS 781 presents data for the map showing the predicted distribution of tall sea pens in the Santa Barbara Channel, California, region. The raster data file is included in "TallSeaPens_SantaBarbaraChannel.zip," which is accessible from https://pubs.usgs.gov/ds/781/SantaBarbaraChannel/data_catalog_SantaBarbaraChannel.html. Presence-absence data of benthic macro-invertebrates and associated habitat (that is, sediment type and depth) were collected using a towed camera sled in selected areas along the coast off southern California during a ground-truth observation cruise conducted by the U.S. Geological Survey and NOAA National Marine Fisheries Service for the California Seafloor Mapping Program. Benthic community structure was determined from 35 video towed-camera transects within California's State Waters 3-nautical-mile limit in the Santa Barbara Channel. These transects produced a total of 923 10-second observations from the Offshore of Refugio Beach map area (34.5 degrees N., 120.1 degrees W.) to the Hueneme Canyon and vicinity map area (34.1 degrees N., 119.2 degrees W.). Presence-absence data were collected for 29 benthic, structure-forming nonmobile taxa. Using this information, generalized linear models (GLMs) were developed to predict the probability of occurrence of five commonly observed taxa (cup corals, hydroids, short and tall sea pens, and brittle stars in the sediment) in five map areas within the Santa Barbara Channel (SBC). A sixth map area (Offshore of Carpinteria) was not modeled owing to insufficient data. The analysis demonstrates that the community structure for the five map areas can be divided into three statistically distinct groups: (1) the Hueneme Canyon and vicinity and the Offshore of Ventura map areas; (2) the Offshore of Santa Barbara and the Offshore of Coal Oil Point map areas; and (3) the Offshore of Refugio Beach map area. These three distinct groups are the main reason that the probability for each taxa can be so dramatically different within one predictive-distribution map area. The five most frequently observed benthic macro-invertebrate taxa were selected for these predictive-distribution grids. Presence-absence data for each selected invertebrate were fit to specific generalized linear models using geographic location, depth, and seafloor character as covariates. Data for the covariates were informed by the bathymetry, seafloor character, and other ground-truth data from the different map areas of the Santa Barbara Channel region that are part of the California State Waters Map Series DS 781. Observations based on depth were limited by the capability of the towed camera sled; as a result, no predictions were made below depths of 150 m (in other words, on the continental slope or in Hueneme Canyon). Cup corals and hydroids had high predicted probabilities of occurrence in areas of hard substrata, whereas short and tall sea pens were predicted to occur in parts of the SBC that had unconsolidated and mixed sediment. Our model predicted that brittle stars would occur throughout the entire SBC on various bottom types.

This part of USGS Data Series 935 (Cochrane, 2014) presents observations from underwater video collected in the Offshore of Burien, California, map area, a part of the Southern Salish Sea Habitat Map Series. To validate the interpretations of multibeam sonar data and turn it into geologically and biologically useful information, the U.S. Geological Survey (USGS) towed a camera sled over specific locations throughout the Seattle map area to collect video and photographic data that would “ground truth” the seafloor. The ground-truth survey conducted in the Offshore of Burien map area occurred in 2011 on the R/V Karluk (USGS field activities K0109WO, K0111PS) and on the Washington State Department of Fish and Game R/V Molluscan (USGS field activity M0112PS, M0111PS, M0212PS). The underwater camera sled was towed 1 to 2 m above the seafloor at speeds of between 1 and 2 nautical miles/hour. The surveys for this map area include approximately 6 hours (9.1 trackline km) of video.

Hydrodynamic and sediment transport time-series data, including water depth, velocity, turbidity, conductivity, and temperature, were collected by the U.S. Geological Survey (USGS) Pacific Coastal and Marine Science Center in South San Francisco Bay and in the Whale's Tail South marsh in Eden Landing Ecological Reserve in Alameda County, CA in 2021 and 2022. Data files are grouped by data type and season (summer and winter). At Bay sites, instruments were deployed on small quadpods. In the tidal creek, instruments were attached to grates mounted directly on the sediment bed. Marsh sites consisted of one transect of six stations perpendicular to the bay-marsh interface, and a second transect perpendicular to a tidal creek. Note that marsh stations were positioned fairly high in the tidal frame (close to the mean higher-high water elevation), so they were inundated less than 10 percent of the time. Instruments at the Bay stations were inundated most of the time but were subaerial at low tide. Data are only valid when the instruments were submerged. Users are advised to assess data quality carefully, and to check metadata for instrument information, as platform deployment times and data-processing methods varied.

Groundwater emergence and shoaling extents are derived from water table depth GeoTIFFs, which are calculated as steady-state groundwater model heads subtracted from high-resolution topographic digital elevation model (DEM) land surface elevations. Results are provided as shapefiles of water table depth in specific depth ranges. Similar modeled data for North Carolina and South Carolina are available from Barnard and others, 2023 at https://doi.org/10.5066/P9W91314.

Seamless unconfined groundwater heads for U.S. coastal Virginia, Georgia, and Florida (Atlantic and Gulf coast south of Sarasota) groundwater systems were modeled with homogeneous, steady-state MODFLOW simulations. The geographic extent examined was limited primarily to low-elevation (land surface less than approximately 10 m above mean sea level) areas. Steady-state MODFLOW groundwater flow models were used to obtain detailed (50-meter-scale) predictions over large geographic scales (100s of kilometers) of groundwater heads for both current and future sea-level rise (SLR) scenarios (0, 0.25, 0.5, 1, 1.5, 2, 2.5, and 3 m) using 3 spatially varying hydraulic conductivities (K); one based on published K's, one with published K's reduced by a factor of 10 (K*0.1), and one with published K's increased by a factor of 10 (K*10) to assess the sensitivity of model results to K. All models had variable thicknesses corresponding to published transmissivities. The models were run with a local mean higher-high water (MHHW) marine boundary condition and with groundwater reaching the land surface removed from the model, simulating loss via natural drainage. Similar modeled data for North Carolina and South Carolina are available from Barnard and others, 2023 at https://doi.org/10.5066/P9W91314.

To predict water table depths, seamless groundwater heads for unconfined coastal Virginia, Georgia, and Florida (Atlantic and Gulf coast south of Sarasota) groundwater systems were modeled with homogeneous, steady-state MODFLOW simulations. The geographic extent examined was limited primarily to low-elevation (land surface less than approximately 10 m above mean sea level) areas. Steady-state MODFLOW groundwater flow models were used to obtain detailed (50-meter-scale) predictions over large geographic scales (100s of kilometers) of groundwater heads for both current and future sea-level rise (SLR) scenarios (0, 0.25, 0.5, 1, 1.5, 2, 2.5, and 3 m) using 3 spatially varying hydraulic conductivities (K); one based on published K's, one with published K's reduced by a factor of 10 (K*0.1), and one with published K's increased by a factor of 10 (K*10) to assess the sensitivity of model results to K. All models had variable thicknesses corresponding to published transmissivities. The models were run with a local mean higher-high water (MHHW) marine boundary condition, and with groundwater reaching the land surface removed from the model, simulating loss via natural drainage. Modeled groundwater heads were then subtracted from high-resolution topographic digital elevation model (DEM) data to obtain the water table depths. Similar modeled data for North Carolina and South Carolina are available from Barnard and others, 2023, at https://doi.org/10.5066/P9W91314.

A dataset of modeled nearshore water levels (WLs) was developed for three states (Virginia, Georgia, and Florida) along the U.S. Atlantic coast. Water levels, defined for this dataset as the linear sum of tides and non-tidal residuals (NTR), were produced by Muis and others (2016) using a global tide and surge model (GTSM) forced by global atmospheric fields. Water level outputs were extracted from the global grid at approximately 20 km resolution along the Atlantic coastline. These data were then statistically downscaled using a signal-specific set of corrections to improve skill in comparison to tide gauge observations (Parker and others, 2023). Projected water levels were forced by CMIP6 future period data. Four CMIP6 climate models were selected from the High-Resolution Model Intercomparison project (highresMIP; Haarsma and others, 2016) to sample variability in climate predictions. Similar modeled data for North Carolina and South Carolina are available from Barnard and others, 2023, at https://doi.org/10.5066/P9W91314)

A dataset of modeled nearshore water levels (WLs) was developed for three states (Virginia, Georgia, and Florida) along the U.S. Atlantic coast. Water levels, defined for this dataset as the linear sum of tides and non-tidal residuals (NTR), were produced by Muis and others (2016) using a global tide and surge model (GTSM) forced by global atmospheric fields -. Water level outputs were extracted from the global grid at approximately 20 km resolution along the coastlines. These data were then statistically downscaled using a signal-specific set of corrections to improve skill in comparison to tide gauge observations (Parker and others, 2023). Hindcast water levels were forced by ERA5 atmospheric forcing provided by the dataset of Hersbach and others (2020). ERA5 is a reanalysis product, incorporating observations and data assimilation to best represent the experienced climate. Therefore, data from this version of the dataset are comparable to observed WLs along the study region. Similar modeled data for North Carolina and South Carolina are available from Barnard and others, 2023, at https://doi.org/10.5066/P9W91314)

This dataset presents alongshore wave setup timeseries for three states (Virginia, Georgia, and Florida) along the U.S. Atlantic coast. Wave setup was modelled using parameterization for open coast sandy beaches as presented in Stockdon and others (2006). The parameterization relates onshore wave setup to offshore wave conditions and beach characteristics. Wave conditions were extracted at approximately the 10 m depth contour and reverse shoaled to the deep-water condition. These data were then matched to cross-shore transects spaced at approximately 1 km along the coastline. Beach slope at these transects were extracted from lidar (Doran and others, 2017) and temporally averaged across all available datasets. Waves were modelled using a global WAVEWATCHIII model forced by atmospheric forcing from the Coupled Model Intercomparison Project (CMIP6) future period data. Data are provided for 6 CMIP6 models from the HighResMIP project (Haarsma and others, 2016). Output includes 1-hour wave setup provided at approximately 1,600 alongshore transects at approximately 1-5 km resolution. Data are available as csv files for each transect location and are bundled by state. The methodology used to produce this dataset is further detailed in Parker and others (2023) and similar modelled data for North Carolina and South Carolina are available from Barnard and others, 2023, at https://doi.org/10.5066/P9W91314.

This dataset presents alongshore wave setup timeseries for three states (Virginia, Georgia, and Florida) along the U.S. Atlantic coast. Wave setup was modelled using parameterization for open coast sandy beaches as presented in Stockdon and others (2006). The parameterization relates onshore wave setup to offshore wave conditions and beach characteristics. Wave conditions were extracted at approximately the 10 m depth contour and reverse shoaled to the deep-water condition. These data were then matched to cross-shore transects spaced at approximately 1 km along the coastline. Beach slope at these transects were extracted from lidar (Doran and others, 2017) and temporally averaged across all available datasets. The hindcast model is forced by waves taken directly from the ERA5 reanalysis, which incorporates observations and data assimilation (Hersbach and others, 2020). Modeled wave setup time series are presented for the hindcast period 1979 to 2019. Output includes 1-hour wave setup provided at approximately 1,600 alongshore transects at approximately 1-5 km resolution. Data are available as csv files for each transect location and are bundled by state. This dataset and the methodology used for its production is further detailed in Parker and others (2023) and similar modelled data for North Carolina and South Carolina are available from Barnard and others, 2023, at https://doi.org/10.5066/P9W91314).

Groundwater emergence and shoaling extents are derived from water table depth GeoTIFFs, which are calculated as steady-state groundwater model heads subtracted from high-resolution topographic digital elevation model (DEM) land surface elevations. Results are provided as shapefiles of water table depth in specific depth ranges.

Seamless unconfined groundwater heads for U.S. coastal North and South Carolina groundwater systems were modeled with homogeneous, steady-state MODFLOW simulations. The geographic extent examined was limited primarily to low-elevation (land surface less than approximately 10 m above mean sea level) areas. Steady-state MODFLOW groundwater flow models were used to obtain detailed (50-meter-scale) predictions over large geographic scales (100s of kilometers) of groundwater heads for both current and future sea-level rise (SLR) scenarios (0, 0.25, 0.5, 1, 1.5, 2, 2.5, and 3 m) using 3 spatially varying hydraulic conductivities (K); one based on published K’s, one with published K’s reduced by a factor of 10 (K*0.1), and one with published K’s increased by a factor of 10 (K*10) to assess the sensitivity of model results to K. All models had variable thicknesses corresponding to published transmissivities. The models were run with a local mean higher-high water (MHHW) marine boundary condition and with groundwater reaching the land surface removed from the model, simulating loss via natural drainage.

To predict water table depths, seamless groundwater heads for unconfined coastal North and South Carolina groundwater systems were modeled with homogeneous, steady-state MODFLOW simulations. The geographic extent examined was limited primarily to low-elevation (land surface less than approximately 10 m above mean sea level) areas. Steady-state MODFLOW groundwater flow models were used to obtain detailed (50-meter-scale) predictions over large geographic scales (100s of kilometers) of groundwater heads for both current and future sea-level rise (SLR) scenarios (0, 0.25, 0.5, 1, 1.5, 2, 2.5, and 3 m) using 3 spatially varying hydraulic conductivities (K); one based on published K’s, one with published K’s reduced by a factor of 10 (K*0.1), and one with published K’s increased by a factor of 10 (K*10) to assess the sensitivity of model results to K. All models had variable thicknesses corresponding to published transmissivities. The models were run with a local mean higher-high water (MHHW) marine boundary condition, and with groundwater reaching the land surface removed from the model, simulating loss via natural drainage. Modeled groundwater heads were then subtracted from high-resolution topographic digital elevation model (DEM) data to obtain the water table depths.

A dataset of modeled nearshore water levels (WLs) was developed for the North and South Carolina coastlines. Water levels, defined for this dataset as the linear sum of tides and non-tidal residuals (NTR), were produced by Muis and others (2016) using a global tide and surge model (GTSM) forced by global atmospheric fields. Water level outputs were extracted from the global grid at approximately 20 km resolution along the southeast Atlantic coastline. These data were then statistically downscaled using a signal-specific set of corrections to improve skill in comparison to tide gauge observations (Parker and others, 2023). Projected water levels were forced by CMIP6 future period data. This dataset provides information on how water levels are expected to change moving towards the future. Four CMIP6 climate models were selected from the High-Resolution Model Intercomparison project (highresMIP; Haarsma and others, 2016) to sample variability in climate predictions.

A dataset of modeled nearshore water levels (WLs) was developed for the North and South Carolina coastlines. Water levels, defined for this dataset as the linear sum of tides and non-tidal residuals (NTR), were produced by Muis and others (2016) using a global tide and surge model (GTSM) forced by global atmospheric fields -. Water level outputs were extracted from the global grid at approximately 20 km resolution along the coastlines. These data were then statistically downscaled using a signal-specific set of corrections to improve skill in comparison to tide gauge observations (Parker and others, 2023). Hindcast water levels were forced by ERA5 atmospheric forcing provided by the dataset of Hersbach and others (2020). ERA5 is a reanalysis product, incorporating observations and data assimilation to best represent the experienced climate. Therefore, data from this version of the dataset are comparable to observed WLs along the study region.

This dataset presents alongshore wave setup timeseries for the North and South Carolina coastlines. Wave setup was modelled using parameterization for open coast sandy beaches as presented in Stockdon and others (2006). The parameterization relates onshore wave setup to offshore wave conditions and beach characteristics. Wave conditions were extracted at approximately the 10 m depth contour and reverse shoaled to the deep-water condition. These data were then matched to cross-shore transects spaced at approximately 1 km along the coastline. Beach slope at these transects were extracted from lidar (Doran and others, 2017) and temporally averaged across all available datasets. Waves were modelled using a global WAVEWATCHIII model forced by atmospheric forcing from the Coupled Model Intercomparison Project (CMIP6) future period data. This dataset provides information on how water setup is expected to change moving towards the future. The methodology used to produce this dataset is further detailed in Parker and others (2023). Data are provided for 6 CMIP6 models from the HighResMIP project (Haarsma and others, 2016). Output includes 1-hour wave setup provided at approximately 1,600 alongshore transects at approximately 1-5 km resolution. Data are available as csv files for each transect location and are bundled by state.

This dataset presents alongshore wave setup timeseries for the North and South Carolina coastlines. Wave setup was modelled using parameterization for open coast sandy beaches as presented in Stockdon and others (2006). The parameterization relates onshore wave setup to offshore wave conditions and beach characteristics. Wave conditions were extracted at approximately the 10 m depth contour and reverse shoaled to the deep-water condition. These data were then matched to cross-shore transects spaced at approximately 1 km along the coastline. Beach slope at these transects were extracted from lidar (Doran and others, 2017) and temporally averaged across all available datasets. This dataset is forced by waves taken directly from the ERA5 reanalysis, which incorporates observations and data assimilation (Hersbach and others, 2020). Therefore, data presented in this data release represent a best prediction of the observed historical wave setup along the study region. This dataset and the methodology used for its production is further detailed in Parker and others (2023). Modeled wave setup time series are presented for the hindcast period 1979 to 2019. Output includes 1-hour wave setup provided at approximately 1,600 alongshore transects at approximately 1-5 km resolution. Data are available as csv files for each transect location and are bundled by state.

This data layer (PAC_EXT.txt) is one of five point coverages of known sediment samples, inspections, and probes from the usSEABED data collection for the U.S. Pacific continental margin integrated using the software system dbSEABED. This data layer represents the extracted (EXT) output of the dbSEABED mining software and contains data items which were extracted from the data resources files and generally represent lab-based analytical data. The EXT data are usually considered the most rigorous data available, although some data may represent a subsample of the sediment (that is, large shells or stones may have been excluded from the analysis). This file contains the same data fields as the parsed (PAC_PRS) and calculated (PAC_CLC) data files, and the three files may be combined.

In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ecosystems as part of the design and proposal process for the establishment of Marine Protected Areas. A focus of CSMP is to map California’s State Waters with consistent methods at a consistent scale. The CSMP approach is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar data (the undersea equivalent of satellite remote-sensing data in terrestrial mapping), acoustic backscatter, seafloor video, seafloor photography, high-resolution seismic-reflection profiles, and bottom-sediment sampling data. The map products display seafloor morphology and character, identify potential marine benthic habitats, and illustrate both the surficial seafloor geology and shallow (to about 100 m) subsurface geology. It is emphasized that the more interpretive habitat and geology data rely on the integration of multiple, new high-resolution datasets and that mapping at small scales would not be possible without such data. This approach and CSMP planning is based in part on recommendations of the Marine Mapping Planning Workshop (Kvitek and others, 2006), attended by coastal and marine managers and scientists from around the state. That workshop established geographic priorities for a coastal mapping project and identified the need for coverage of “lands” from the shore strand line (defined as Mean Higher High Water; MHHW) out to the 3-nautical-mile (5.6-km) limit of California’s State Waters. Unfortunately, surveying the zone from MHHW out to 10-m water depth is not consistently possible using ship-based surveying methods, owing to sea state (for example, waves, wind, or currents), kelp coverage, and shallow rock outcrops. Accordingly, some of the data presented in this series commonly do not cover the zone from the shore out to 10-m depth. This data is part of a series of online U.S. Geological Survey (USGS) publications, each of which includes several map sheets, some explanatory text, and a descriptive pamphlet. Each map sheet is published as a PDF file. Geographic information system (GIS) files that contain both ESRI ArcGIS raster grids (for example, bathymetry, seafloor character) and geotiffs (for example, shaded relief) are also included for each publication. For those who do not own the full suite of ESRI GIS and mapping software, the data can be read using ESRI ArcReader, a free viewer that is available at http://www.esri.com/software/arcgis/arcreader/index.html (last accessed September 20, 2013). The California Seafloor Mapping Program is a collaborative venture between numerous different federal and state agencies, academia, and the private sector. CSMP partners include the California Coastal Conservancy, the California Ocean Protection Council, the California Department of Fish and Wildlife, the California Geological Survey, California State University at Monterey Bay’s Seafloor Mapping Lab, Moss Landing Marine Laboratories Center for Habitat Studies, Fugro Pelagos, Pacific Gas and Electric Company, National Oceanic and Atmospheric Administration (NOAA, including National Ocean Service–Office of Coast Surveys, National Marine Sanctuaries, and National Marine Fisheries Service), U.S. Army Corps of Engineers, the Bureau of Ocean Energy Management, the National Park Service, and the U.S. Geological Survey. These web services for the Offshore of Santa Cruz map area includes data layers that are associated to GIS and map sheets available from the USGS CSMP web page at https://walrus.wr.usgs.gov/mapping/csmp/index.html. Each published CSMP map area includes a data catalog of geographic information system (GIS) files; map sheets that contain explanatory text; and an associated descriptive pamphlet. This web service represents the available data layers for this map area. Data was combined from different sonar surveys to generate a comprehensive high-resolution bathymetry and acoustic-backscatter coverage of the map area. These data reveal a range of physiographic including exposed bedrock outcrops, large fields of sand waves, as well as many human impacts on the seafloor. To validate geological and biological interpretations of the sonar data, the U.S. Geological Survey towed a camera sled over specific offshore locations, collecting both video and photographic imagery; these “ground-truth” surveying data are available from the CSMP Video and Photograph Portal at https://doi.org/10.5066/F7J1015K. The “seafloor character” data layer shows classifications of the seafloor on the basis of depth, slope, rugosity (ruggedness), and backscatter intensity and which is further informed by the ground-truth-survey imagery. The “potential habitats” polygons are delineated on the basis of substrate type, geomorphology, seafloor process, or other attributes that may provide a habitat for a specific species or assemblage of organisms. Representative seismic-reflection profile data from the map area is also include and provides information on the subsurface stratigraphy and structure of the map area. The distribution and thickness of young sediment (deposited over the past about 21,000 years, during the most recent sea-level rise) is interpreted on the basis of the seismic-reflection data. The geologic polygons merge onshore geologic mapping (compiled from existing maps by the California Geological Survey) and new offshore geologic mapping that is based on integration of high-resolution bathymetry and backscatter imagery seafloor-sediment and rock samplesdigital camera and video imagery, and high-resolution seismic-reflection profiles. The information provided by the map sheets, pamphlet, and data catalog has a broad range of applications. High-resolution bathymetry, acoustic backscatter, ground-truth-surveying imagery, and habitat mapping all contribute to habitat characterization and ecosystem-based management by providing essential data for delineation of marine protected areas and ecosystem restoration. Many of the maps provide high-resolution baselines that will be critical for monitoring environmental change associated with climate change, coastal development, or other forcings. High-resolution bathymetry is a critical component for modeling coastal flooding caused by storms and tsunamis, as well as inundation associated with longer term sea-level rise. Seismic-reflection and bathymetric data help characterize earthquake and tsunami sources, critical for natural-hazard assessments of coastal zones. Information on sediment distribution and thickness is essential to the understanding of local and regional sediment transport, as well as the development of regional sediment-management plans. In addition, siting of any new offshore infrastructure (for example, pipelines, cables, or renewable-energy facilities) will depend on high-resolution mapping. Finally, this mapping will both stimulate and enable new scientific research and also raise public awareness of, and education about, coastal environments and issues. Web services were created using an ArcGIS service definition file. The ArcGIS REST service and OGC WMS service include all Offshore of Santa Cruz map area data layers. Data layers are symbolized as shown on the associated map sheets.

In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ecosystems as part of the design and proposal process for the establishment of Marine Protected Areas. A focus of CSMP is to map California’s State Waters with consistent methods at a consistent scale. The CSMP approach is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar data (the undersea equivalent of satellite remote-sensing data in terrestrial mapping), acoustic backscatter, seafloor video, seafloor photography, high-resolution seismic-reflection profiles, and bottom-sediment sampling data. The map products display seafloor morphology and character, identify potential marine benthic habitats, and illustrate both the surficial seafloor geology and shallow (to about 100 m) subsurface geology. It is emphasized that the more interpretive habitat and geology data rely on the integration of multiple, new high-resolution datasets and that mapping at small scales would not be possible without such data. This approach and CSMP planning is based in part on recommendations of the Marine Mapping Planning Workshop (Kvitek and others, 2006), attended by coastal and marine managers and scientists from around the state. That workshop established geographic priorities for a coastal mapping project and identified the need for coverage of “lands” from the shore strand line (defined as Mean Higher High Water; MHHW) out to the 3-nautical-mile (5.6-km) limit of California’s State Waters. Unfortunately, surveying the zone from MHHW out to 10-m water depth is not consistently possible using ship-based surveying methods, owing to sea state (for example, waves, wind, or currents), kelp coverage, and shallow rock outcrops. Accordingly, some of the data presented in this series commonly do not cover the zone from the shore out to 10-m depth. This data is part of a series of online U.S. Geological Survey (USGS) publications, each of which includes several map sheets, some explanatory text, and a descriptive pamphlet. Each map sheet is published as a PDF file. Geographic information system (GIS) files that contain both ESRI ArcGIS raster grids (for example, bathymetry, seafloor character) and geotiffs (for example, shaded relief) are also included for each publication. For those who do not own the full suite of ESRI GIS and mapping software, the data can be read using ESRI ArcReader, a free viewer that is available at http://www.esri.com/software/arcgis/arcreader/index.html (last accessed September 20, 2013). The California Seafloor Mapping Program is a collaborative venture between numerous different federal and state agencies, academia, and the private sector. CSMP partners include the California Coastal Conservancy, the California Ocean Protection Council, the California Department of Fish and Wildlife, the California Geological Survey, California State University at Monterey Bay’s Seafloor Mapping Lab, Moss Landing Marine Laboratories Center for Habitat Studies, Fugro Pelagos, Pacific Gas and Electric Company, National Oceanic and Atmospheric Administration (NOAA, including National Ocean Service–Office of Coast Surveys, National Marine Sanctuaries, and National Marine Fisheries Service), U.S. Army Corps of Engineers, the Bureau of Ocean Energy Management, the National Park Service, and the U.S. Geological Survey. These web services for the Offshore of San Gregorio map area includes data layers that are associated to GIS and map sheets available from the USGS CSMP web page at https://walrus.wr.usgs.gov/mapping/csmp/index.html. Each published CSMP map area includes a data catalog of geographic information system (GIS) files; map sheets that contain explanatory text; and an associated descriptive pamphlet. This web service represents the available data layers for this map area. Data was combined from different sonar surveys to generate a comprehensive high-resolution bathymetry and acoustic-backscatter coverage of the map area. These data reveal a range of physiographic including exposed bedrock outcrops, large fields of sand waves, as well as many human impacts on the seafloor. To validate geological and biological interpretations of the sonar data, the U.S. Geological Survey towed a camera sled over specific offshore locations, collecting both video and photographic imagery; these “ground-truth” surveying data are available from the CSMP Video and Photograph Portal at https://doi.org/10.5066/F7J1015K. The “seafloor character” data layer shows classifications of the seafloor on the basis of depth, slope, rugosity (ruggedness), and backscatter intensity and which is further informed by the ground-truth-survey imagery. The “potential habitats” polygons are delineated on the basis of substrate type, geomorphology, seafloor process, or other attributes that may provide a habitat for a specific species or assemblage of organisms. Representative seismic-reflection profile data from the map area is also include and provides information on the subsurface stratigraphy and structure of the map area. The distribution and thickness of young sediment (deposited over the past about 21,000 years, during the most recent sea-level rise) is interpreted on the basis of the seismic-reflection data. The geologic polygons merge onshore geologic mapping (compiled from existing maps by the California Geological Survey) and new offshore geologic mapping that is based on integration of high-resolution bathymetry and backscatter imagery seafloor-sediment and rock samplesdigital camera and video imagery, and high-resolution seismic-reflection profiles. The information provided by the map sheets, pamphlet, and data catalog has a broad range of applications. High-resolution bathymetry, acoustic backscatter, ground-truth-surveying imagery, and habitat mapping all contribute to habitat characterization and ecosystem-based management by providing essential data for delineation of marine protected areas and ecosystem restoration. Many of the maps provide high-resolution baselines that will be critical for monitoring environmental change associated with climate change, coastal development, or other forcings. High-resolution bathymetry is a critical component for modeling coastal flooding caused by storms and tsunamis, as well as inundation associated with longer term sea-level rise. Seismic-reflection and bathymetric data help characterize earthquake and tsunami sources, critical for natural-hazard assessments of coastal zones. Information on sediment distribution and thickness is essential to the understanding of local and regional sediment transport, as well as the development of regional sediment-management plans. In addition, siting of any new offshore infrastructure (for example, pipelines, cables, or renewable-energy facilities) will depend on high-resolution mapping. Finally, this mapping will both stimulate and enable new scientific research and also raise public awareness of, and education about, coastal environments and issues. Web services were created using an ArcGIS service definition file. The ArcGIS REST service and OGC WMS service include all Offshore of San Gregorio map area data layers. Data layers are symbolized as shown on the associated map sheets.

This part of USGS Data Series 935 (Cochrane, 2014) presents observations from underwater video collected in the Offshore of Tacoma, Washington, map area, a part of the Southern Salish Sea Map Series. To validate the interpretations of sonar data in order to turn it into geologically and biologically useful information, the U.S. Geological Survey (USGS) towed a camera sled over specific locations throughout the Tacoma map area to collect video and photographic data that would “ground truth” the seafloor. The ground-truth survey conducted in the Tacoma map area occurred in 2009 and 2011 on the R/V Karluk (USGS field activity K109PS, and K0111PS) and on the Washington State Department of Fish and Game R/V Molluscan in 2011 and 2012 (USGS field activity M0111PS, M0112PS, and M0212PS). The camera sled was towed 1 to 2 m above the seafloor at speeds of between 1 and 2 nautical miles/hour. The surveys for this map area includes approximately 30 hours (47 trackline km) of video.

This data set consists of physics-based Delft3D-Flexible Mesh hydrodynamic model input files that are used to simulate compound flood exposure of the lower Nooksack River and delta of western Washington State under existing and future conditions of anticipated climate and land-use change. The model enables assessment of the changing flood exposure associated with the cumulative impacts of expected sea-level rise, greater tidal inundation, more frequent storm surge effects, and higher winter stream floods in the 2040s and 2080s. The model also accounts for proposed flood mitigation strategies, and recently observed decadal climate-driven sedimentation patterns. Example model input and configuration files are included for the base 2020 flood and the 2020 flood under the 2080s high change scenario and alternative 3B flood mitigation strategy.

Computed flood depths associated with the combined influence of sea level position, tides, storm surge, and streamflow under existing conditions and projected future higher sea level and peak stream runoff are provided for the lower (Reach 1) of the Nooksack River and delta in Whatcom County, western Washington State. The flood-depth projection data are provided in a series of raster geotiff files. Flood-depth projections were computed using a system of numerical models that accounted for projected changes in climate forcing including sea level rise, storm surge, and stream discharge in the 2040s and 2080s based on the Coupled Model Intercomparison Project Phase 5 (CMIP5) Global Climate Model (GCM) projections. Additionally, the models were run with modifications to land surface elevations to represent proposed flood hazard reduction and salmon habitat restoration strategies (alternatives) under existing and future conditions. Variations of the models also simulated changes to the stream bed to reflect recently observed decadal-scale sedimentation patterns that affect flow conveyance and flood risk.

1-m resolution acoustic-backscatter data were collected during a February 2013 SWATHPlus survey offshore of the Hawaiian Islands of Maui and Kaho`olawe. Data were collected and processed by the U.S. Geological Survey (USGS), Pacific Coastal and Marine Science Center (PCMSC), with fieldwork activity number A-01-13-HW. The 1-m backscatter data are provided as a GeoTIFF file.

1-m resolution bathymetry data were collected during a February 2013 SWATHPlus survey offshore of the Hawaiian Islands of Maui and Kaho`olawe. Data were collected and processed by the U.S. Geological Survey (USGS), Pacific Coastal and Marine Science Center (PCMSC), with fieldwork activity number A-01-13-HW. The 1-m bathymetry data are provided as a GeoTIFF file.

Simulatations of water levels in the Salish Sea for a continuous hindcast of the period October 1, 1985, to September 30, 2015 were conducted to evaluate the utility and skill of a sea-level anomaly predictor and to develop extreme water level estimates accounting for decadal climate variability. The model accounts for sea level position, tides, remote sea-level anomalies, local winds and storm surge and stream flows as they affect water density. Comparison of modeled and measured water levels showed the model predicts extreme water levels at NOAA tide gage stations within 0.15 m. Model inputs and outputs of time-series water levels along the -5 m depth isobath are presented. In addition, extreme water level recurrence for the 1-,2-,5-,10-,20-,50-, and 100-year water levels computed from annual Maxima/Generalized Extreme Value (AM/GEV) and peak-over-threshold (POT) extreme value analyses across the entire domain are presented.

Simulations of the period 2016-2099 were conducted using the Salish Sea hydrodynamic model to evaluate extreme water levels associated with anticipated changes in sea level and climate forcing. The model projections accounting for sea level position, tides, remote sea-level anomalies, local winds and storm surge and stream flows as they affect water density. Dynamically downscaled Weather Research and Forecasting (WRF) CMIP5 GFDL wind and atmospheric pressure fields were prescribed over the model open boundary and used to compute sea-level anomaly prescribed at the model ocean boundary. Simulations were made for eight different Sea-Level Rise (SLR) conditions, 0, 0.25, 0.5, 1, 1.5, 2, 3, and 5 meters relative to current conditions (1983-2001 epoch) and provided as time-series outputs along the -5 m depth isobath. Model inputs are also provided.

Simulations of water levels in the Salish Sea over the period October 1, 2016 to September 30, 2020 were conducted to validate the Salish Sea hydrodynamic model. The model accounts for sea level position, tides, remote sea-level anomalies, local winds and storm surge and stream flows as they affect water density. Comparison of modeled and measured water levels showed the model predicts extreme water levels at NOAA and USGS tide gage stations within 0.15 m. Model inputs and outputs of time-series forcing and water levels, respectively, are presented.

This portion of the USGS data release presents bathymetry data collected during surveys performed in the Columbia River littoral cell and mouth of the Columbia River, Washington and Oregon, in 2022 (USGS Field Activity Number 2022-641-FA). Bathymetry data were collected using four personal watercraft (PWCs) equipped with single-beam sonar systems and global navigation satellite system (GNSS) receivers. The sonar systems consisted of either an Odom Echotrac CV-100 or CEE Hydrosystems Ceescope single-beam echosounder and 200 kHz transducer with a 9-degree beam angle. Raw acoustic backscatter returns were digitized by the echosounder with a vertical resolution of 1.25 cm. Depths from the echosounders were computed using sound velocity profiles measured using a YSI CastAway CTD during the survey. Positioning of the survey vessels was determined at 5 to 10 Hz using either Trimble R9s or Trimble BD990 GNSS receivers. Output from the GNSS receivers and sonar systems were combined in real time on the PWC by a computer running HYPACK hydrographic survey software. Navigation information was displayed on a video monitor, allowing PWC operators to navigate along survey lines at speeds of 2 to 3 m/s. Survey-grade positions of the PWCs were achieved with a single-base station and differential post-processing. Positioning data from the GNSS receivers were post-processed using Waypoint Grafnav to apply differential corrections from a GNSS base station with known horizontal and vertical coordinates relative to the North American Datum of 1983. Orthometric elevations relative to the NAVD88 vertical datum were computed using National Geodetic Survey Geoid12a offsets. Bathymetric data were merged with post-processed positioning data and spurious soundings were removed using a custom Graphical User Interface (GUI) programmed with the computer program MATLAB. The average estimated vertical uncertainty of the bathymetric measurements is 10 cm. The final point data from the PWCs are provided in a comma-separated text file and are projected in cartesian coordinates using the Washington State Plane South, meters coordinate system.

This portion of the USGS data release presents topography data collected during surveys performed in the Columbia River littoral cell, Washington and Oregon, in 2022 (USGS Field Activity Number 2022-641-FA). Topographic profiles were collected by walking along survey lines with global navigation satellite system (GNSS) receivers mounted on backpacks. Prior to data collection, vertical distances between the GNSS antennas and the ground were measured using a tape measure. Hand-held data collectors were used to log raw data and display navigational information allowing surveyors to navigate survey lines spaced at 100- to 1000-m intervals along the beach. Profiles were surveyed from the landward edge of the study area (either the base of a bluff, engineering structure, or just landward of the primary dune) over the beach foreshore, to wading depth on the same series of transects as nearshore bathymetric surveys that were conducted during the same time period. Additional topographic data were collected between survey lines in some areas with an all-terrain vehicle (ATV) equipped with a GNSS receiver to constrain the elevations and alongshore extent of major morphological features. Positioning data from the survey platforms were referenced to a GNSS base station with known horizontal and vertical coordinates relative to the North American Datum of 1983. Differential corrections from the GNSS base stations to the survey platforms were either applied in real-time with a UHF radio link, or post-processed using Trimble Business Center software. Orthometric elevations relative to the NAVD88 vertical datum were computed using National Geodetic Survey Geoid12a offsets. The average estimated vertical uncertainty of the topographic measurements is 4 cm. The final point data are provided in comma-separated text format and are projected in Cartesian coordinates using the Washington State Plane South, meters coordinate system.

This portion of the USGS data release presents bathymetry data collected during surveys performed in the Columbia River littoral cell and mouth of the Columbia River, Washington and Oregon, in 2023 (USGS Field Activity Number 2023-644-FA). Bathymetry data were collected using four personal watercraft (PWCs) equipped with single-beam sonar systems and global navigation satellite system (GNSS) receivers. The sonar systems consisted of either an Odom Echotrac CV-100 or CEE Hydrosystems Ceescope single-beam echosounder and 200 kHz transducer with a 9-degree beam angle. Raw acoustic backscatter returns were digitized by the echosounder with a vertical resolution of 1.25 cm. Depths from the echosounders were computed using sound velocity profiles measured using a YSI CastAway CTD during the survey. Positioning of the survey vessels was determined at 5 to 10 Hz using either Trimble R9s or Trimble BD990 GNSS receivers. Output from the GNSS receivers and sonar systems were combined in real time on the PWC by a computer running HYPACK hydrographic survey software. Navigation information was displayed on a video monitor, allowing PWC operators to navigate along survey lines at speeds of 2 to 3 m/s. Survey-grade positions of the PWCs were achieved with a single-base station and differential post-processing. Positioning data from the GNSS receivers were post-processed using Waypoint Grafnav to apply differential corrections from a GNSS base station with known horizontal and vertical coordinates relative to the North American Datum of 1983. Orthometric elevations relative to the NAVD88 vertical datum were computed using National Geodetic Survey Geoid12a offsets. Bathymetric data were merged with post-processed positioning data and spurious soundings were removed using a custom Graphical User Interface (GUI) programmed with the computer program MATLAB. The average estimated vertical uncertainty of the bathymetric measurements is 10 cm. The final point data from the PWCs are provided in a comma-separated text file and are projected in cartesian coordinates using the Washington State Plane South, meters coordinate system.

This portion of the USGS data release presents topography data collected during surveys performed in the Columbia River littoral cell, Washington and Oregon, in 2023 (USGS Field Activity Number 2023-644-FA). Topographic profiles were collected by walking along survey lines with global navigation satellite system (GNSS) receivers mounted on backpacks. Prior to data collection, vertical distances between the GNSS antennas and the ground were measured using a tape measure. Hand-held data collectors were used to log raw data and display navigational information allowing surveyors to navigate survey lines spaced at 100- to 1000-m intervals along the beach. Profiles were surveyed from the landward edge of the study area (either the base of a bluff, engineering structure, or just landward of the primary dune) over the beach foreshore, to wading depth on the same series of transects as nearshore bathymetric surveys that were conducted during the same time period. Additional topographic data were collected between survey lines in some areas with an all-terrain vehicle (ATV) equipped with a GNSS receiver to constrain the elevations and alongshore extent of major morphological features. Positioning data from the survey platforms were referenced to a GNSS base station with known horizontal and vertical coordinates relative to the North American Datum of 1983. Differential corrections from the GNSS base stations to the survey platforms were either applied in real-time with a UHF radio link, or post-processed using Trimble Business Center software. Orthometric elevations relative to the NAVD88 vertical datum were computed using National Geodetic Survey Geoid12a offsets. The average estimated vertical uncertainty of the topographic measurements is 4 cm. The final point data are provided in comma-separated text format and are projected in Cartesian coordinates using the Washington State Plane South, meters coordinate system.

Projected flood velocities associated with compound coastal flood hazards for future sea-level rise (SLR) and storm scenarios are provided for Whatcom County, Washington, in a series of raster geotiff files. Projections were made using a system of numerical models with atmospheric forcing, tides, sea level position and stream discharge driven by output from Global Climate Models (GCMs) from the Coupled Model Intercomparison Project Phase 5 (CMIP5). The resulting computed coastal flood velocities along the Whatcom County coast due to predicted sea level rise and future storm conditions consider the changing climate. In addition to sea-level rise, flood simulations run by these numerical models included dynamic contributions from tide, storm surge, wind, waves, and seasonal sea-level fluctuations. In the absence of concordant downscaled GCM stream discharge, daily average stream discharge was fed to the model. Outputs include flood velocities from the combinations of SLR scenarios (0, 0.25, 0.5, 1.0, 1.5, 2.0, 2.5, 3.0 and 5.0 m) storm conditions including 1-year, 5-year, 10-year, 20-year, 50-year and 100-year return interval storms and a background condition (no storm - astronomic tide and average atmospheric conditions). Predicted flood velocities during the largest annual astronomic tides (King Tide) in combination with an average storm surge scenario are also provided.

Groundwater emergence and shoaling extents are derived from water table depth GeoTIFFs, which are calculated as steady-state groundwater model heads subtracted from high-resolution topographic digital elevation model (DEM) land surface elevations. Results are provided as shapefiles of water table depth in specific depth ranges.

Seamless unconfined groundwater heads for coastal groundwater systems around Puget Sound (Washington State) were modeled with homogeneous, steady-state MODFLOW simulations. The geographic extent examined was defined primarily by watershed boundaries. Steady-state MODFLOW groundwater flow models were used to obtain detailed (50-meter-scale) predictions over large geographic scales (100s of kilometers) of groundwater heads for both current and future sea-level rise (SLR) scenarios (0, 0.25, 0.5, 1, 1.5, 2, 2.5, and 3 m) using 3 spatially varying hydraulic conductivities (K); one based on published K's, one with published K's reduced by a factor of 10 (K*0.1), and one with published K's increased by a factor of 10 (K*10), to assess the sensitivity of model results to K. All models had variable thicknesses with cell tops at the land surface and bottoms at 0m NAVD88 to ensure that steep groundwater gradients in topographically steep and/or high-recharge watersheds did not result in model convergence failure. The models were run with a local mean higher-high water (MHHW) marine boundary condition and with groundwater reaching the land surface removed from the model, simulating loss via natural drainage. Because of the large number of lakes in this region and the influence of lakes on adjacent groundwater levels, large (> 0.5 km2) lake heads were fixed in the model at published present-day levels, In sea-level rise cases where lake elevations would have been below model sea level, lake elevations were raised to model sea level.

To predict water table depths, seamless unconfined groundwater heads for coastal groundwater systems around Puget Sound (Washington State) were modeled with homogeneous, steady-state MODFLOW simulations. The geographic extent examined was defined primarily by watershed boundaries. Steady-state MODFLOW groundwater flow models were used to obtain detailed (50-meter-scale) predictions over large geographic scales (100s of kilometers) of groundwater heads for both current and future sea-level rise (SLR) scenarios (0, 0.25, 0.5, 1, 1.5, 2, 2.5, and 3 m) using 3 spatially varying hydraulic conductivities (K); one based on published K's, one with published K's reduced by a factor of 10 (K*0.1), and one with published K's increased by a factor of 10 (K*10), to assess the sensitivity of model results to K. All models had variable thicknesses with cell tops at the land surface and bottoms at 0m NAVD88 to ensure that steep groundwater gradients in topographically steep and/or high-recharge watersheds did not result in model convergence failure. The models were run with a local mean higher-high water (MHHW) marine boundary condition and with groundwater reaching the land surface removed from the model, simulating loss via natural drainage. Because of the large number of lakes in this region and the influence of lakes on adjacent groundwater levels, large (> 0.5 km2) lake heads mostly were fixed in the model at published present-day levels. In sea-level rise cases where lake elevations would have been below model sea level, lake elevations were set at model sea level. Modeled groundwater heads were then subtracted from high-resolution topographic digital elevation model (DEM) data to obtain water table depths.

This data set consists of physics-based XBeach and SFINCS hydrodynamic model input files used for Coastal Storm Modeling System (CoSMoS) Tier 3 simulations. This data release is for Whatcom County in Washington State and presents the final tier 3 models used to produce output data that is then post-processed into final CoSMoS products. Example model input and configuration files are included for a single domain and SLR scenario, with the full modelling framework iterating on this process to simulate hundreds of individual storm events and sea-level rise (SLR) scenarios.

Projected impacts by compound coastal flood hazards for future sea-level rise (SLR) and storm scenarios are shown for the U.S. Atlantic coast for three states (Florida, Georgia, and southern Virginia). Accompanying uncertainty for each SLR and storm scenario, indicating total uncertainty from model processes and contributing datasets, are illustrated in maximum and minimum flood potential. As described by Nederhoff and others (2024), projections were made using a system of numerical models driven by output from Global Climate Models (GCMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6) and a tropical cyclone database from US Army Corp of Engineers. The resulting data products include detailed flood-hazard maps along the U.S. Atlantic coast due to sea-level rise and plausible future storm conditions that consider the changing climate, hurricanes, and natural variability. In addition to sea-level rise, flood simulations run by these numerical models included dynamic contributions from tide, storm surge, wind, waves, river discharge, precipitation, and seasonal sea-level fluctuations. Outputs include impacts from combinations of SLR scenarios (0, 0.25, 0.5, 1.0, 1.5, 2.0, and 3.0 m) storm conditions including 1-year, 20-year and 100-year return interval storms and a background condition (no storm - astronomic tide and average atmospheric conditions). See Nederhoff and others (2024) for a full explanation of data and methods. Similar projections for North Carolina and South Carolina are available from Barnard and others, 2023, at https://doi.org/10.5066/P9W91314.

Projected depths from compound coastal flood hazards for future sea-level rise (SLR) and storm scenarios are shown for the U.S. Atlantic coast for three states (Florida, Georgia, and Virginia). Projections were made using a system of numerical models driven by output from Global Climate Models (GCMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6) and a tropical cyclone database from U.S. Army Corp of Engineers. The resulting data are depths of projected flood hazards along the U.S. Atlantic coast due to sea-level rise and plausible future storm conditions that consider the changing climate, hurricanes, and natural variability. The resulting data products include flood depths that are consistent with coastal flood projections, also available in this dataset (Barnard, and others, 2023); see Nederhoff and others (2024) for a full explanation of data and methods. In addition to sea-level rise, flood simulations run by these numerical models included dynamic contributions from tide, storm surge, wind, waves, river discharge, precipitation, and seasonal sea-level fluctuations. Outputs include impacts from combinations of SLR scenarios (0, 0.25, 0.5, 1.0, 1.5, 2.0, and 3.0 m), storm conditions including 1-year, 20-year, and 100-year return interval storms, and a background condition (no storm - astronomic tide and average atmospheric conditions). Similar projections for North Carolina and South Carolina are available from Barnard and others, 2023, at https://doi.org/10.5066/P9W91314

Projected impacts by compound coastal flood hazards for future sea-level rise (SLR) and storm scenarios are shown for North Carolina and South Carolina. Accompanying uncertainty for each SLR and storm scenario, indicating total uncertainty from model processes and contributing datasets, are illustrated in maximum and minimum flood potential. As described by Nederhoff and others (2024), projections were made using a system of numerical models driven by output from Global Climate Models (GCMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6) and a tropical cyclone database from US Army Corp of Engineers. The resulting data products include detailed flood-hazard maps along the North Carolina and South Carolina coast due to sea level rise and plausible future storm conditions that consider the changing climate, hurricanes, and natural variability. In addition to sea-level rise, flood simulations run by these numerical models included dynamic contributions from tide, storm surge, wind, waves, river discharge, precipitation, and seasonal sea-level fluctuations. Outputs include impacts from combinations of SLR scenarios (0, 0.25, 0.5, 1.0, 1.5, 2.0, and 3.0 m) storm conditions including 1-year, 20-year and 100-year return interval storms and a background condition (no storm - astronomic tide and average atmospheric conditions).

Projected water depths from compound coastal flood hazards for future sea-level rise (SLR) and storm scenarios are shown for North Carolina and South Carolina. As described by Nederhoff and others (2024), projections were made using a system of numerical models driven by output from Global Climate Models (GCMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6) and a tropical cyclone database from U.S. Army Corp of Engineers. The resulting data are depths of projected flood hazards along the North Carolina and South Carolina coast due to sea level rise and plausible future storm conditions that consider the changing climate, hurricanes, and natural variability. The resulting data products include water depths that are consistent with coastal flood projections, also available in this dataset (Barnard, and others, 2023). In addition to sea-level rise, flood simulations run by these numerical models included dynamic contributions from tide, storm surge, wind, waves, river discharge, precipitation, and seasonal sea-level fluctuations. Outputs include impacts from combinations of SLR scenarios (0, 0.25, 0.5, 1.0, 1.5, 2.0, and 3.0 m), storm conditions including 1-year, 20-year, and 100-year return interval storms, and a background condition (no storm - astronomic tide and average atmospheric conditions).

Projected wave heights associated with compound coastal flood hazards for existing and future sea-level rise (SLR) and storm scenarios are shown for Whatcom County, Washington, in a series of raster geotiff files. Projections were made using a system of numerical models driven by output from Global Climate Models (GCMs) from the Coupled Model Intercomparison Project Phase 5 (CMIP5). The resulting data are water levels of projected flood hazards along the Whatcom County coast due to sea level rise and plausible future storm conditions that consider the changing climate and natural variability. In addition to sea-level rise, flood simulations run by these numerical models included dynamic contributions from tide, storm surge, wind, waves, river discharge, and seasonal sea-level fluctuations. Outputs include waves from combinations of SLR scenarios (0, 0.25, 0.5, 1.0, 1.5, 2.0, 2.5, 3.0 and 5.0 m) storm conditions including 1-year, 5-year, 10-year, 20-year, 50-year and 100-year return interval storms and a background condition (no storm - astronomic tide and average atmospheric conditions). The annual average King Tide is also provided and includes mean storm surge occurring during King Tides.

Projected flood duration associated with compound coastal flood hazards for future sea-level rise (SLR) and storm scenarios are provided for Whatcom County, Washington, in a series of raster geotiff files. Projections were made using a system of numerical models with atmospheric forcing, tides, sea level position and stream discharge driven by output from Global Climate Models (GCMs) from the Coupled Model Intercomparison Project Phase 5 (CMIP5). The resulting computed coastal flood duration along the Whatcom County coast due to predicted sea level rise and future storm conditions consider the changing climate. In addition to sea-level rise, flood simulations run by these numerical models included dynamic contributions from tide, storm surge, wind, waves, and seasonal sea-level fluctuations. In the absence of concordant downscaled GCM stream discharge, daily average stream discharge was fed to the model. Outputs include flood durations from the combinations of SLR scenarios (0, 0.25, 0.5, 1.0, 1.5, 2.0, 2.5, 3.0 and 5.0 m) storm conditions including 1-year, 5-year, 10-year, 20-year, 50-year and 100-year return interval storms and a background condition (no storm - astronomic tide and average atmospheric conditions). Predicted flood duration during the largest annual astronomic tides (King Tide) in combination with an average storm surge scenario are also provided.

Projected flood extents associated with compound coastal flood hazards for future sea-level rise (SLR) and storm scenarios are provided for Whatcom County, Washington, in a series of shapefile files. Projections were made using a system of numerical models with atmospheric forcing, tides, sea level position and stream discharge driven by output from Global Climate Models (GCMs) from the Coupled Model Intercomparison Project Phase 5 (CMIP5). The resulting computed coastal flood extents along the Whatcom County coast due to predicted sea level rise and future storm conditions consider the changing climate. In addition to sea-level rise, flood simulations run by these numerical models included dynamic contributions from tide, storm surge, wind, waves, and seasonal sea-level fluctuations. In the absence of concordant downscaled GCM stream discharge, daily average stream discharge was fed to the model. Outputs include flood extents from the combinations of SLR scenarios (0, 0.25, 0.5, 1.0, 1.5, 2.0, 2.5, 3.0 and 5.0 m) storm conditions including 1-year, 5-year, 10-year, 20-year, 50-year and 100-year return interval storms and a background condition (no storm - astronomic tide and average atmospheric conditions). Predicted flood extents during the largest annual astronomic tides (King Tide) in combination with an average storm surge scenario are also provided.

Projected flood depths associated with compound coastal flood hazards for future sea-level rise (SLR) and storm scenarios are provided for Whatcom County, Washington, in a series of raster geotiff files. Projections were made using a system of numerical models with atmospheric forcing, tides, sea level position and stream discharge driven by output from Global Climate Models (GCMs) from the Coupled Model Intercomparison Project Phase 5 (CMIP5). The resulting computed coastal flood depths along the Whatcom County coast due to predicted sea level rise and future storm conditions consider the changing climate. In addition to sea-level rise, flood simulations run by these numerical models included dynamic contributions from tide, storm surge, wind, waves, and seasonal sea-level fluctuations. In the absence of concordant downscaled GCM stream discharge, daily average stream discharge was fed to the model. Outputs include flood depths from the combinations of SLR scenarios (0, 0.25, 0.5, 1.0, 1.5, 2.0, 2.5, 3.0 and 5.0 m) storm conditions including 1-year, 5-year, 10-year, 20-year, 50-year and 100-year return interval storms and a background condition (no storm - astronomic tide and average atmospheric conditions). Predicted flood depths during the largest annual astronomic tides (King Tide) in combination with an average storm surge scenario are also provided.

Projected flood levels associated with compound coastal flood hazards for future sea-level rise (SLR) and storm scenarios are provided for Whatcom County, Washington, in a series of raster geotiff files. Projections were made using a system of numerical models with atmospheric forcing, tides, sea level position and stream discharge driven by output from Global Climate Models (GCMs) from the Coupled Model Intercomparison Project Phase 5 (CMIP5). The resulting computed coastal flood levels along the Whatcom County coast due to predicted sea level rise and future storm conditions consider the changing climate. In addition to sea-level rise, flood simulations run by these numerical models included dynamic contributions from tide, storm surge, wind, waves, and seasonal sea-level fluctuations. In the absence of concordant downscaled GCM stream discharge, daily average stream discharge was fed to the model. Outputs include flood levels from the combinations of SLR scenarios (0, 0.25, 0.5, 1.0, 1.5, 2.0, 2.5, 3.0 and 5.0 m) storm conditions including 1-year, 5-year, 10-year, 20-year, 50-year and 100-year return interval storms and a background condition (no storm - astronomic tide and average atmospheric conditions). Predicted flood levels during the largest annual astronomic tides (King Tide) in combination with an average storm surge scenario are also provided.

Bathymetric data collected in Whales Tail Marsh tidal creeks, South San Francisco Bay, California, in 2023 with a shallow draft vessel equipped with a single-beam sonar system and global navigation satellite system (GNSS) receiver. The bathymetric data are provided in a comma-separated text file.

Whales Tail Marsh, a restored salt pond in South San Francisco Bay, California, is experiencing rapid shoreline erosion. Determining whether the eroded sediment is exported to the ocean or imported via tidal channels and deposited on the marsh platform is critical to understanding the long-term response of the marsh to wave attack and sea-level rise. Quantifying water-column sediment flux helps to characterize the role of tidal channels in this process, and water discharge is a key component of sediment flux. To that end, discharge was measured repeatedly over diurnal tidal cycles in the tidal channels of the Whales Tail Marsh, within Eden Landing Ecological Refuge, California in the summer of 2021 and during king tides in the winter of 2021-2022. These transect data were collected by using a downward-looking Teledyne RDI RiverPro 1200-kilohertz acoustic doppler current profiler (ADCP) from a moving boat.

Spatial surveys of water column physical properties were acquired with a conductivity-temperature-depth (CTD) profiler for five (5) surveys in summer 2021 and three (3) surveys in winter 2021-2022 during king tides along transects of tidal creeks in the Whales Tail Marsh, South San Francisco Bay, California. The data are provided in netCDF files.

Corte Madera Marsh, located in northern San Francisco Bay, California, is experiencing shoreline erosion. Determining whether the eroded sediment is exported to the bay or imported via tidal channels and deposited on the marsh platform is critical to understanding the long-term response of the marsh to wave attack and sea-level rise. Quantifying water-column sediment flux helps to characterize the role of tidal channels in this process, and water discharge is a key component of sediment flux. Tidal creek discharge was measured repeatedly over diurnal tidal cycles in a tidal channel located in the central, Muzzi marsh region of Corte Madera marsh, California during the summer of 2022 and during the winter of 2023. These transect data were collected using a downward-looking Teledyne RDI RiverPro 1200-kilohertz acoustic Doppler current profiler (ADCP) from a moving boat.

Hydrodynamic and sediment transport time-series data, including water depth, velocity, turbidity, conductivity, and temperature, were collected by the U.S. Geological Survey (USGS) Pacific Coastal and Marine Science Center at shallow subtidal and intertidal sites in Corte Madera Bay and San Pablo Bay National Wildlife Refuge (SPNWF) in San Francisco Bay, CA, as well as on the marsh plain of SPNWF marsh and in a tidal creek and on the marsh plain of Corte Madera Marsh, in 2022 and 2023. Data files are grouped by station, San Pablo subtidal, San Pablo intertidal, San Pablo marsh, Corte Madera subtidal, Corte Madera intertidal, Corte Madera marsh, or Corte Madera tidal creek, then by instrument type. At most stations there were periods of low water when sensors were no longer submerged, resulting in spurious data. In addition, most instruments experienced some degree of biofouling, particularly at the subtidal and intertidal stations. The subtidal stations also occasionally show signs of platform rocking or movement due to strong water flow, and/or from accidental fisher/boater interference. Users are advised to assess data quality carefully, and to check the metadata for instrument information, as platform deployment times and data-processing methods varied.

This dataset contains projections of shoreline change and uncertainty bands across California for future scenarios of sea-level rise (SLR). Projections were made using the Coastal Storm Modeling System - Coastal One-line Assimilated Simulation Tool (CoSMoS-COAST), a numerical model run in an ensemble forced with global-to-local nested wave models and assimilated with satellite-derived shoreline (SDS) observations across the state. Scenarios include 25, 50, 75, 100, 125, 150, 175, 200, 250, 300 and 500 centimeters (cm) of SLR by the year 2100. Output for SLR of 0 cm is also included, reflective of conditions in 2000. This model shows change in shoreline positions along pre-determined cross-shore transects, considering sea level, wave conditions, along-shore/cross-shore sediment transport, long-term trends due to sediment supply, and estimated variability due to unresolved processes (as described in Vitousek and others, 2021). Variability associated with complex coastal processes (for example, beach cusps/undulations and shore-attached sandbars) are included via a noise parameter in a model, which is tuned using observations of shoreline change at each transect and run in an ensemble of 200 simulations; this approach allows for a representation of statistical variability in a model that is assimilated with sequences of noisy observations. The model synthesizes and improves upon numerous, well-established shoreline models in the scientific literature; processes and methods are described in this metadata (see lineage and process steps), but also described in more detail in Vitousek and others 2017, 2021, and 2023. Output includes different cases covering important model behaviors (cases are described in process steps of this metadata). KMZ data are readily viewable in Google Earth. For best display of results, it is recommended to turn off any 3D features or terrain. For technical users and researchers, shapefile and KMZ data can be ingested into geographic information system (GIS) software such as Global Mapper or QGIS.

Modeled wave time series from a downscaled wave data base (DWDB) are presented for the period 2020 to 2050, for locations from the U.S. Canada border to the southern boundary of Norton Sound along the approximate 5 and 10 m isobaths. The model boundary conditions were determined from wave time-series computed with a global WAVEWATCHIII (WWIII) model (Erikson and others,2024) and wind conditions, forced with models from the Coupled Model Intercomparison Project (CMIP6) future period. Wave data are provided for four CMIP6 models (see Process Description for details) from the HighResMIP project. Outputs include three-hourly nearshore significant wave heights (Hs), mean wave periods (Tm01) and mean wave directions (Dm) for 8485 (5 m isobath) and 8232 (10 m isobath) locations. Data are available as netCDF files and are packaged for the Beaufort Sea region from the U.S. Canada border to Nuwuk (Point Barrow), for the Chukchi Sea region from Nuwuk to Kotzebue Sound and from Kotzebue Sound to the Bering Strait, and from the Bering Strait to Norton Sound. The methods used to create this dataset are described in detail in Engelstad and others, 2024.

Modeled wave time series from a downscaled wave data base (DWDB) are presented for the period 1979 to 2014, for locations from the U.S. Canada border to the southern boundary of Norton Sound along the approximate 5 and 10 m isobaths. The model boundary conditions were determined from wave time-series computed with a global WAVEWATCHIII (WWIII) model (Erikson and others, 2024) and wind conditions, forced with models from the Coupled Model Intercomparison Project (CMIP6) historical period. Wave data are provided for four CMIP6 models (see Process Description for details) from the HighResMIP project. Outputs include three-hourly nearshore significant wave heights (Hs), mean wave periods (Tm01) and mean wave directions (Dm) for 8485 (5 m isobath) and 8232 (10 m isobath) locations. Data are available as netCDF files and are packaged for the Beaufort Sea region from the U.S. Canada border to Nuwuk (Point Barrow), for the Chukchi Sea region from Nuwuk to Kotzebue Sound and from Kotzebue Sound to the Bering Strait, and from the Bering Strait to Norton Sound. The methods used to create this dataset are described in detail in Engelstad and others, 2024.

Modeled wave time series data from a downscaled wave database (DWDB)are presented for the hindcast period of 1979 to 2023 from the U.S. Canada border to Norton Sound close to the 5 and 10 m isobaths. Outputs include three-hourly nearshore significant wave heights (Hs), mean wave periods (Tm) and mean wave directions (Dm) for 8485 (5 m isobath) and 8232 (10 m isobath) locations. Data are available as netCDF files and are packaged for the Beaufort Sea region from the U.S. Canada border to Nuwuk (Point Barrow), for the Chukchi Sea region from Nuwuk to Kotzebue Sound and from Kotzebue Sound to the Bering Strait, and from the Bering Strait to the southern boundary of Norton Sound. The methods used to create this dataset are described in detail in Engelstad and others, 2024

Provided here are the required input files to run a standalone wave model (Simulating Waves Nearshore [SWAN]; Booij and others, 1999) on eleven model domains from the Canada-U.S. border to Norton Sound, Alaska. The model runs create a downscaled wave database (DWDB) which, can be used to reconstruct hindcast, historical, or projected time series at each point in the model domains (see Engelstad and others, 2023 for further information on reconstruction of time-series). The model forcing files consist of reduced sets of binned wind and wave parameter combinations, hereafter termed ‘sea states’. The use of representative sea states allows for lower computational costs and follows modified methods outlined in for example Camus and others, 2011, Reguero and others, 2013, and Lucero and others, 2017. Wind and wave parameters were extracted from the ERA5 reanalysis (Hersbach and others, 2020; https://cds.climate.copernicus.eu/) for the hindcast period (1979–2019) and for the historical (1979-2014) and projected (2020-2050) time periods from WAVEWATCHIII wave model runs (Erikson and others, 2022) driven by winds and sea ice fields from the 6th generation Coupled Model Inter-comparison Projects (CMIP6 Haarsma and others, 2016 The extent of each model domain can be inferred from the browse graphic. Model input files are described in the Entity and Attribute Overview section.

Projected water elevations from compound coastal flood hazards for future sea-level rise (SLR) and storm scenarios are shown for the U.S. Atlantic coast for three states (Florida, Georgia, and Virginia). Projections were made using a system of numerical models driven by output from Global Climate Models (GCMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6) and a tropical cyclone database from U.S. Army Corps of Engineers. The resulting data are water elevations of projected flood hazards along the U.S. Atlantic coast due to sea-level rise and plausible future storm conditions that consider the changing climate, hurricanes, and natural variability. The resulting data products include water elevations that are consistent with coastal flood projections, also available in this dataset (Barnard, and others, 2023); see Nederhoff and others (2024) for a full explanation of data and methods. In addition to sea-level rise, flood simulations run by these numerical models included dynamic contributions from tide, storm surge, wind, waves, river discharge, precipitation, and seasonal sea-level fluctuations. Outputs include impacts from combinations of SLR scenarios (0, 0.25, 0.5, 1.0, 1.5, 2.0, and 3.0 m), storm conditions including 1-year, 20-year, and 100-year return interval storms, and a background condition (no storm - astronomic tide and average atmospheric conditions). Similar projections for North Carolina and South Carolina are available from Barnard and others, 2023, at https://doi.org/10.5066/P9W91314

Projected water elevations from compound coastal flood hazards for future sea-level rise (SLR) and storm scenarios are shown for North Carolina and South Carolina. As described by Nederhoff and others (2024), projections were made using a system of numerical models driven by output from Global Climate Models (GCMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6) and a tropical cyclone database from U.S. Army Corps of Engineers. The resulting data are elevations of projected flood hazards along the North Carolina and South Carolina coast due to sea level rise and plausible future storm conditions that consider the changing climate, hurricanes, and natural variability. The resulting data products include water elevations that are consistent with coastal flood projections, also available in this dataset (Barnard, and others, 2023). In addition to sea-level rise, flood simulations run by these numerical models included dynamic contributions from tide, storm surge, wind, waves, river discharge, precipitation, and seasonal sea-level fluctuations. Outputs include impacts from combinations of SLR scenarios (0, 0.25, 0.5, 1.0, 1.5, 2.0, and 3.0 m), storm conditions including 1-year, 20-year, and 100-year return interval storms, and a background condition (no storm - astronomic tide and average atmospheric conditions).

On July 17, 2018, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jensen Beach, Florida. This dataset, Jensen_20180717.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and others, 2018), data were acquired by USGS scientists walking along cross-shore transect lines while carrying a survey backpack that was equipped with a Global Navigation Satellite System (GNSS) receiver and GNSS antenna. The horizontal position data are provided in the Universal Transverse Mercator (UTM) coordinate system, Zone 17 North (17N), referenced to the North American Datum of 1983 (NAD83), and the elevation data are referenced to the North American Vertical Datum of 1988 (NAVD88), GEOID12B.

On August 07, 2018, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jensen Beach, Florida. This dataset, Jensen_20180807.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and others, 2018), data were acquired by USGS scientists walking along cross-shore transect lines while carrying a survey backpack that was equipped with a Global Navigation Satellite System (GNSS) receiver and GNSS antenna. The horizontal position data are provided in the Universal Transverse Mercator (UTM) coordinate system, Zone 17 North (17N), referenced to the North American Datum of 1983 (NAD83), and the elevation data are referenced to the North American Vertical Datum of 1988 (NAVD88), GEOID12B.

On May 22, 2019, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jensen Beach, Florida. This dataset, Jensen_20190522.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and others, 2018), data were acquired by USGS scientists walking along cross-shore transect lines while carrying a survey backpack that was equipped with a Global Navigation Satellite System (GNSS) receiver and GNSS antenna. The horizontal position data are provided in the Universal Transverse Mercator (UTM) coordinate system, Zone 17 North (17N), referenced to the North American Datum of 1983 (NAD83), and the elevation data are referenced to the North American Vertical Datum of 1988 (NAVD88), GEOID12B.

On May 23, 2019, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jensen Beach, Florida. This dataset, Jensen_20190523.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and others, 2018), data were acquired by USGS scientists walking along cross-shore transect lines while carrying a survey backpack that was equipped with a Global Navigation Satellite System (GNSS) receiver and GNSS antenna. The horizontal position data are provided in the Universal Transverse Mercator (UTM) coordinate system, Zone 17 North (17N), referenced to the North American Datum of 1983 (NAD83), and the elevation data are referenced to the North American Vertical Datum of 1988 (NAVD88), GEOID12B.

On June 27, 2019, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jensen Beach, Florida. This dataset, Jensen_20190627.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and others, 2018), data were acquired by USGS scientists walking along cross-shore transect lines while carrying a survey backpack that was equipped with a Global Navigation Satellite System (GNSS) receiver and GNSS antenna. The horizontal position data are provided in the Universal Transverse Mercator (UTM) coordinate system, Zone 17 North (17N), referenced to the North American Datum of 1983 (NAD83), and the elevation data are referenced to the North American Vertical Datum of 1988 (NAVD88), GEOID12B.

On June 28, 2019, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jensen Beach, Florida. This dataset, Jensen_20190628.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and others, 2018), data were acquired by USGS scientists walking along cross-shore transect lines while carrying a survey backpack that was equipped with a Global Navigation Satellite System (GNSS) receiver and GNSS antenna. The horizontal position data are provided in the Universal Transverse Mercator (UTM) coordinate system, Zone 17 North (17N), referenced to the North American Datum of 1983 (NAD83), and the elevation data are referenced to the North American Vertical Datum of 1988 (NAVD88), GEOID12B.

On July 25, 2019, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jensen Beach, Florida. This dataset, Jensen_20190725.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and others, 2018), data were acquired by USGS scientists walking along cross-shore transect lines while carrying a survey backpack that was equipped with a Global Navigation Satellite System (GNSS) receiver and GNSS antenna. The horizontal position data are provided in the Universal Transverse Mercator (UTM) coordinate system, Zone 17 North (17N), referenced to the North American Datum of 1983 (NAD83), and the elevation data are referenced to the North American Vertical Datum of 1988 (NAVD88), GEOID12B.

On July 26, 2019, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jensen Beach, Florida. This dataset, Jensen_20190726.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and others, 2018), data were acquired by USGS scientists walking along cross-shore transect lines while carrying a survey backpack that was equipped with a Global Navigation Satellite System (GNSS) receiver and GNSS antenna. The horizontal position data are provided in the Universal Transverse Mercator (UTM) coordinate system, Zone 17 North (17N), referenced to the North American Datum of 1983 (NAD83), and the elevation data are referenced to the North American Vertical Datum of 1988 (NAVD88), GEOID12B.

On May 20, 2021, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Juno Beach, Florida. This dataset, Juno_20210520.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and others, 2018), data were acquired by USGS scientists walking along cross-shore transect lines while carrying a survey backpack that was equipped with a Global Navigation Satellite System (GNSS) receiver and GNSS antenna. The horizontal position data are provided in the Universal Transverse Mercator (UTM) coordinate system, Zone 17 North (17N), referenced to the North American Datum of 1983 (NAD83), and the elevation data are referenced to the North American Vertical Datum of 1988 (NAVD88), GEOID12B.

On May 21, 2021, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Juno Beach, Florida. This dataset, Juno_20210521.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and others, 2018), data were acquired by USGS scientists walking along cross-shore transect lines while carrying a survey backpack that was equipped with a Global Navigation Satellite System (GNSS) receiver and GNSS antenna. The horizontal position data are provided in the Universal Transverse Mercator (UTM) coordinate system, Zone 17 North (17N), referenced to the North American Datum of 1983 (NAD83), and the elevation data are referenced to the North American Vertical Datum of 1988 (NAVD88), GEOID12B.

On June 24, 2021, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Juno Beach, Florida. This dataset, Juno_20210624.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and others, 2018), data were acquired by USGS scientists walking along cross-shore transect lines while carrying a survey backpack that was equipped with a Global Navigation Satellite System (GNSS) receiver and GNSS antenna. The horizontal position data are provided in the Universal Transverse Mercator (UTM) coordinate system, Zone 17 North (17N), referenced to the North American Datum of 1983 (NAD83), and the elevation data are referenced to the North American Vertical Datum of 1988 (NAVD88), GEOID12B.

On June 25, 2021, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Juno Beach, Florida. This dataset, Juno_20210625.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and others, 2018), data were acquired by USGS scientists walking along cross-shore transect lines while carrying a survey backpack that was equipped with a Global Navigation Satellite System (GNSS) receiver and GNSS antenna. The horizontal position data are provided in the Universal Transverse Mercator (UTM) coordinate system, Zone 17 North (17N), referenced to the North American Datum of 1983 (NAD83), and the elevation data are referenced to the North American Vertical Datum of 1988 (NAVD88), GEOID12B.

On July 15, 2021, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Juno Beach, Florida. This dataset, Juno_20210715.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and others, 2018), data were acquired by USGS scientists walking along cross-shore transect lines while carrying a survey backpack that was equipped with a Global Navigation Satellite System (GNSS) receiver and GNSS antenna. The horizontal position data are provided in the Universal Transverse Mercator (UTM) coordinate system, Zone 17 North (17N), referenced to the North American Datum of 1983 (NAD83), and the elevation data are referenced to the North American Vertical Datum of 1988 (NAVD88), GEOID12B.

On July 16, 2021, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Juno Beach, Florida. This dataset, Juno_20210716.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and others, 2018), data were acquired by USGS scientists walking along cross-shore transect lines while carrying a survey backpack that was equipped with a Global Navigation Satellite System (GNSS) receiver and GNSS antenna. The horizontal position data are provided in the Universal Transverse Mercator (UTM) coordinate system, Zone 17 North (17N), referenced to the North American Datum of 1983 (NAD83), and the elevation data are referenced to the North American Vertical Datum of 1988 (NAVD88), GEOID12B.

On August 05, 2021, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Juno Beach, Florida. This dataset, Juno_20210805.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and others, 2018), data were acquired by USGS scientists walking along cross-shore transect lines while carrying a survey backpack that was equipped with a Global Navigation Satellite System (GNSS) receiver and GNSS antenna. The horizontal position data are provided in the Universal Transverse Mercator (UTM) coordinate system, Zone 17 North (17N), referenced to the North American Datum of 1983 (NAD83), and the elevation data are referenced to the North American Vertical Datum of 1988 (NAVD88), GEOID12B.

On August 06, 2021, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Juno Beach, Florida. This dataset, Juno_20210806.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and others, 2018), data were acquired by USGS scientists walking along cross-shore transect lines while carrying a survey backpack that was equipped with a Global Navigation Satellite System (GNSS) receiver and GNSS antenna. The horizontal position data are provided in the Universal Transverse Mercator (UTM) coordinate system, Zone 17 North (17N), referenced to the North American Datum of 1983 (NAD83), and the elevation data are referenced to the North American Vertical Datum of 1988 (NAVD88), GEOID12B.

On May 26, 2022, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Juno Beach, Florida. This dataset, Juno_20220526.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and others, 2018), data were acquired by USGS scientists walking along cross-shore transect lines while carrying a survey backpack that was equipped with a Global Navigation Satellite System (GNSS) receiver and GNSS antenna. The horizontal position data are provided in the Universal Transverse Mercator (UTM) coordinate system, Zone 17 North (17N), referenced to the North American Datum of 1983 (NAD83), and the elevation data are referenced to the North American Vertical Datum of 1988 (NAVD88), GEOID12B.

On May 27, 2022, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Juno Beach, Florida. This dataset, Juno_20220527.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and others, 2018), data were acquired by USGS scientists walking along cross-shore transect lines while carrying a survey backpack that was equipped with a Global Navigation Satellite System (GNSS) receiver and GNSS antenna. The horizontal position data are provided in the Universal Transverse Mercator (UTM) coordinate system, Zone 17 North (17N), referenced to the North American Datum of 1983 (NAD83), and the elevation data are referenced to the North American Vertical Datum of 1988 (NAVD88), GEOID12B.

On June 16, 2022, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Juno Beach, Florida. This dataset, Juno_20220616.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and others, 2018), data were acquired by USGS scientists walking along cross-shore transect lines while carrying a survey backpack that was equipped with a Global Navigation Satellite System (GNSS) receiver and GNSS antenna. The horizontal position data are provided in the Universal Transverse Mercator (UTM) coordinate system, Zone 17 North (17N), referenced to the North American Datum of 1983 (NAD83), and the elevation data are referenced to the North American Vertical Datum of 1988 (NAVD88), GEOID12B.

On June 17, 2022, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Juno Beach, Florida. This dataset, Juno_20220617.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and others, 2018), data were acquired by USGS scientists walking along cross-shore transect lines while carrying a survey backpack that was equipped with a Global Navigation Satellite System (GNSS) receiver and GNSS antenna. The horizontal position data are provided in the Universal Transverse Mercator (UTM) coordinate system, Zone 17 North (17N), referenced to the North American Datum of 1983 (NAD83), and the elevation data are referenced to the North American Vertical Datum of 1988 (NAVD88), GEOID12B.

On July 21, 2022, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Juno Beach, Florida. This dataset, Juno_20220721.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and others, 2018), data were acquired by USGS scientists walking along cross-shore transect lines while carrying a survey backpack that was equipped with a Global Navigation Satellite System (GNSS) receiver and GNSS antenna. The horizontal position data are provided in the Universal Transverse Mercator (UTM) coordinate system, Zone 17 North (17N), referenced to the North American Datum of 1983 (NAD83), and the elevation data are referenced to the North American Vertical Datum of 1988 (NAVD88), GEOID12B.

On July 22, 2022, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Juno Beach, Florida. This dataset, Juno_20220722.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and others, 2018), data were acquired by USGS scientists walking along cross-shore transect lines while carrying a survey backpack that was equipped with a Global Navigation Satellite System (GNSS) receiver and GNSS antenna. The horizontal position data are provided in the Universal Transverse Mercator (UTM) coordinate system, Zone 17 North (17N), referenced to the North American Datum of 1983 (NAD83), and the elevation data are referenced to the North American Vertical Datum of 1988 (NAVD88), GEOID12B.

On May 20, 2019, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jupiter Island, Florida. This dataset, Jupiter_20190520.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and others, 2018), data were acquired by USGS scientists walking along cross-shore transect lines while carrying a survey backpack that was equipped with a Global Navigation Satellite System (GNSS) receiver and GNSS antenna. The horizontal position data are provided in the Universal Transverse Mercator (UTM) coordinate system, Zone 17 North (17N), referenced to the North American Datum of 1983 (NAD83), and the elevation data are referenced to the North American Vertical Datum of 1988 (NAVD88), GEOID12B.

On May 21, 2019, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jupiter Island, Florida. This dataset, Jupiter_20190521.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and others, 2018), data were acquired by USGS scientists walking along cross-shore transect lines while carrying a survey backpack that was equipped with a Global Navigation Satellite System (GNSS) receiver and GNSS antenna. The horizontal position data are provided in the Universal Transverse Mercator (UTM) coordinate system, Zone 17 North (17N), referenced to the North American Datum of 1983 (NAD83), and the elevation data are referenced to the North American Vertical Datum of 1988 (NAVD88), GEOID12B.

On June 25, 2019, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jupiter Island, Florida. This dataset, Jupiter_20190625.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and others, 2018), data were acquired by USGS scientists walking along cross-shore transect lines while carrying a survey backpack that was equipped with a Global Navigation Satellite System (GNSS) receiver and GNSS antenna. The horizontal position data are provided in the Universal Transverse Mercator (UTM) coordinate system, Zone 17 North (17N), referenced to the North American Datum of 1983 (NAD83), and the elevation data are referenced to the North American Vertical Datum of 1988 (NAVD88), GEOID12B.

On June 26, 2019, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jupiter Island, Florida. This dataset, Jupiter_20190626.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and others, 2018), data were acquired by USGS scientists walking along cross-shore transect lines while carrying a survey backpack that was equipped with a Global Navigation Satellite System (GNSS) receiver and GNSS antenna. The horizontal position data are provided in the Universal Transverse Mercator (UTM) coordinate system, Zone 17 North (17N), referenced to the North American Datum of 1983 (NAD83), and the elevation data are referenced to the North American Vertical Datum of 1988 (NAVD88), GEOID12B.

On July 23, 2019, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jupiter Island, Florida. This dataset, Jupiter_20190723.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and others, 2018), data were acquired by USGS scientists walking along cross-shore transect lines while carrying a survey backpack that was equipped with a Global Navigation Satellite System (GNSS) receiver and GNSS antenna. The horizontal position data are provided in the Universal Transverse Mercator (UTM) coordinate system, Zone 17 North (17N), referenced to the North American Datum of 1983 (NAD83), and the elevation data are referenced to the North American Vertical Datum of 1988 (NAVD88), GEOID12B.

On July 24, 2019, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jupiter Island, Florida. This dataset, Jupiter_20190724.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and others, 2018), data were acquired by USGS scientists walking along cross-shore transect lines while carrying a survey backpack that was equipped with a Global Navigation Satellite System (GNSS) receiver and GNSS antenna. The horizontal position data are provided in the Universal Transverse Mercator (UTM) coordinate system, Zone 17 North (17N), referenced to the North American Datum of 1983 (NAD83), and the elevation data are referenced to the North American Vertical Datum of 1988 (NAVD88), GEOID12B.

On August 27, 2019, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jupiter Island, Florida. This dataset, Jupiter_20190827.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and others, 2018), data were acquired by USGS scientists walking along cross-shore transect lines while carrying a survey backpack that was equipped with a Global Navigation Satellite System (GNSS) receiver and GNSS antenna. The horizontal position data are provided in the Universal Transverse Mercator (UTM) coordinate system, Zone 17 North (17N), referenced to the North American Datum of 1983 (NAD83), and the elevation data are referenced to the North American Vertical Datum of 1988 (NAVD88), GEOID12B.

On August 28, 2019, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jupiter Island, Florida. This dataset, Jupiter_20190828.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and others, 2018), data were acquired by USGS scientists walking along cross-shore transect lines while carrying a survey backpack that was equipped with a Global Navigation Satellite System (GNSS) receiver and GNSS antenna. The horizontal position data are provided in the Universal Transverse Mercator (UTM) coordinate system, Zone 17 North (17N), referenced to the North American Datum of 1983 (NAD83), and the elevation data are referenced to the North American Vertical Datum of 1988 (NAVD88), GEOID12B.

On June 16, 2020, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jupiter Island, Florida. This dataset, Jupiter_20200616.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and others, 2018), data were acquired by USGS scientists walking along cross-shore transect lines while carrying a survey backpack that was equipped with a Global Navigation Satellite System (GNSS) receiver and GNSS antenna. The horizontal position data are provided in the Universal Transverse Mercator (UTM) coordinate system, Zone 17 North (17N), referenced to the North American Datum of 1983 (NAD83), and the elevation data are referenced to the North American Vertical Datum of 1988 (NAVD88), GEOID12B.

On June 17, 2020, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jupiter Island, Florida. This dataset, Jupiter_20200617.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and others, 2018), data were acquired by USGS scientists walking along cross-shore transect lines while carrying a survey backpack that was equipped with a Global Navigation Satellite System (GNSS) receiver and GNSS antenna. The horizontal position data are provided in the Universal Transverse Mercator (UTM) coordinate system, Zone 17 North (17N), referenced to the North American Datum of 1983 (NAD83), and the elevation data are referenced to the North American Vertical Datum of 1988 (NAVD88), GEOID12B.

On May 18, 2021, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jupiter Island, Florida. This dataset, Jupiter_20210518.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and others, 2018), data were acquired by USGS scientists walking along cross-shore transect lines while carrying a survey backpack that was equipped with a Global Navigation Satellite System (GNSS) receiver and GNSS antenna. The horizontal position data are provided in the Universal Transverse Mercator (UTM) coordinate system, Zone 17 North (17N), referenced to the North American Datum of 1983 (NAD83), and the elevation data are referenced to the North American Vertical Datum of 1988 (NAVD88), GEOID12B.

On May 19, 2021, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jupiter Island, Florida. This dataset, Jupiter_20210519.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and others, 2018), data were acquired by USGS scientists walking along cross-shore transect lines while carrying a survey backpack that was equipped with a Global Navigation Satellite System (GNSS) receiver and GNSS antenna. The horizontal position data are provided in the Universal Transverse Mercator (UTM) coordinate system, Zone 17 North (17N), referenced to the North American Datum of 1983 (NAD83), and the elevation data are referenced to the North American Vertical Datum of 1988 (NAVD88), GEOID12B.

On June 22, 2021, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jupiter Island, Florida. This dataset, Jupiter_20210622.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and others, 2018), data were acquired by USGS scientists walking along cross-shore transect lines while carrying a survey backpack that was equipped with a Global Navigation Satellite System (GNSS) receiver and GNSS antenna. The horizontal position data are provided in the Universal Transverse Mercator (UTM) coordinate system, Zone 17 North (17N), referenced to the North American Datum of 1983 (NAD83), and the elevation data are referenced to the North American Vertical Datum of 1988 (NAVD88), GEOID12B.

On June 23, 2021, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jupiter Island, Florida. This dataset, Jupiter_20210623.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and others, 2018), data were acquired by USGS scientists walking along cross-shore transect lines while carrying a survey backpack that was equipped with a Global Navigation Satellite System (GNSS) receiver and GNSS antenna. The horizontal position data are provided in the Universal Transverse Mercator (UTM) coordinate system, Zone 17 North (17N), referenced to the North American Datum of 1983 (NAD83), and the elevation data are referenced to the North American Vertical Datum of 1988 (NAVD88), GEOID12B.

On July 13, 2021, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jupiter Island, Florida. This dataset, Jupiter_20210713.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and others, 2018), data were acquired by USGS scientists walking along cross-shore transect lines while carrying a survey backpack that was equipped with a Global Navigation Satellite System (GNSS) receiver and GNSS antenna. The horizontal position data are provided in the Universal Transverse Mercator (UTM) coordinate system, Zone 17 North (17N), referenced to the North American Datum of 1983 (NAD83), and the elevation data are referenced to the North American Vertical Datum of 1988 (NAVD88), GEOID12B.

On July 14, 2021, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jupiter Island, Florida. This dataset, Jupiter_20210714.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and others, 2018), data were acquired by USGS scientists walking along cross-shore transect lines while carrying a survey backpack that was equipped with a Global Navigation Satellite System (GNSS) receiver and GNSS antenna. The horizontal position data are provided in the Universal Transverse Mercator (UTM) coordinate system, Zone 17 North (17N), referenced to the North American Datum of 1983 (NAD83), and the elevation data are referenced to the North American Vertical Datum of 1988 (NAVD88), GEOID12B.

On August 03, 2021, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jupiter Island, Florida. This dataset, Jupiter_20210803.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and others, 2018), data were acquired by USGS scientists walking along cross-shore transect lines while carrying a survey backpack that was equipped with a Global Navigation Satellite System (GNSS) receiver and GNSS antenna. The horizontal position data are provided in the Universal Transverse Mercator (UTM) coordinate system, Zone 17 North (17N), referenced to the North American Datum of 1983 (NAD83), and the elevation data are referenced to the North American Vertical Datum of 1988 (NAVD88), GEOID12B.

On August 04, 2021, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jupiter Island, Florida. This dataset, Jupiter_20210804.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and others, 2018), data were acquired by USGS scientists walking along cross-shore transect lines while carrying a survey backpack that was equipped with a Global Navigation Satellite System (GNSS) receiver and GNSS antenna. The horizontal position data are provided in the Universal Transverse Mercator (UTM) coordinate system, Zone 17 North (17N), referenced to the North American Datum of 1983 (NAD83), and the elevation data are referenced to the North American Vertical Datum of 1988 (NAVD88), GEOID12B.

On May 24, 2022, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jupiter Island, Florida. This dataset, Jupiter_20220524.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and others, 2018), data were acquired by USGS scientists walking along cross-shore transect lines while carrying a survey backpack that was equipped with a Global Navigation Satellite System (GNSS) receiver and GNSS antenna. The horizontal position data are provided in the Universal Transverse Mercator (UTM) coordinate system, Zone 17 North (17N), referenced to the North American Datum of 1983 (NAD83), and the elevation data are referenced to the North American Vertical Datum of 1988 (NAVD88), GEOID12B.

On May 25, 2022, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jupiter Island, Florida. This dataset, Jupiter_20220525.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and others, 2018), data were acquired by USGS scientists walking along cross-shore transect lines while carrying a survey backpack that was equipped with a Global Navigation Satellite System (GNSS) receiver and GNSS antenna. The horizontal position data are provided in the Universal Transverse Mercator (UTM) coordinate system, Zone 17 North (17N), referenced to the North American Datum of 1983 (NAD83), and the elevation data are referenced to the North American Vertical Datum of 1988 (NAVD88), GEOID12B.

On June 14, 2022, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jupiter Island, Florida. This dataset, Jupiter_20220614.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and others, 2018), data were acquired by USGS scientists walking along cross-shore transect lines while carrying a survey backpack that was equipped with a Global Navigation Satellite System (GNSS) receiver and GNSS antenna. The horizontal position data are provided in the Universal Transverse Mercator (UTM) coordinate system, Zone 17 North (17N), referenced to the North American Datum of 1983 (NAD83), and the elevation data are referenced to the North American Vertical Datum of 1988 (NAVD88), GEOID12B.

On June 15, 2022, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jupiter Island, Florida. This dataset, Jupiter_20220615.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and others, 2018), data were acquired by USGS scientists walking along cross-shore transect lines while carrying a survey backpack that was equipped with a Global Navigation Satellite System (GNSS) receiver and GNSS antenna. The horizontal position data are provided in the Universal Transverse Mercator (UTM) coordinate system, Zone 17 North (17N), referenced to the North American Datum of 1983 (NAD83), and the elevation data are referenced to the North American Vertical Datum of 1988 (NAVD88), GEOID12B.

On July 19, 2022, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jupiter Island, Florida. This dataset, Jupiter_20220719.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and others, 2018), data were acquired by USGS scientists walking along cross-shore transect lines while carrying a survey backpack that was equipped with a Global Navigation Satellite System (GNSS) receiver and GNSS antenna. The horizontal position data are provided in the Universal Transverse Mercator (UTM) coordinate system, Zone 17 North (17N), referenced to the North American Datum of 1983 (NAD83), and the elevation data are referenced to the North American Vertical Datum of 1988 (NAVD88), GEOID12B.

On July 20, 2022, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jupiter Island, Florida. This dataset, Jupiter_20220720.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and others, 2018), data were acquired by USGS scientists walking along cross-shore transect lines while carrying a survey backpack that was equipped with a Global Navigation Satellite System (GNSS) receiver and GNSS antenna. The horizontal position data are provided in the Universal Transverse Mercator (UTM) coordinate system, Zone 17 North (17N), referenced to the North American Datum of 1983 (NAD83), and the elevation data are referenced to the North American Vertical Datum of 1988 (NAVD88), GEOID12B.

On May 09, 2018, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Melbourne Beach, Florida. This dataset, Melbourne_20180509.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and others, 2018), data were acquired by USGS scientists walking along cross-shore transect lines while carrying a survey backpack that was equipped with a Global Navigation Satellite System (GNSS) receiver and GNSS antenna. The horizontal position data are provided in the Universal Transverse Mercator (UTM) coordinate system, Zone 17 North (17N), referenced to the North American Datum of 1983 (NAD83), and the elevation data are referenced to the North American Vertical Datum of 1988 (NAVD88), GEOID12B.

On June 13, 2018, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Melbourne Beach, Florida. This dataset, Melbourne_20180613.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and others, 2018), data were acquired by USGS scientists walking along cross-shore transect lines while carrying a survey backpack that was equipped with a Global Navigation Satellite System (GNSS) receiver and GNSS antenna. The horizontal position data are provided in the Universal Transverse Mercator (UTM) coordinate system, Zone 17 North (17N), referenced to the North American Datum of 1983 (NAD83), and the elevation data are referenced to the North American Vertical Datum of 1988 (NAVD88), GEOID12B.

On July 18, 2018, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Melbourne Beach, Florida. This dataset, Melbourne_20180718.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and others, 2018), data were acquired by USGS scientists walking along cross-shore transect lines while carrying a survey backpack that was equipped with a Global Navigation Satellite System (GNSS) receiver and GNSS antenna. The horizontal position data are provided in the Universal Transverse Mercator (UTM) coordinate system, Zone 17 North (17N), referenced to the North American Datum of 1983 (NAD83), and the elevation data are referenced to the North American Vertical Datum of 1988 (NAVD88), GEOID12B.

On August 08, 2018, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Melbourne Beach, Florida. This dataset, Melbourne_20180808.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and others, 2018), data were acquired by USGS scientists walking along cross-shore transect lines while carrying a survey backpack that was equipped with a Global Navigation Satellite System (GNSS) receiver and GNSS antenna. The horizontal position data are provided in the Universal Transverse Mercator (UTM) coordinate system, Zone 17 North (17N), referenced to the North American Datum of 1983 (NAD83), and the elevation data are referenced to the North American Vertical Datum of 1988 (NAVD88), GEOID12B.

On May 30, 2019, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Melbourne Beach, Florida. This dataset, Melbourne_20190530.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and others, 2018), data were acquired by USGS scientists walking along cross-shore transect lines while carrying a survey backpack that was equipped with a Global Navigation Satellite System (GNSS) receiver and GNSS antenna. The horizontal position data are provided in the Universal Transverse Mercator (UTM) coordinate system, Zone 17 North (17N), referenced to the North American Datum of 1983 (NAD83), and the elevation data are referenced to the North American Vertical Datum of 1988 (NAVD88), GEOID12B.

On May 31, 2019, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Melbourne Beach, Florida. This dataset, Melbourne_20190531.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and others, 2018), data were acquired by USGS scientists walking along cross-shore transect lines while carrying a survey backpack that was equipped with a Global Navigation Satellite System (GNSS) receiver and GNSS antenna. The horizontal position data are provided in the Universal Transverse Mercator (UTM) coordinate system, Zone 17 North (17N), referenced to the North American Datum of 1983 (NAD83), and the elevation data are referenced to the North American Vertical Datum of 1988 (NAVD88), GEOID12B.

On June 18, 2019, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Melbourne Beach, Florida. This dataset, Melbourne_20190618.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and others, 2018), data were acquired by USGS scientists walking along cross-shore transect lines while carrying a survey backpack that was equipped with a Global Navigation Satellite System (GNSS) receiver and GNSS antenna. The horizontal position data are provided in the Universal Transverse Mercator (UTM) coordinate system, Zone 17 North (17N), referenced to the North American Datum of 1983 (NAD83), and the elevation data are referenced to the North American Vertical Datum of 1988 (NAVD88), GEOID12B.

On June 19, 2019, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Melbourne Beach, Florida. This dataset, Melbourne_20190619.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and others, 2018), data were acquired by USGS scientists walking along cross-shore transect lines while carrying a survey backpack that was equipped with a Global Navigation Satellite System (GNSS) receiver and GNSS antenna. The horizontal position data are provided in the Universal Transverse Mercator (UTM) coordinate system, Zone 17 North (17N), referenced to the North American Datum of 1983 (NAD83), and the elevation data are referenced to the North American Vertical Datum of 1988 (NAVD88), GEOID12B.

On July 16, 2019, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Melbourne Beach, Florida. This dataset, Melbourne_20190716.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and others, 2018), data were acquired by USGS scientists walking along cross-shore transect lines while carrying a survey backpack that was equipped with a Global Navigation Satellite System (GNSS) receiver and GNSS antenna. The horizontal position data are provided in the Universal Transverse Mercator (UTM) coordinate system, Zone 17 North (17N), referenced to the North American Datum of 1983 (NAD83), and the elevation data are referenced to the North American Vertical Datum of 1988 (NAVD88), GEOID12B.

On July 17, 2019, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Melbourne Beach, Florida. This dataset, Melbourne_20190717.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and others, 2018), data were acquired by USGS scientists walking along cross-shore transect lines while carrying a survey backpack that was equipped with a Global Navigation Satellite System (GNSS) receiver and GNSS antenna. The horizontal position data are provided in the Universal Transverse Mercator (UTM) coordinate system, Zone 17 North (17N), referenced to the North American Datum of 1983 (NAD83), and the elevation data are referenced to the North American Vertical Datum of 1988 (NAVD88), GEOID12B.

On August 20, 2019, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Melbourne Beach, Florida. This dataset, Melbourne_20190820.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and others, 2018), data were acquired by USGS scientists walking along cross-shore transect lines while carrying a survey backpack that was equipped with a Global Navigation Satellite System (GNSS) receiver and GNSS antenna. The horizontal position data are provided in the Universal Transverse Mercator (UTM) coordinate system, Zone 17 North (17N), referenced to the North American Datum of 1983 (NAD83), and the elevation data are referenced to the North American Vertical Datum of 1988 (NAVD88), GEOID12B.

On August 21, 2019, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Melbourne Beach, Florida. This dataset, Melbourne_20190821.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and others, 2018), data were acquired by USGS scientists walking along cross-shore transect lines while carrying a survey backpack that was equipped with a Global Navigation Satellite System (GNSS) receiver and GNSS antenna. The horizontal position data are provided in the Universal Transverse Mercator (UTM) coordinate system, Zone 17 North (17N), referenced to the North American Datum of 1983 (NAD83), and the elevation data are referenced to the North American Vertical Datum of 1988 (NAVD88), GEOID12B.

On September 10, 2019, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Melbourne Beach, Florida. This dataset, Melbourne_20190910.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and others, 2018), data were acquired by USGS scientists walking along cross-shore transect lines while carrying a survey backpack that was equipped with a Global Navigation Satellite System (GNSS) receiver and GNSS antenna. The horizontal position data are provided in the Universal Transverse Mercator (UTM) coordinate system, Zone 17 North (17N), referenced to the North American Datum of 1983 (NAD83), and the elevation data are referenced to the North American Vertical Datum of 1988 (NAVD88), GEOID12B.

On September 11, 2019, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Melbourne Beach, Florida. This dataset, Melbourne_20190911.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and others, 2018), data were acquired by USGS scientists walking along cross-shore transect lines while carrying a survey backpack that was equipped with a Global Navigation Satellite System (GNSS) receiver and GNSS antenna. The horizontal position data are provided in the Universal Transverse Mercator (UTM) coordinate system, Zone 17 North (17N), referenced to the North American Datum of 1983 (NAD83), and the elevation data are referenced to the North American Vertical Datum of 1988 (NAVD88), GEOID12B.

On June 25, 2020, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Melbourne Beach, Florida. This dataset, Melbourne_20200625.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and others, 2018), data were acquired by USGS scientists walking along cross-shore transect lines while carrying a survey backpack that was equipped with a Global Navigation Satellite System (GNSS) receiver and GNSS antenna. The horizontal position data are provided in the Universal Transverse Mercator (UTM) coordinate system, Zone 17 North (17N), referenced to the North American Datum of 1983 (NAD83), and the elevation data are referenced to the North American Vertical Datum of 1988 (NAVD88), GEOID12B.

On June 26, 2020, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Melbourne Beach, Florida. This dataset, Melbourne_20200626.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and others, 2018), data were acquired by USGS scientists walking along cross-shore transect lines while carrying a survey backpack that was equipped with a Global Navigation Satellite System (GNSS) receiver and GNSS antenna. The horizontal position data are provided in the Universal Transverse Mercator (UTM) coordinate system, Zone 17 North (17N), referenced to the North American Datum of 1983 (NAD83), and the elevation data are referenced to the North American Vertical Datum of 1988 (NAVD88), GEOID12B.

On May 25, 2021, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Melbourne Beach, Florida. This dataset, Melbourne_20210525.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and others, 2018), data were acquired by USGS scientists walking along cross-shore transect lines while carrying a survey backpack that was equipped with a Global Navigation Satellite System (GNSS) receiver and GNSS antenna. The horizontal position data are provided in the Universal Transverse Mercator (UTM) coordinate system, Zone 17 North (17N), referenced to the North American Datum of 1983 (NAD83), and the elevation data are referenced to the North American Vertical Datum of 1988 (NAVD88), GEOID12B.

On May 26, 2021, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Melbourne Beach, Florida. This dataset, Melbourne_20210526.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and others, 2018), data were acquired by USGS scientists walking along cross-shore transect lines while carrying a survey backpack that was equipped with a Global Navigation Satellite System (GNSS) receiver and GNSS antenna. The horizontal position data are provided in the Universal Transverse Mercator (UTM) coordinate system, Zone 17 North (17N), referenced to the North American Datum of 1983 (NAD83), and the elevation data are referenced to the North American Vertical Datum of 1988 (NAVD88), GEOID12B.

On June 15, 2021, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Melbourne Beach, Florida. This dataset, Melbourne_20210615.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and others, 2018), data were acquired by USGS scientists walking along cross-shore transect lines while carrying a survey backpack that was equipped with a Global Navigation Satellite System (GNSS) receiver and GNSS antenna. The horizontal position data are provided in the Universal Transverse Mercator (UTM) coordinate system, Zone 17 North (17N), referenced to the North American Datum of 1983 (NAD83), and the elevation data are referenced to the North American Vertical Datum of 1988 (NAVD88), GEOID12B.

On June 16, 2021, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Melbourne Beach, Florida. This dataset, Melbourne_20210616.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and others, 2018), data were acquired by USGS scientists walking along cross-shore transect lines while carrying a survey backpack that was equipped with a Global Navigation Satellite System (GNSS) receiver and GNSS antenna. The horizontal position data are provided in the Universal Transverse Mercator (UTM) coordinate system, Zone 17 North (17N), referenced to the North American Datum of 1983 (NAD83), and the elevation data are referenced to the North American Vertical Datum of 1988 (NAVD88), GEOID12B.

On July 20, 2021, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Melbourne Beach, Florida. This dataset, Melbourne_20210720.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and others, 2018), data were acquired by USGS scientists walking along cross-shore transect lines while carrying a survey backpack that was equipped with a Global Navigation Satellite System (GNSS) receiver and GNSS antenna. The horizontal position data are provided in the Universal Transverse Mercator (UTM) coordinate system, Zone 17 North (17N), referenced to the North American Datum of 1983 (NAD83), and the elevation data are referenced to the North American Vertical Datum of 1988 (NAVD88), GEOID12B.

On July 21, 2021, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Melbourne Beach, Florida. This dataset, Melbourne_20210721.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and others, 2018), data were acquired by USGS scientists walking along cross-shore transect lines while carrying a survey backpack that was equipped with a Global Navigation Satellite System (GNSS) receiver and GNSS antenna. The horizontal position data are provided in the Universal Transverse Mercator (UTM) coordinate system, Zone 17 North (17N), referenced to the North American Datum of 1983 (NAD83), and the elevation data are referenced to the North American Vertical Datum of 1988 (NAVD88), GEOID12B.

On August 10, 2021, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Melbourne Beach, Florida. This dataset, Melbourne_20210810.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and others, 2018), data were acquired by USGS scientists walking along cross-shore transect lines while carrying a survey backpack that was equipped with a Global Navigation Satellite System (GNSS) receiver and GNSS antenna. The horizontal position data are provided in the Universal Transverse Mercator (UTM) coordinate system, Zone 17 North (17N), referenced to the North American Datum of 1983 (NAD83), and the elevation data are referenced to the North American Vertical Datum of 1988 (NAVD88), GEOID12B.

On August 11, 2021, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Melbourne Beach, Florida. This dataset, Melbourne_20210811.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and others, 2018), data were acquired by USGS scientists walking along cross-shore transect lines while carrying a survey backpack that was equipped with a Global Navigation Satellite System (GNSS) receiver and GNSS antenna. The horizontal position data are provided in the Universal Transverse Mercator (UTM) coordinate system, Zone 17 North (17N), referenced to the North American Datum of 1983 (NAD83), and the elevation data are referenced to the North American Vertical Datum of 1988 (NAVD88), GEOID12B.

On September 08, 2021, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Melbourne Beach, Florida. This dataset, Melbourne_20210908.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and others, 2018), data were acquired by USGS scientists walking along cross-shore transect lines while carrying a survey backpack that was equipped with a Global Navigation Satellite System (GNSS) receiver and GNSS antenna. The horizontal position data are provided in the Universal Transverse Mercator (UTM) coordinate system, Zone 17 North (17N), referenced to the North American Datum of 1983 (NAD83), and the elevation data are referenced to the North American Vertical Datum of 1988 (NAVD88), GEOID12B.

On September 09, 2021, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Melbourne Beach, Florida. This dataset, Melbourne_20210909.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and others, 2018), data were acquired by USGS scientists walking along cross-shore transect lines while carrying a survey backpack that was equipped with a Global Navigation Satellite System (GNSS) receiver and GNSS antenna. The horizontal position data are provided in the Universal Transverse Mercator (UTM) coordinate system, Zone 17 North (17N), referenced to the North American Datum of 1983 (NAD83), and the elevation data are referenced to the North American Vertical Datum of 1988 (NAVD88), GEOID12B.

On May 19, 2022, surveys were conducted on ‘high-density’ sea turtle nesting areas located on South Hutchinson Beach, Florida. This dataset, SouthHutchinson_20220519.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and others, 2018), data were acquired by USGS scientists walking along cross-shore transect lines while carrying a survey backpack that was equipped with a Global Navigation Satellite System (GNSS) receiver and GNSS antenna. The horizontal position data are provided in the Universal Transverse Mercator (UTM) coordinate system, Zone 17 North (17N), referenced to the North American Datum of 1983 (NAD83), and the elevation data are referenced to the North American Vertical Datum of 1988 (NAVD88), GEOID12B.

On May 20, 2022, surveys were conducted on ‘high-density’ sea turtle nesting areas located on South Hutchinson Beach, Florida. This dataset, SouthHutchinson_20220520.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and others, 2018), data were acquired by USGS scientists walking along cross-shore transect lines while carrying a survey backpack that was equipped with a Global Navigation Satellite System (GNSS) receiver and GNSS antenna. The horizontal position data are provided in the Universal Transverse Mercator (UTM) coordinate system, Zone 17 North (17N), referenced to the North American Datum of 1983 (NAD83), and the elevation data are referenced to the North American Vertical Datum of 1988 (NAVD88), GEOID12B.

On June 22, 2022, surveys were conducted on ‘high-density’ sea turtle nesting areas located on South Hutchinson Beach, Florida. This dataset, SouthHutchinson_20220622.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and others, 2018), data were acquired by USGS scientists walking along cross-shore transect lines while carrying a survey backpack that was equipped with a Global Navigation Satellite System (GNSS) receiver and GNSS antenna. The horizontal position data are provided in the Universal Transverse Mercator (UTM) coordinate system, Zone 17 North (17N), referenced to the North American Datum of 1983 (NAD83), and the elevation data are referenced to the North American Vertical Datum of 1988 (NAVD88), GEOID12B.

On June 23, 2022, surveys were conducted on ‘high-density’ sea turtle nesting areas located on South Hutchinson Beach, Florida. This dataset, SouthHutchinson_20220623.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and others, 2018), data were acquired by USGS scientists walking along cross-shore transect lines while carrying a survey backpack that was equipped with a Global Navigation Satellite System (GNSS) receiver and GNSS antenna. The horizontal position data are provided in the Universal Transverse Mercator (UTM) coordinate system, Zone 17 North (17N), referenced to the North American Datum of 1983 (NAD83), and the elevation data are referenced to the North American Vertical Datum of 1988 (NAVD88), GEOID12B.

On June 24, 2022, surveys were conducted on ‘high-density’ sea turtle nesting areas located on South Hutchinson Beach, Florida. This dataset, SouthHutchinson_20220624.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and others, 2018), data were acquired by USGS scientists walking along cross-shore transect lines while carrying a survey backpack that was equipped with a Global Navigation Satellite System (GNSS) receiver and GNSS antenna. The horizontal position data are provided in the Universal Transverse Mercator (UTM) coordinate system, Zone 17 North (17N), referenced to the North American Datum of 1983 (NAD83), and the elevation data are referenced to the North American Vertical Datum of 1988 (NAVD88), GEOID12B.

On July 12, 2022, surveys were conducted on ‘high-density’ sea turtle nesting areas located on South Hutchinson Beach, Florida. This dataset, SouthHutchinson_20220712.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and others, 2018), data were acquired by USGS scientists walking along cross-shore transect lines while carrying a survey backpack that was equipped with a Global Navigation Satellite System (GNSS) receiver and GNSS antenna. The horizontal position data are provided in the Universal Transverse Mercator (UTM) coordinate system, Zone 17 North (17N), referenced to the North American Datum of 1983 (NAD83), and the elevation data are referenced to the North American Vertical Datum of 1988 (NAVD88), GEOID12B.

On July 13, 2022, surveys were conducted on ‘high-density’ sea turtle nesting areas located on South Hutchinson Beach, Florida. This dataset, SouthHutchinson_20220713.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and others, 2018), data were acquired by USGS scientists walking along cross-shore transect lines while carrying a survey backpack that was equipped with a Global Navigation Satellite System (GNSS) receiver and GNSS antenna. The horizontal position data are provided in the Universal Transverse Mercator (UTM) coordinate system, Zone 17 North (17N), referenced to the North American Datum of 1983 (NAD83), and the elevation data are referenced to the North American Vertical Datum of 1988 (NAVD88), GEOID12B.

On August 02, 2022, surveys were conducted on ‘high-density’ sea turtle nesting areas located on South Hutchinson Beach, Florida. This dataset, SouthHutchinson_20220802.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and others, 2018), data were acquired by USGS scientists walking along cross-shore transect lines while carrying a survey backpack that was equipped with a Global Navigation Satellite System (GNSS) receiver and GNSS antenna. The horizontal position data are provided in the Universal Transverse Mercator (UTM) coordinate system, Zone 17 North (17N), referenced to the North American Datum of 1983 (NAD83), and the elevation data are referenced to the North American Vertical Datum of 1988 (NAVD88), GEOID12B.

On August 03, 2022, surveys were conducted on ‘high-density’ sea turtle nesting areas located on South Hutchinson Beach, Florida. This dataset, SouthHutchinson_20220803.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and others, 2018), data were acquired by USGS scientists walking along cross-shore transect lines while carrying a survey backpack that was equipped with a Global Navigation Satellite System (GNSS) receiver and GNSS antenna. The horizontal position data are provided in the Universal Transverse Mercator (UTM) coordinate system, Zone 17 North (17N), referenced to the North American Datum of 1983 (NAD83), and the elevation data are referenced to the North American Vertical Datum of 1988 (NAVD88), GEOID12B.

On September 01, 2022, surveys were conducted on ‘high-density’ sea turtle nesting areas located on South Hutchinson Beach, Florida. This dataset, SouthHutchinson_20220901.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and others, 2018), data were acquired by USGS scientists walking along cross-shore transect lines while carrying a survey backpack that was equipped with a Global Navigation Satellite System (GNSS) receiver and GNSS antenna. The horizontal position data are provided in the Universal Transverse Mercator (UTM) coordinate system, Zone 17 North (17N), referenced to the North American Datum of 1983 (NAD83), and the elevation data are referenced to the North American Vertical Datum of 1988 (NAVD88), GEOID12B.

On May 08, 2018, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jensen Beach, Florida. This dataset, Jensen_20180508.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and others, 2018), data were acquired by USGS scientists walking along cross-shore transect lines while carrying a survey backpack that was equipped with a Global Navigation Satellite System (GNSS) receiver and GNSS antenna. The horizontal position data are provided in the Universal Transverse Mercator (UTM) coordinate system, Zone 17 North (17N), referenced to the North American Datum of 1983 (NAD83), and the elevation data are referenced to the North American Vertical Datum of 1988 (NAVD88), GEOID12B.

On June 12, 2018, surveys were conducted on ‘high-density’ sea turtle nesting areas located on Jensen Beach, Florida. This dataset, Jensen_20180612.zip, was collected and processed by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and includes sea turtle nesting decision point locations (.csv) and cross-shore beach profiles (.xyz) at those locations. Utilizing previously published methods for collecting beach profile data (Henderson and others, 2016; Brown and others, 2018), data were acquired by USGS scientists walking along cross-shore transect lines while carrying a survey backpack that was equipped with a Global Navigation Satellite System (GNSS) receiver and GNSS antenna. The horizontal position data are provided in the Universal Transverse Mercator (UTM) coordinate system, Zone 17 North (17N), referenced to the North American Datum of 1983 (NAD83), and the elevation data are referenced to the North American Vertical Datum of 1988 (NAVD88), GEOID12B.

Grain size distribution, bulk density, and percent carbon are reported for sediment push cores from two flooded agricultural tracts, Little Holland Tract and Liberty Island, in the Sacramento-San Joaquin Delta, California. Push core samples were collected from 14 sites by the U.S Geological Survey in August, 2014. Each core was analyzed at multiple depths to investigate variations in particle sizes with depth below the sediment surface. The same sites were sampled again in 2016 (https://www.sciencebase.gov/catalog/item/5a73aa70e4b0a9a2e9e172de). These data provide insight into the variation of particle size distributions in space, bed depth, and time.

Grain size distribution, bulk density, and percent carbon are reported for sediment samples from two flooded agricultural tracts, Little Holland Tract and Liberty Island, in the Sacramento-San Joaquin Delta, California. Samples were repeatedly collected at 8 sites using a Ponar grab or push core samplers during 19 visits to the study area from 2015 to 2019. The long-term time series data collection stations (sites LWA, HVB, HWC, and LVB) were sampled on almost every field survey, and the remaining sites were sampled 6 or times or fewer, some only once. All samples were analyzed for grain size distribution, and some were analyzed for bulk density and/or percent carbon. These data provide insight into how particle size distributions varied spatially and temporally.

Grain size distribution, bulk density, and percent carbon are reported for sediment push cores from two flooded agricultural tracts, Little Holland Tract and Liberty Island, in the Sacramento-San Joaquin Delta, California. Push core samples were collected from 17 sites by the U.S. Geological Survey in June 2016. Each core was analyzed at multiple depths to investigate variations in particle sizes with depth below the sediment surface. The same sites were sampled previously in 2014 (https://www.sciencebase.gov/catalog/item/5a73a58fe4b0a9a2e9e172cf). These data provide insight into the variation of particle size distributions in space, bed depth, and time.

Processed Reson 7111 multibeam line files from a May 2015 survey offshore Cross Sound, southeast Alaska. Data were collected and processed by the U.S. Geological Survey (USGS) Pacific Coastal and Marine Science Center (PCMSC) with fieldwork activity number 2015-629-FA. Data are provided as generic sensor format (GSF) line files.

Along-shore surface-based 2D electrical resistivity tomography (ERT) surveys were collected in the nearshore region of Ofu, American Samoa.

The data sets provided here consist of 2D XBeach model files and sample input files used for Coastal Storm Modeling System (CoSMoS) simulations of flood and erosion hazards in Elim, Alaska. The models produce outputs for a suite of hazard products (see products in this release), such as flood depths, flood extents, and erosion and sedimentation. In this release, example forcing files for conditions with a 100-year return period coastal storm and a sea level rise of 0.5 m are provided, in addition to all other files needed to run the model in surfbeat and nonhydrostatic modes.

Erosion and sedimentation maps resulting from compound coastal hazards —specifically sea-level rise (SLR) and projected coastal storms-are provided for Elim, Alaska. These products are consistent with other data in this release (for example, flood extent and velocity hazards; Erikson and others, 2025), supporting integrated coastal hazard assessments for Alaskan communities. The data are provided as gridded maps (GeoTIFFs) for 30 storm and SLR combinations (SLR scenarios 0, 0.5, 1.0, 1.5, 2.0, and 3.0 meters combined with 1-year, 10-year, 20-year, 50-year, and 100-year storm return periods).

Flood extents, as well as the upper and lower uncertainty bounds of flood extents, from compound coastal hazards—specifically sea-level rise (SLR) and projected coastal storms—are provided for Elim, Alaska. These products are consistent with other data in this release (for example, flood depths and event-driven erosion; Erikson and others, 2025), supporting integrated coastal hazard assessments for Alaskan communities. The data are provided as shapefiles for 36 storm and SLR combinations (SLR scenarios 0, 0.5, 1.0, 1.5, 2.0, and 3.0 meters combined with 1-year, 10-year, 20-year, 50-year, and 100-year storm return periods, as well as the background, no storm, conditions).

Velocity hazards (maximum depth times velocity) from compound coastal hazards—specifically sea-level rise (SLR) and projected coastal storms—are provided for Elim, Alaska. Velocity hazards are a measure of the velocity severity. Categories range from 0 (low hazard) to 4 (extreme hazard) following guidance from the Federal Emergency Management Agency (2020). These products are consistent with other data in this release (for example, flood extent and event-driven erosion; Erikson and others, 2025), supporting integrated coastal hazard assessments for Alaskan communities. The data are provided as gridded maps (GeoTIFFs) for 30 storm and SLR combinations (SLR scenarios 0, 0.5, 1.0, 1.5, 2.0, and 3.0 meters combined with 1-year, 10-year, 20-year, 50-year, and 100-year storm return periods).

Water elevations from compound coastal hazards—specifically sea-level rise (SLR) and projected coastal storms—are provided for Elim, Alaska. These products are consistent with other data in this release (for example, flood extent and event-driven erosion; Erikson and others, 2025), supporting integrated coastal hazard assessments for Alaskan communities. The data are provided as gridded maps (GeoTIFFs) for 36 storm and SLR combinations (SLR scenarios 0, 0.5, 1.0, 1.5, 2.0, and 3.0 meters combined with 1-year, 10-year, 20-year, 50-year, and 100-year storm return periods, as well as the background, no storm, conditions).

Wave hazards (wave heights) from compound coastal hazards—specifically sea-level rise (SLR) and projected coastal storms—are provided for Elim, Alaska. These products are consistent with other data in this release (for example, flood extent and event-driven erosion; Erikson and others, 2025), supporting integrated coastal hazard assessments for Alaskan communities. The data are provided as gridded maps (GeoTIFFs) for 30 storm and SLR combinations (SLR scenarios 0, 0.5, 1.0, 1.5, 2.0, and 3.0 meters combined with 1-year, 10-year, 20-year, 50-year, and 100-year storm return periods).

The data sets provided here consist of 2D XBeach model files and sample input files used for Coastal Storm Modeling System (CoSMoS) simulations of flood and erosion hazards in Unalakleet, Alaska. The models produce outputs for a suite of hazard products (see products in this release), such as flood depths, flood extents, and erosion and sedimentation. In this release, example forcing files for conditions with a 100-year return period coastal storm and a sea level rise of 0.5 m are provided, in addition to all other files needed to run the model in surfbeat and nonhydrostatic modes.

Erosion and sedimentation maps resulting from compound coastal hazards —specifically sea-level rise (SLR) and projected coastal storms-are provided for Unalakleet, Alaska. These products are consistent with other data in this release (for example, flood extent and velocity hazards; Erikson and others, 2025), supporting integrated coastal hazard assessments for Alaskan communities. The data are provided as gridded maps (GeoTIFFs) for 30 storm and SLR combinations (SLR scenarios 0, 0.5, 1.0, 1.5, 2.0, and 3.0 meters combined with 1-year, 10-year, 20-year, 50-year, and 100-year storm return periods).

Flood depths from compound coastal hazards—specifically sea-level rise (SLR) and projected coastal storms—are provided for Unalakleet, Alaska. The flood depth products are consistent with other data in this release (for example, flood extent and event-driven erosion; Erikson and others, 2025), supporting integrated coastal hazard assessments for Alaskan communities. The data are provided as gridded maps (GeoTIFFs) for 36 storm and SLR combinations (SLR scenarios 0, 0.5, 1.0, 1.5, 2.0, and 3.0 meters combined with 1-year, 10-year, 20-year, 50-year, and 100-year storm return periods, as well as the background, no storm, conditions). As an additional product, these data are also provided only for areas landward of the present-day shoreline to make the impact of each scenario more visible. These are available for all mentioned storm and SLR combinations but the background condition with no SLR (since this scenario does not exceed the present-day shoreline).

Flood extents, as well as the upper and lower uncertainty bounds of flood extents, from compound coastal hazards—specifically sea-level rise (SLR) and projected coastal storms—are provided for Unalakleet, Alaska. These products are consistent with other data in this release (for example, flood depths and event-driven erosion; Erikson and others, 2025), supporting integrated coastal hazard assessments for Alaskan communities. The data are provided as shapefiles for 36 storm and SLR combinations (SLR scenarios 0, 0.5, 1.0, 1.5, 2.0, and 3.0 meters combined with 1-year, 10-year, 20-year, 50-year, and 100-year storm return periods, as well as the background, no storm, conditions).

Velocity hazards (maximum depth times velocity) from compound coastal hazards—specifically sea-level rise (SLR) and projected coastal storms—are provided for Unalakleet, Alaska. Velocity hazards are a measure of the velocity severity. Categories range from 0 (low hazard) to 4 (extreme hazard) following guidance from the Federal Emergency Management Agency (2020). These products are consistent with other data in this release (for example, flood extent and event-driven erosion; Erikson and others, 2025), supporting integrated coastal hazard assessments for Alaskan communities. The data are provided as gridded maps (GeoTIFFs) for 30 storm and SLR combinations (SLR scenarios 0, 0.5, 1.0, 1.5, 2.0, and 3.0 meters combined with 1-year, 10-year, 20-year, 50-year, and 100-year storm return periods).

Water elevations from compound coastal hazards—specifically sea-level rise (SLR) and projected coastal storms—are provided for Unalakleet, Alaska. These products are consistent with other data in this release (for example, flood extent and event-driven erosion; Erikson and others, 2025), supporting integrated coastal hazard assessments for Alaskan communities. The data are provided as gridded maps (GeoTIFFs) for 36 storm and SLR combinations (SLR scenarios 0, 0.5, 1.0, 1.5, 2.0, and 3.0 meters combined with 1-year, 10-year, 20-year, 50-year, and 100-year storm return periods, as well as the background, no storm, conditions).

Wave hazards (wave heights) from compound coastal hazards—specifically sea-level rise (SLR) and projected coastal storms—are provided for Unalakleet, Alaska. These products are consistent with other data in this release (for example, flood extent and event-driven erosion; Erikson and others, 2025), supporting integrated coastal hazard assessments for Alaskan communities. The data are provided as gridded maps (GeoTIFFs) for 30 storm and SLR combinations (SLR scenarios 0, 0.5, 1.0, 1.5, 2.0, and 3.0 meters combined with 1-year, 10-year, 20-year, 50-year, and 100-year storm return periods).

The data sets provided here consist of 2D XBeach model files and sample input files used for Coastal Storm Modeling System (CoSMoS) simulations of flood and erosion hazards in Utqiagvik, Alaska. The models produce outputs for a suite of hazard products (see products in this release), such as flood depths, flood extents, and erosion and sedimentation. In this release, example forcing files for conditions with a 100-year return period coastal storm and a sea level rise of 0.5 m are provided, in addition to all other files needed to run the model in surfbeat and nonhydrostatic modes.

Erosion and sedimentation maps resulting from compound coastal hazards —specifically sea-level rise (SLR) and projected coastal storms-are provided for Utqiagvik, Alaska. These products are consistent with other data in this release (for example, flood extent and velocity hazards; Erikson and others, 2025), supporting integrated coastal hazard assessments for Alaskan communities. The data are provided as gridded maps (GeoTIFFs) for 30 storm and SLR combinations (SLR scenarios 0, 0.5, 1.0, 1.5, 2.0, and 3.0 meters combined with 1-year, 10-year, 20-year, 50-year, and 100-year storm return periods).

Flood depths from compound coastal hazards—specifically sea-level rise (SLR) and projected coastal storms—are provided for Utqiagvik, Alaska. The flood depth products are consistent with other data in this release (for example, flood extent and event-driven erosion; Erikson and others, 2025), supporting integrated coastal hazard assessments for Alaskan communities. The data are provided as gridded maps (GeoTIFFs) for 36 storm and SLR combinations (SLR scenarios 0, 0.5, 1.0, 1.5, 2.0, and 3.0 meters combined with 1-year, 10-year, 20-year, 50-year, and 100-year storm return periods, as well as the background, no storm, conditions). These data are also provided for areas landward of the present-day shoreline only to make the impact of each scenario more visible. These are available for all mentioned storm and SLR combinations but the background condition with no SLR (since this scenario does not exceed the present-day shoreline).

Flood extents, as well as the upper and lower uncertainty bounds of flood extents, from compound coastal hazards—specifically sea-level rise (SLR) and projected coastal storms—are provided for Utqiagvik, Alaska. These products are consistent with other data in this release (for example, flood depths and event-driven erosion; Erikson and others, 2025), supporting integrated coastal hazard assessments for Alaskan communities. The data are provided as shapefiles for 36 storm and SLR combinations (SLR scenarios 0, 0.5, 1.0, 1.5, 2.0, and 3.0 meters combined with 1-year, 10-year, 20-year, 50-year, and 100-year storm return periods, as well as the background, no storm, conditions).

Velocity hazards (maximum depth times velocity) from compound coastal hazards—specifically sea-level rise (SLR) and projected coastal storms—are provided for Utqiagvik, Alaska. Velocity hazards are a measure of the velocity severity. Categories range from 0 (low hazard) to 4 (extreme hazard) following guidance from the Federal Emergency Management Agency (2020). These products are consistent with other data in this release (for example, flood extent and event-driven erosion; Erikson and others, 2025), supporting integrated coastal hazard assessments for Alaskan communities. The data are provided as gridded maps (GeoTIFFs) for 30 storm and SLR combinations (SLR scenarios 0, 0.5, 1.0, 1.5, 2.0, and 3.0 meters combined with 1-year, 10-year, 20-year, 50-year, and 100-year storm return periods).

Water elevations from compound coastal hazards—specifically sea-level rise (SLR) and projected coastal storms—are provided for Utqiagvik, Alaska. These products are consistent with other data in this release (for example, flood extent and event-driven erosion; Erikson and others, 2025), supporting integrated coastal hazard assessments for Alaskan communities. The data are provided as gridded maps (GeoTIFFs) for 36 storm and SLR combinations (SLR scenarios 0, 0.5, 1.0, 1.5, 2.0, and 3.0 meters combined with 1-year, 10-year, 20-year, 50-year, and 100-year storm return periods, as well as the background, no storm, conditions).

Wave hazards (wave heights) from compound coastal hazards—specifically sea-level rise (SLR) and projected coastal storms—are provided for Utqiagvik, Alaska. These products are consistent with other data in this release (for example, flood extent and event-driven erosion; Erikson and others, 2025), supporting integrated coastal hazard assessments for Alaskan communities. The data are provided as gridded maps (GeoTIFFs) for 30 storm and SLR combinations (SLR scenarios 0, 0.5, 1.0, 1.5, 2.0, and 3.0 meters combined with 1-year, 10-year, 20-year, 50-year, and 100-year storm return periods).

CTD profiles were collected by the U.S. Geological Survey (USGS) Pacific Coastal and Marine Science Center to measure the physical characteristics of Corte Madera tidal creek over the course of a tidal cycle during one of the largest spring tides in both Winter and Summer. Conductivity, temperature, and pressure data were collected, as well as suspended-sediment concentration in the water column Each profile was collected from surface to bed. Profiles were collected on 4 days: August 8 and 9 of 2022 and January 19 and 20 of 2023. Data files are grouped by season (summer or winter). Users are advised to assess data quality carefully.

The data sets provided here consist of 2D XBeach model files and sample input files used for Coastal Storm Modeling System (CoSMoS) simulations of flood and erosion hazards in Golovin, Alaska. The models produce outputs for a suite of hazard products (see products in this release), such as flood depths, flood extents, and erosion and sedimentation. In this release, example forcing files for conditions with a 100-year return period coastal storm and a sea level rise of 0.5 m are provided, in addition to all other files needed to run the model in surfbeat and nonhydrostatic modes.

Erosion and sedimentation maps resulting from compound coastal hazards —specifically sea-level rise (SLR) and projected coastal storms-are provided for Golovin, Alaska. These products are consistent with other data in this release (for example, flood extent and velocity hazards; Erikson and others, 2025), supporting integrated coastal hazard assessments for Alaskan communities. The data are provided as gridded maps (GeoTIFFs) for 30 storm and SLR combinations (SLR scenarios 0, 0.5, 1.0, 1.5, 2.0, and 3.0 meters combined with 1-year, 10-year, 20-year, 50-year, and 100-year storm return periods).

Flood depths from compound coastal hazards—specifically sea-level rise (SLR) and projected coastal storms—are provided for Golovin, Alaska. The flood depth products are consistent with other data in this release (for example, flood extent and event-driven erosion; Erikson and others, 2025), supporting integrated coastal hazard assessments for Alaskan communities. The data are provided as gridded maps (GeoTIFFs) for 36 storm and SLR combinations (SLR scenarios 0, 0.5, 1.0, 1.5, 2.0, and 3.0 meters combined with 1-year, 10-year, 20-year, 50-year, and 100-year storm return periods, as well as the background, no storm, conditions). As an additional product, these data are also provided only for areas landward of the present-day shoreline to make the impact of each scenario more visible. These are available for all mentioned storm and SLR combinations but not for the background condition with no SLR (since this scenario does not exceed the present-day shoreline).

Flood extents, as well as the upper and lower uncertainty bounds of flood extents, from compound coastal hazards—specifically sea-level rise (SLR) and projected coastal storms—are provided for Golovin, Alaska. These products are consistent with other data in this release (for example, flood depths and event-driven erosion; Erikson and others, 2025), supporting integrated coastal hazard assessments for Alaskan communities. The data are provided as shapefiles for 36 storm and SLR combinations (SLR scenarios 0, 0.5, 1.0, 1.5, 2.0, and 3.0 meters combined with 1-year, 10-year, 20-year, 50-year, and 100-year storm return periods, as well as the background, no storm, conditions).

Velocity hazards (maximum depth times velocity) from compound coastal hazards—specifically sea-level rise (SLR) and projected coastal storms—are provided for Golovin, Alaska. Velocity hazards are a measure of the velocity severity. Categories range from 0 (low hazard) to 4 (extreme hazard) following guidance from the Federal Emergency Management Agency (2020). These products are consistent with other data in this release (for example, flood extent and event-driven erosion; Erikson and others, 2025), supporting integrated coastal hazard assessments for Alaskan communities. The data are provided as gridded maps (GeoTIFFs) for 30 storm and SLR combinations (SLR scenarios 0, 0.5, 1.0, 1.5, 2.0, and 3.0 meters combined with 1-year, 10-year, 20-year, 50-year, and 100-year storm return periods).

Water elevations from compound coastal hazards—specifically sea-level rise (SLR) and projected coastal storms—are provided for Golovin, Alaska. These products are consistent with other data in this release (for example, flood extent and event-driven erosion; Erikson and others, 2025), supporting integrated coastal hazard assessments for Alaskan communities. The data are provided as gridded maps (GeoTIFFs) for 36 storm and SLR combinations (SLR scenarios 0, 0.5, 1.0, 1.5, 2.0, and 3.0 meters combined with 1-year, 10-year, 20-year, 50-year, and 100-year storm return periods, as well as the background, no storm, conditions).

Wave hazards (wave heights) from compound coastal hazards—specifically sea-level rise (SLR) and projected coastal storms—are provided for Golovin, Alaska. These products are consistent with other data in this release (for example, flood extent and event-driven erosion; Erikson and others, 2025), supporting integrated coastal hazard assessments for Alaskan communities. The data are provided as gridded maps (GeoTIFFs) for 30 storm and SLR combinations (SLR scenarios 0, 0.5, 1.0, 1.5, 2.0, and 3.0 meters combined with 1-year, 10-year, 20-year, 50-year, and 100-year storm return periods).

Flood depths (meters) associated with coincident compound coastal hazards—specifically sea-level rise (SLR), projected coastal storms, and streamflow—are provided for King County, Washington. The flood depth products are consistent with other data in this release (for example, flood extent and water elevation), supporting integrated coastal hazard assessments for Washington communities. The data are provided as gridded rasters (GeoTIFFs) for 42 storm and SLR combinations (SLR scenarios 0, 0.25, 0.5, 1.0, 1.5, 2.0, and 3.0 meters (m) combined with 1-year, 10-year, 20-year, 50-year, and 100-year storm return periods, as well as the background, no storm, conditions).

Flood duration (maximum hours per years that occurs on average once every 'rp' years) associated with coincident compound coastal hazards—specifically sea-level rise (SLR), projected coastal storms, and streamflow—are provided for King County, Washington. The flood duration products are consistent with other data in this release (for example, flood extent and water elevation), supporting integrated coastal hazard assessments for Washington communities. The data are provided as gridded rasters (GeoTIFFs) for 42 storm and SLR combinations (SLR scenarios 0, 0.25, 0.5, 1.0, 1.5, 2.0, and 3.0 meters (m) combined with 1-year, 10-year, 20-year, 50-year, and 100-year storm return periods, as well as the background, no storm, conditions).

The datasets provided here consist of SFINCS model files and sample input files used for Coastal Storm Modeling System (CoSMoS) simulations of flood hazards in King County, Washington. The models produce outputs for a suite of hazard products (see products in this release), such as flood depths, flood extents, and others. In this release, example forcing files for a single water year and a sea level rise of 0.0 m are provided, in addition to all other files needed to run the model.

Velocity-depth hazards (maximum depth times velocity, binned to severity levels) associated with coincident compound coastal hazards—specifically sea-level rise (SLR), projected coastal storms, and streamflow—are provided for King County, Washington. These products are consistent with other data in this release (for example, flood depths and water elevation), supporting integrated coastal hazard assessments for Washington communities. The data are provided as shapefiles for 42 storm and SLR combinations (SLR scenarios 0, 0.25, 0.5, 1.0, 1.5, 2.0, and 3.0 meters (m) combined with 1-year, 10-year, 20-year, 50-year, and 100-year storm return periods, as well as the background, no storm, conditions).

Water surface elevation (meters, NAVD88) associated with coincident compound coastal hazards—specifically sea-level rise (SLR), projected coastal storms, and streamflow—are provided for King County, Washington. The water elevation products are consistent with other data in this release (for example, flood extent and flood depth), supporting integrated coastal hazard assessments for Washington communities. The data are provided as gridded rasters (GeoTIFFs) for 42 storm and SLR combinations (SLR scenarios 0, 0.25, 0.5, 1.0, 1.5, 2.0, and 3.0 meters (m) combined with 1-year, 10-year, 20-year, 50-year, and 100-year storm return periods, as well as the background, no storm, conditions).

Flood depths from compound coastal hazards—specifically sea-level rise (SLR) and projected coastal storms—are provided for Pierce County, Washington. The flood depth products are consistent with other data in this release (for example, flood extent and water elevation), supporting integrated coastal hazard assessments for Washington communities. The data are provided as gridded rasters (GeoTIFFs) for 36 storm and SLR combinations (SLR scenarios 0, 0.5, 1.0, 1.5, 2.0, and 3.0 meters (m) combined with 1-year, 10-year, 20-year, 50-year, and 100-year storm return periods, as well as the background, no storm, conditions).

Flood duration from compound coastal hazards—specifically sea-level rise (SLR) and projected coastal storms—are provided for Pierce County, Washington. The flood duration products are consistent with other data in this release (for example, flood extent and water elevation), supporting integrated coastal hazard assessments for Washington communities. The data are provided as gridded rasters (GeoTIFFs) for 36 storm and SLR combinations (SLR scenarios 0, 0.5, 1.0, 1.5, 2.0, and 3.0 meters (m) combined with 1-year, 10-year, 20-year, 50-year, and 100-year storm return periods, as well as the background, no storm, conditions).

Flood extents, upper and lower uncertainty bounds of flood extents, and low lying vulnerable areas associated with coincident compound coastal hazards—specifically sea-level rise (SLR), projected coastal storms, and streamflow—are provided for Pierce County, Washington. These products are consistent with other data in this release (for example, flood depths and water elevation), supporting integrated coastal hazard assessments for Washington communities. The data are provided as shapefiles for 42 storm and SLR combinations (SLR scenarios 0, 0.25, 0.5, 1.0, 1.5, 2.0, and 3.0 meters (m) combined with 1-year, 10-year, 20-year, 50-year, and 100-year storm return periods, as well as the background, no storm, conditions).

The datasets provided here consist of SFINCS model files and sample input files used for Coastal Storm Modeling System (CoSMoS) simulations of flood hazards in Pierce County, Washington. The models produce outputs for a suite of hazard products (see products in this release), such as flood depths, flood extents, and others. In this release, example forcing files for a single water year and a sea level rise of 0.0 m are provided, in addition to all other files needed to run the model.

Velocity hazards (maximum depth times velocity) from compound coastal hazards—specifically sea-level rise (SLR) and projected coastal storms—are provided for Pierce County, Washington. These products are consistent with other data in this release (for example, flood depths and water elevation), supporting integrated coastal hazard assessments for Washington communities. The data are provided as shapefiles for 36 storm and SLR combinations (SLR scenarios 0, 0.5, 1.0, 1.5, 2.0, and 3.0 meters (m) combined with 1-year, 10-year, 20-year, 50-year, and 100-year storm return periods, as well as the background, no storm, conditions).

Water elevation from compound coastal hazards—specifically sea-level rise (SLR) and projected coastal storms—are provided for Pierce County, Washington. The water elevation products are consistent with other data in this release (for example, flood extent and flood depth), supporting integrated coastal hazard assessments for Washington communities. The data are provided as gridded rasters (GeoTIFFs) for 36 storm and SLR combinations (SLR scenarios 0, 0.5, 1.0, 1.5, 2.0, and 3.0 meters (m) combined with 1-year, 10-year, 20-year, 50-year, and 100-year storm return periods, as well as the background, no storm, conditions).

This data set consists of physics-based Delft3D-FLOW and WAVE hydrodynamic model input files used for Coastal Storm Modeling System (CoSMoS) sub-regional tier 2 simulations. Sub-regional tier 2 simulations cover portions of the Northern California open-coast region, from Point Arena to the California/Oregon state border, and they provide boundary conditions to higher-resolution simulations. Simulations are run for several storm events (covering a range of no storm, 1-year, 20-year, and 100-year coastal storm conditions) and sea-level rise (SLR) scenarios.

This data set consists of 2D XBeach model input files used for Coastal Storm Modeling System (CoSMoS) sub-regional tier 3 simulations. Sub-regional tier 3 simulations cover portions of the Northern California open-coast region for Humboldt, Del Norte, and Mendocino Counties, and they provide final modeled hazard outputs going into projected hazard products. Simulations are run for several storm events (covering a range of no storm, 1-year, 20-year, and 100-year coastal storm conditions) and sea-level scenarios.

Flood extents, upper and lower uncertainty bounds of flood extents, and low lying vulnerable areas associated with coincident compound coastal hazards—specifically sea-level rise (SLR), projected coastal storms, and streamflow—are provided for King County, Washington. These products are consistent with other data in this release (for example, flood depths and water elevation), supporting integrated coastal hazard assessments for Washington communities. The data are provided as shapefiles for 42 storm and SLR combinations (SLR scenarios 0, 0.25, 0.5, 1.0, 1.5, 2.0, and 3.0 meters (m) combined with 1-year, 10-year, 20-year, 50-year, and 100-year storm return periods, as well as the background, no storm, conditions).

Flood depths from compound coastal hazards—specifically sea-level rise (SLR) and projected coastal storms—are provided for Elim, Alaska. These projections focus on areas landward of the present-day shoreline. The flood depth products are consistent with other data in this release (for example, flood extent and event-driven erosion; Erikson and others, 2025), supporting integrated coastal hazard assessments for Alaskan communities. The data are provided as gridded maps (GeoTiffs) for 36 storm and SLR combinations (SLR scenarios 0, 0.5, 1.0, 1.5, 2.0, and 3.0 meters combined with 1-year, 10-year, 20-year, 50-year, and 100-year storm return periods, as well as the background, no storm, conditions).

This data release contains bathymetry and topography data from surveys performed on the Elwha River delta between 2010 and 2017. Sediment grain-size data are available for selected surveys performed after May 2012. This data release will be updated as additional bathymetry, topography, and surface-sediment grain-size data from future surveys become available.

Oceanographic and meteorological time-series monitoring data were collected by the U.S. Geological Survey (USGS) Pacific Coastal and Marine Science Center from 2023 to 2025, to monitor a pilot shallow-water placement of dredged sediment project led by the US Army Corps of Engineers San Francisco District. Data were collected at nine stations located in the shallows offshore of Whales Tail Marsh in south San Francisco Bay, CA. Stations were positioned around the placement site of the dredged material. Data were collected prior to, during, and after the sediment was placed. Stations consisted of platforms deployed along 2 transects: one along-shore and one cross-shore. Stations in the cross-shore transect included: XM, located approximately 25 meters from the bay edge on Whales Tail marsh; X4 located slightly offshore of the marsh; X3 just offshore (west) of X4; X2 (same location as XG and XL) east/marsh side of the placement area; X1 western side of the placement area; and X0 just east of the navigational channel. A wave-met buoy MW was close to and slightly east of X0. Along-shore transect platforms included AN and AS, north and south of the placement area, respectively. Data types include pressure, velocity, turbidity, suspended particle size distribution, conductivity, temperature, wave statistics, and wind speed and direction, barometric pressure and air temperature. Data files are grouped by deployment (A-E) then by station name (OR) instrument type, except for data recorded at station X0 and MW, which have their own folders. At several stations there were periods of low water when sensors were no longer submerged, resulting in spurious data. In addition, most instruments experienced some degree of biofouling. Users are advised to assess data quality carefully, and to check the metadata for instrument information, as platform deployment times and data-processing methods varied. Turbidity values (in NTU or volts) can be converted to SSC (in milligrams per liter) via the calibration coefficient (slope value) located in the “Support Files” section below, DMP_Turbidity_to_SSC_calibration_constants.csv. Turbidity data were recorded using either a 1x gain or a 5x gain setting however, all calibration coefficients were obtained using 5x gain data. Therefore, users should refer to the “Deployment Gain Setting” column in the support file to determine the gain setting of the data in use. Data collected at 1x gain must be scaled to 5x gain before comparison with other 5x datasets or conversion to SSC. To convert a sensor from 1x gain to 5x gain, simply multiply the turbidity data by 5. To convert a 1x gain data to SSC, use the following equation: (SSC = 5 * turbidity data * slope), where slope is calibration coefficient obtained from the support file. To convert a sensor that was deployed using a 5x gain setting to SSC, simply multiply the turbidity data by the appropriate slope value from the support file.

Data from various sources, including 2018-2022 multibeam bathymetry data collected by the National Oceanic and Atmospheric Administration (NOAA) and the U.S. Geological Survey (USGS), were combined to create a composite 30-m resolution multibeam bathymetry surface of southern Cascadia Margin offshore Oregon and northern California. The data are available as a GeoTIFF file.

This polygon shapefile describes the data sources used to create a composite 30-m resolution multibeam bathymetry surface of southern Cascadia Margin offshore Oregon and northern California.

This dataset includes swell-filtered, high-resolution seismic-reflection data jointly collected by the U.S. Geological Survey (USGS) and Oregon State University in 2012, between Punta Gorda and Fort Bragg in northern California.

This dataset includes Magnetic-field level data jointly collected by the U.S. Geological Survey (USGS) and Oregon State University in 2012, between Punta Gorda and Fort Bragg in northern California.

This dataset includes navigation data for marine geophysical data jointly collected by the U.S. Geological Survey (USGS) and Oregon State University in 2012, between Punta Gorda and Fort Bragg in northern California.

This dataset includes raw, high-resolution seismic-reflection data jointly collected by the U.S. Geological Survey (USGS) and Oregon State University in 2012, between Punta Gorda and Fort Bragg in northern California.

This dataset includes swell-filtered, high-resolution seismic-reflection data jointly collected by the U.S. Geological Survey (USGS) and Oregon State University in 2010, between Shelter Cove and Fort Bragg in northern California.

This dataset includes navigation data for marine geophysical data jointly collected by the U.S. Geological Survey (USGS) and Oregon State University in 2010, between Shelter Cove and Fort Bragg in northern California.

This dataset includes raw, high-resolution seismic-reflection data jointly collected by the U.S. Geological Survey (USGS) and Oregon State University in 2010, between Shelter Cove and Fort Bragg in northern California.

This dataset includes swell-filtered, high-resolution seismic-reflection data jointly collected by the U.S. Geological Survey (USGS) and Oregon State University in 2010, between Fort Bragg and Point Arena in northern California.

This dataset includes navigation data for marine geophysical data jointly collected by the U.S. Geological Survey (USGS) and Oregon State University in 2010, between Fort Bragg and Point Arena in northern California.

This dataset includes raw, high-resolution seismic-reflection data jointly collected by the U.S. Geological Survey (USGS) and Oregon State University in 2010, between Fort Bragg and Point Arena in northern California.

Files contain hydrodynamic and sediment transport data for the location and deployment indicated. Time-series data of water depth, velocity, turbidity, and temperature were collected in San Pablo Bay and China Camp Marsh as part of the San Francisco Bay Marsh Sediment Experiments. Several instruments were deployed in tidal creek, marsh, mudflat, and Bay locations, gathering data on water depth, velocity, salinity/temperature, and turbidity. Deployment data are grouped by region (Bay channel (main Bay), Bay shallows, tidal creek, or marsh/mudflat/upper tidal creek). Users are advised check metadata and instrument information carefully for applicable time periods of specific data, as individual instrument deployment times vary.

Files contain hydrodynamic and sediment transport data for the location and deployment indicated. Time-series data of water depth, velocity, turbidity, and temperature were collected in San Pablo Bay and China Camp Marsh as part of the San Francisco Bay Marsh Sediment Experiments. Several instruments were deployed in tidal creek, marsh, mudflat, and Bay locations, gathering data on water depth, velocity, salinity/temperature, and turbidity. Deployment data are grouped by region (Bay channel (main Bay), Bay shallows, tidal creek, or marsh/mudflat/upper tidal creek). Users are advised to check metadata and instrument information carefully for applicable time periods of specific data, as individual instrument deployment times vary.

Files contain hydrodynamic and sediment transport data for the location and deployment indicated. Time-series data of water depth, velocity, turbidity, and temperature were collected in San Pablo Bay and China Camp Marsh as part of the San Francisco Bay Marsh Sediment Experiments. Several instruments were deployed in tidal creek, marsh, mudflat, and Bay locations, gathering data on water depth, velocity, salinity/temperature, and turbidity. Deployment data are grouped by region (Bay channel (main Bay), Bay shallows, tidal creek, or marsh/mudflat/upper tidal creek). Users are advised check metadata and instrument information carefully for applicable time periods of specific data, as individual instrument deployment times vary.

Files contain hydrodynamic and sediment transport data for the location and deployment indicated. Time-series data of water depth, velocity, turbidity, and temperature were collected in San Pablo Bay and China Camp Marsh as part of the San Francisco Bay Marsh Sediment Experiments. Several instruments were deployed in tidal creek, marsh, mudflat, and Bay locations, gathering data on water depth, velocity, salinity/temperature, and turbidity. Deployment data are grouped by region (Bay channel (main Bay), Bay shallows, tidal creek, or marsh/mudflat/upper tidal creek). Users are advised check metadata and instrument information carefully for applicable time periods of specific data, as individual instrument deployment times vary.

Files contain hydrodynamic and sediment transport data for the location and deployment indicated. Time-series data of water depth, velocity, turbidity, and temperature were collected in San Pablo Bay and China Camp Marsh as part of the San Francisco Bay Marsh Sediment Experiments. Several instruments were deployed in tidal creek, marsh, mudflat, and Bay locations, gathering data on water depth, velocity, salinity/temperature, and turbidity. Deployment data are grouped by region (Bay channel (main Bay), Bay shallows, tidal creek, or marsh/mudflat/upper tidal creek). Users are advised check metadata and instrument information carefully for applicable time periods of specific data, as individual instrument deployment times vary.

Files contain hydrodynamic and sediment transport data for the location and deployment indicated. Time-series data of water depth, velocity, turbidity, and temperature were collected in San Pablo Bay and China Camp Marsh as part of the San Francisco Bay Marsh Sediment Experiments. Several instruments were deployed in tidal creek, marsh, mudflat, and Bay locations, gathering data on water depth, velocity, salinity/temperature, and turbidity. Deployment data are grouped by region (Bay channel (main Bay), Bay shallows, tidal creek, or marsh/mudflat/upper tidal creek). Users are advised check metadata and instrument information carefully for applicable time periods of specific data, as individual instrument deployment times vary.

Files contain hydrodynamic and sediment transport data for the location and deployment indicated. Time-series data of water depth, velocity, turbidity, and temperature were collected in San Pablo Bay and China Camp Marsh as part of the San Francisco Bay Marsh Sediment Experiments. Several instruments were deployed in tidal creek, marsh, mudflat, and Bay locations, gathering data on water depth, velocity, salinity/temperature, and turbidity. Deployment data are grouped by region (Bay channel (main Bay), Bay shallows, tidal creek, or marsh/mudflat/upper tidal creek). Users are advised check metadata and instrument information carefully for applicable time periods of specific data, as individual instrument deployment times vary.

Files contain hydrodynamic and sediment transport data for the location and deployment indicated. Time-series data of water depth, velocity, turbidity, and temperature were collected in San Pablo Bay and China Camp Marsh as part of the San Francisco Bay Marsh Sediment Experiments. Several instruments were deployed in tidal creek, marsh, mudflat, and Bay locations, gathering data on water depth, velocity, salinity/temperature, and turbidity. Deployment data are grouped by region (Bay channel (main Bay), Bay shallows, tidal creek, or marsh/mudflat/upper tidal creek). Users are advised check metadata and instrument information carefully for applicable time periods of specific data, as individual instrument deployment times vary.

Files contain hydrodynamic and sediment transport data for the location and deployment indicated. Time-series data of water depth, velocity, turbidity, and temperature were collected in San Pablo Bay and China Camp Marsh as part of the San Francisco Bay Marsh Sediment Experiments. Several instruments were deployed in tidal creek, marsh, mudflat, and Bay locations, gathering data on water depth, velocity, salinity/temperature, and turbidity. Deployment data are grouped by region (Bay channel (main Bay), Bay shallows, tidal creek, or marsh/mudflat/upper tidal creek). Users are advised check metadata and instrument information carefully for applicable time periods of specific data, as individual instrument deployment times vary.

Files contain hydrodynamic and sediment transport data for the location and deployment indicated. Time-series data of water depth, velocity, turbidity, and temperature were collected in San Pablo Bay and China Camp Marsh as part of the San Francisco Bay Marsh Sediment Experiments. Several instruments were deployed in tidal creek, marsh, mudflat, and Bay locations, gathering data on water depth, velocity, salinity/temperature, and turbidity. Deployment data are grouped by region (Bay channel (main Bay), Bay shallows, tidal creek, or marsh/mudflat/upper tidal creek). Users are advised check metadata and instrument information carefully for applicable time periods of specific data, as individual instrument deployment times vary.

Files contain hydrodynamic and sediment transport data for the location and deployment indicated. Time-series data of water depth, velocity, turbidity, and temperature were collected in San Pablo Bay and China Camp Marsh as part of the San Francisco Bay Marsh Sediment Experiments. Several instruments were deployed in tidal creek, marsh, mudflat, and Bay locations, gathering data on water depth, velocity, salinity/temperature, and turbidity. Deployment data are grouped by region (Bay channel (main Bay), Bay shallows, tidal creek, or marsh/mudflat/upper tidal creek). Users are advised to check metadata and instrument information carefully for applicable time periods of specific data, as individual instrument deployment times vary.

Files contain hydrodynamic and sediment transport data for the location and deployment indicated. Time-series data of water depth, velocity, turbidity, and temperature were collected in San Pablo Bay and China Camp Marsh as part of the San Francisco Bay Marsh Sediment Experiments. Several instruments were deployed in tidal creek, marsh, mudflat, and Bay locations, gathering data on water depth, velocity, salinity/temperature, and turbidity. Deployment data are grouped by region (Bay channel (main Bay), Bay shallows, tidal creek, or marsh/mudflat/upper tidal creek). Users are advised to check metadata and instrument information carefully for applicable time periods of specific data, as individual instrument deployment times vary.

As part of the hydrodynamic and sediment transport investigations in San Pablo Bay and China Camp Marsh, California, particle size distributions of bed sediments were measured at most instrumented stations and are presented in a comma-delimited values spreadsheet. This portion of the data release presents San Pablo Bay and China Camp Marsh sediment particle size distributions from samples collected during multiple instrument deployments. Users are advised to check the data carefully for sampling time, location, and reference information.

Files contain hydrodynamic and sediment transport data for the location and deployment indicated. Time-series data of water depth, velocity, turbidity, and temperature were collected in San Pablo Bay and China Camp Marsh as part of the San Francisco Bay Marsh Sediment Experiments. Several instruments were deployed in tidal creek, marsh, mudflat, and Bay locations, gathering data on water depth, velocity, salinity/temperature, and turbidity. Deployment data are grouped by region (Bay channel (main Bay), Bay shallows, tidal creek, or marsh/mudflat/upper tidal creek). Users are advised check metadata and instrument information carefully for applicable time periods of specific data, as individual instrument deployment times vary.

Files contain hydrodynamic and sediment transport data for the location and deployment indicated. Time-series data of water depth, velocity, turbidity, and temperature were collected in San Pablo Bay and China Camp Marsh as part of the San Francisco Bay Marsh Sediment Experiments. Several instruments were deployed in tidal creek, marsh, mudflat, and Bay locations, gathering data on water depth, velocity, salinity/temperature, and turbidity. Deployment data are grouped by region (Bay channel (main Bay), Bay shallows, tidal creek, or marsh/mudflat/upper tidal creek). Users are advised check metadata and instrument information carefully for applicable time periods of specific data, as individual instrument deployment times vary.

Files contain hydrodynamic and sediment transport data for the location and deployment indicated. Time-series data of water depth, velocity, turbidity, and temperature were collected in San Pablo Bay and China Camp Marsh as part of the San Francisco Bay Marsh Sediment Experiments. Several instruments were deployed in tidal creek, marsh, mudflat, and Bay locations, gathering data on water depth, velocity, salinity/temperature, and turbidity. Deployment data are grouped by region (Bay channel (main Bay), Bay shallows, tidal creek, or marsh/mudflat/upper tidal creek). Users are advised check metadata and instrument information carefully for applicable time periods of specific data, as individual instrument deployment times vary.

Files contain hydrodynamic and sediment transport data for the location and deployment indicated. Time-series data of water depth, velocity, turbidity, and temperature were collected in San Pablo Bay and China Camp Marsh as part of the San Francisco Bay Marsh Sediment Experiments. Several instruments were deployed in tidal creek, marsh, mudflat, and Bay locations, gathering data on water depth, velocity, salinity/temperature, and turbidity. Deployment data are grouped by region (Bay channel (main Bay), Bay shallows, tidal creek, or marsh/mudflat/upper tidal creek). Users are advised check metadata and instrument information carefully for applicable time periods of specific data, as individual instrument deployment times vary.

Maximum depth of flooding surface (in cm) in the region landward of the present day shoreline that is inundated for the storm condition and sea-level rise (SLR) scenario indicated. Note: Duration datasets may have occasional gaps in open-coast sections. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Model details and data sources are outlined in CoSMoS_3.0_Phase_2_Southern_California_Bight:_Summary_of_data_and_methods (available at https://www.sciencebase.gov/catalog/file/get/57f1d4f3e4b0bc0bebfee139?name=CoSMoS_SoCalv3_Phase2_summary_of_methods.pdf). Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception to include the Channel Islands. Please read the Summary of Methods and inspect output carefully. Data are complete for the information presented.

Maximum depth of flooding surface (in cm) in the region landward of the present day shoreline that is inundated for the storm condition and sea-level rise (SLR) scenario indicated. Note: Duration datasets may have occasional gaps in open-coast sections. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Model details and data sources are outlined in CoSMoS_3.0_Phase_2_Southern_California_Bight:_Summary_of_data_and_methods (available at https://www.sciencebase.gov/catalog/file/get/57f1d4f3e4b0bc0bebfee139?name=CoSMoS_SoCalv3_Phase2_summary_of_methods.pdf). Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception to include the Channel Islands. Please read the Summary of Methods and inspect output carefully. Data are complete for the information presented.

Maximum depth of flooding surface (in cm) in the region landward of the present day shoreline that is inundated for the storm condition and sea-level rise (SLR) scenario indicated. Note: Duration datasets may have occasional gaps in open-coast sections. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Model details and data sources are outlined in CoSMoS_3.0_Phase_2_Southern_California_Bight:_Summary_of_data_and_methods (available at https://www.sciencebase.gov/catalog/file/get/57f1d4f3e4b0bc0bebfee139?name=CoSMoS_SoCalv3_Phase2_summary_of_methods.pdf). Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception to include the Channel Islands. Please read the Summary of Methods and inspect output carefully. Data are complete for the information presented.

Maximum depth of flooding surface (in cm) in the region landward of the present day shoreline that is inundated for the storm condition and sea-level rise (SLR) scenario indicated. Note: Duration datasets may have occasional gaps in open-coast sections. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Model details and data sources are outlined in CoSMoS_3.0_Phase_2_Southern_California_Bight:_Summary_of_data_and_methods (available at https://www.sciencebase.gov/catalog/file/get/57f1d4f3e4b0bc0bebfee139?name=CoSMoS_SoCalv3_Phase2_summary_of_methods.pdf). Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception to include the Channel Islands. Please read the Summary of Methods and inspect output carefully. Data are complete for the information presented.

Geographic extent of projected coastal flooding, low-lying vulnerable areas, and maxium/minimum flood potential (flood uncertainty) associated with the sea-level rise and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Model details and data sources are outlined in CoSMoS_3.0_Phase_2_Southern_California_Bight:_Summary_of_data_and_methods (available at https://www.sciencebase.gov/catalog/file/get/57f1d4f3e4b0bc0bebfee139?name=CoSMoS_SoCalv3_Phase2_summary_of_methods.pdf). Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception to include the Channel Islands. Please read the Summary of Methods and inspect output carefully. Data are complete for the information presented.

Geographic extent of projected coastal flooding, low-lying vulnerable areas, and maxium/minimum flood potential (flood uncertainty) associated with the sea-level rise and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Model details and data sources are outlined in CoSMoS_3.0_Phase_2_Southern_California_Bight:_Summary_of_data_and_methods (available at https://www.sciencebase.gov/catalog/file/get/57f1d4f3e4b0bc0bebfee139?name=CoSMoS_SoCalv3_Phase2_summary_of_methods.pdf). Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception to include the Channel Islands. Please read the Summary of Methods and inspect output carefully. Data are complete for the information presented.

Geographic extent of projected coastal flooding, low-lying vulnerable areas, and maxium/minimum flood potential (flood uncertainty) associated with the sea-level rise and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Model details and data sources are outlined in CoSMoS_3.0_Phase_2_Southern_California_Bight:_Summary_of_data_and_methods (available at https://www.sciencebase.gov/catalog/file/get/57f1d4f3e4b0bc0bebfee139?name=CoSMoS_SoCalv3_Phase2_summary_of_methods.pdf). Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception to include the Channel Islands. Please read the Summary of Methods and inspect output carefully. Data are complete for the information presented.

Geographic extent of projected coastal flooding, low-lying vulnerable areas, and maxium/minimum flood potential (flood uncertainty) associated with the sea-level rise and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Model details and data sources are outlined in CoSMoS_3.0_Phase_2_Southern_California_Bight:_Summary_of_data_and_methods (available at https://www.sciencebase.gov/catalog/file/get/57f1d4f3e4b0bc0bebfee139?name=CoSMoS_SoCalv3_Phase2_summary_of_methods.pdf). Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception to include the Channel Islands. Please read the Summary of Methods and inspect output carefully. Data are complete for the information presented.

Model-derived ocean current velocities (in meters per second) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Model details and data sources are outlined in CoSMoS_3.0_Phase_2_Southern_California_Bight:_Summary_of_data_and_methods (available at https://www.sciencebase.gov/catalog/file/get/57f1d4f3e4b0bc0bebfee139?name=CoSMoS_SoCalv3_Phase2_summary_of_methods.pdf). Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception to include the Channel Islands. Please read the Summary of Methods and inspect output carefully. Data are complete for the information presented.

Model-derived ocean current velocities (in meters per second) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Model details and data sources are outlined in CoSMoS_3.0_Phase_2_Southern_California_Bight:_Summary_of_data_and_methods (available at https://www.sciencebase.gov/catalog/file/get/57f1d4f3e4b0bc0bebfee139?name=CoSMoS_SoCalv3_Phase2_summary_of_methods.pdf). Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception to include the Channel Islands. Please read the Summary of Methods and inspect output carefully. Data are complete for the information presented.

Model-derived ocean current velocities (in meters per second) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Model details and data sources are outlined in CoSMoS_3.0_Phase_2_Southern_California_Bight:_Summary_of_data_and_methods (available at https://www.sciencebase.gov/catalog/file/get/57f1d4f3e4b0bc0bebfee139?name=CoSMoS_SoCalv3_Phase2_summary_of_methods.pdf). Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception to include the Channel Islands. Please read the Summary of Methods and inspect output carefully. Data are complete for the information presented.

Model-derived ocean current velocities (in meters per second) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Model details and data sources are outlined in CoSMoS_3.0_Phase_2_Southern_California_Bight:_Summary_of_data_and_methods (available at https://www.sciencebase.gov/catalog/file/get/57f1d4f3e4b0bc0bebfee139?name=CoSMoS_SoCalv3_Phase2_summary_of_methods.pdf). Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception to include the Channel Islands. Please read the Summary of Methods and inspect output carefully. Data are complete for the information presented.

Model-derived total water levels (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Model details and data sources are outlined in CoSMoS_3.0_Phase_2_Southern_California_Bight:_Summary_of_data_and_methods (available at https://www.sciencebase.gov/catalog/file/get/57f1d4f3e4b0bc0bebfee139?name=CoSMoS_SoCalv3_Phase2_summary_of_methods.pdf). Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception to include the Channel Islands. Please read the Summary of Methods and inspect output carefully. Data are complete for the information presented.

Model-derived total water levels (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Model details and data sources are outlined in CoSMoS_3.0_Phase_2_Southern_California_Bight:_Summary_of_data_and_methods (available at https://www.sciencebase.gov/catalog/file/get/57f1d4f3e4b0bc0bebfee139?name=CoSMoS_SoCalv3_Phase2_summary_of_methods.pdf). Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception to include the Channel Islands. Please read the Summary of Methods and inspect output carefully. Data are complete for the information presented.

Model-derived total water levels (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Model details and data sources are outlined in CoSMoS_3.0_Phase_2_Southern_California_Bight:_Summary_of_data_and_methods (available at https://www.sciencebase.gov/catalog/file/get/57f1d4f3e4b0bc0bebfee139?name=CoSMoS_SoCalv3_Phase2_summary_of_methods.pdf). Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception to include the Channel Islands. Please read the Summary of Methods and inspect output carefully. Data are complete for the information presented.

Model-derived total water levels (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Model details and data sources are outlined in CoSMoS_3.0_Phase_2_Southern_California_Bight:_Summary_of_data_and_methods (available at https://www.sciencebase.gov/catalog/file/get/57f1d4f3e4b0bc0bebfee139?name=CoSMoS_SoCalv3_Phase2_summary_of_methods.pdf). Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception to include the Channel Islands. Please read the Summary of Methods and inspect output carefully. Data are complete for the information presented.

Model-derived significant wave height (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Model details and data sources are outlined in CoSMoS_3.0_Phase_2_Southern_California_Bight:_Summary_of_data_and_methods (available at https://www.sciencebase.gov/catalog/file/get/57f1d4f3e4b0bc0bebfee139?name=CoSMoS_SoCalv3_Phase2_summary_of_methods.pdf). Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception to include the Channel Islands. Please read the Summary of Methods and inspect output carefully. Data are complete for the information presented.

Model-derived significant wave height (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Model details and data sources are outlined in CoSMoS_3.0_Phase_2_Southern_California_Bight:_Summary_of_data_and_methods (available at https://www.sciencebase.gov/catalog/file/get/57f1d4f3e4b0bc0bebfee139?name=CoSMoS_SoCalv3_Phase2_summary_of_methods.pdf). Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception to include the Channel Islands. Please read the Summary of Methods and inspect output carefully. Data are complete for the information presented.

Model-derived significant wave height (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Model details and data sources are outlined in CoSMoS_3.0_Phase_2_Southern_California_Bight:_Summary_of_data_and_methods (available at https://www.sciencebase.gov/catalog/file/get/57f1d4f3e4b0bc0bebfee139?name=CoSMoS_SoCalv3_Phase2_summary_of_methods.pdf). Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception to include the Channel Islands. Please read the Summary of Methods and inspect output carefully. Data are complete for the information presented.

Model-derived significant wave height (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Model details and data sources are outlined in CoSMoS_3.0_Phase_2_Southern_California_Bight:_Summary_of_data_and_methods (available at https://www.sciencebase.gov/catalog/file/get/57f1d4f3e4b0bc0bebfee139?name=CoSMoS_SoCalv3_Phase2_summary_of_methods.pdf). Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception to include the Channel Islands. Please read the Summary of Methods and inspect output carefully. Data are complete for the information presented.

Projected Hazard: Maximum depth of flooding surface (in cm) in the region landward of the present day shoreline that is inundated for the storm condition and sea-level rise (SLR) scenario indicated. Note: Duration datasets may have occasional gaps in open-coast sections. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the model summary and inspect output carefully. Data are complete for the information presented. Details: Model background: The CoSMoS model comprises three tiers. Tier I consists of one Delft3D hydrodynamics FLOW grid for computation of tides, water level variations, flows, and currents and one SWAN grid for computation of wave generation and propagation across the continental shelf. The FLOW and SWAN models are two-way coupled so that tidal currents are accounted for in wave propagation and growth and conversely, so that orbital velocities generated by waves impart changes on tidal currents. The Tier I SWAN and FLOW models consist of identical structured curvilinear grids that extend from far offshore to the shore and range in resolution from 0.5 km in the offshore to 0.2 km in the nearshore. Spatially varying astronomic tidal amplitudes and phases and steric rises in water levels due to large-scale effects (for example, a prolonged rise in sea level) are applied along all open boundaries of the Tier I FLOW grid. Winds (split into eastward and northward components) and sea-level pressure (SLP) fields from CaRD10 (Dr. Dan Cayan, Scripps Institute of Oceanography, Los Angeles, California, written commun., 2014) that vary in both space and time are applied to all grid cells at each model time-step. Deep-water wave conditions, applied at the open boundaries of the Tier I SWAN model runs, were projected for the 21st century Representative Concentration Pathway (RCP) 4.5 climate scenario (2011-2100) using the WaveWatch III numerical wave model (Tolman and others, 2002) and 3-hourly winds from the GFDL-ESM2M Global Climate Model (GCM). Tier II provides higher resolution near the shore and in areas that require greater resolution of physical processes (such as bays, harbors, and estuaries). A single nested outer grid and multiple two-way coupled domain decomposition (DD) structured grids allow for local grid refinement and higher resolution where needed. Tier II was segmented into 11 sections along the Southern California Bight, to reduce computation time and complete runs within computational limitations. Water-level and Neumann time-series, extracted from Tier I simulations, are applied to the shore-parallel and lateral open boundaries of each Tier II sub-model outer grid respectively. Several of the sub-models proved to be unstable with lateral Neumann boundaries; for those cases one or both of the lateral boundaries were converted to water-level time-series or left unassigned. The open-boundary time-series are extracted from completed Tier I simulations so that there is no communication from Tier II to Tier I. Because this one-way nesting could produce erroneous results near the boundaries of Tier II and because data near any model boundary are always suspect, Tier II sub-model extents were designed to overlap in the along-coast direction. In the landward direction, Tier II DD grids extend to the 10-m topographic contour; exceptions exist where channels (such as the Los Angeles River) or other low-lying regions extend very far inland. Space- and time-varying wind and SLP fields, identical to those used in Tier I simulations, are applied to all Tier II DD grids to allow for wind-setup and local inverse barometer effects (IBE, rise or depression of water levels in response to atmospheric pressure gradients). A total of 42 time-series fluvial discharges are included in the Tier II FLOW domains in an effort to simulate exacerbated flooding caused by backflow at the confluence of high river seaward flows and elevated coastal surge levels migrating inland. Time-varying fluvial discharges are applied either at the closed boundaries or distributed as point sources within the relevant model domains. Wave computations are accomplished with the SWAN model using two grids for each Tier II sub-model: one larger grid covering the same area as the outer FLOW grid and a second finer resolution two-way coupled nearshore nested grid. The nearshore grid extends from approximately 800-1,000 m water depth up to 8-10 m elevations onshore. The landward extension is included to allow for wave computations of the higher SLR scenarios. Time- and space-varying 2D wave spectra extracted from previously completed Tier I simulations are applied approximately every kilometer along the open boundaries of the outer Tier II sub-model SWAN grids. The same space- and time-varying wind fields used in Tier I simulations are also applied to both Tier II SWAN grids to allow for computation of local wave generation. Tier III for the entire Southern California Bight consists of 4,802 cross-shore transects (CST) spaced approximately 100 m apart in the along-shore direction. The profiles extend from the -15 m isobath to at least 10 m above NAVD88. The CSTs are truncated for cases where a lagoon or other waterway exists on the landward end of the profile. Time-varying water levels and wave parameters (significant wave heights, Hs; peak periods, Tp; and peak incident wave directions, Dp), extracted from Tier II grid cells that coincide with the seaward end of the CSTs, are applied at the open boundary of each CST. The XBeach model is run in a hydrostatic (no vertical pressure gradients) mode including event-based morphodynamic change. Wave propagation, two-way wave-current interaction, water-level variations, and wave runup are computed at each transect. XBeach simulations are included in the CoSMoS model to account for infragravity waves that can significantly extend the reach of wave runup (Roelvink and others, 2009) compared to short-wave incident waves. The U.S. west coast is particularly susceptible to infragravity waves at the shore due to breaking of long-period swell waves (Tp > 15). Resulting water levels (WLs) from both Delft3D (high interest bays and marshes) and open-coast XBeach (CSTs) were spatially combined and interpolated to a 10 m grid. These WL elevations are differenced from the originating 2 m digital elevation model (DEM) to determine final flooding extent and depth of flooding. Events: The model system is run for pre-determined scenarios of interest such as the 1-yr or 100-yr storm event in combination with sea-level rise. Storms are first identified from time-series of total water level proxies (TWLpx) at the shore. TWLpx are computed for the majority of the 21st century (2010-2100), assuming a linear super-position of the major processes that contribute to the overall total water level. TWLpx time-series are then evaluated for extreme events, which define the boundary conditions for subsequent modeling with CoSMoS. Multiple 100-yr events are determined (varying Hs, Tp, Dp) and used for multiple model runs to better account for regional and directional flooding affects. Model results are combined and compiled into scenario-specific composites of flood projection. Digital Elevation Model (DEM): Our seamless, topobathymetric digital elevation model (DEM) was based largely upon the Coastal California TopoBathy Merge Project DEM, with some modifications performed by the USGS Earth Resources Observation and Science (EROS) Center to incorporate the most recent, high-resolution topographic and bathymetric datasets available. Topography is derived from bare-earth light detection and ranging (lidar) data collected in 2009-2011 for the CA Coastal Conservancy Lidar Project and bathymetry from 2009-2010 bathymetric lidar as well as acoustic multi- and single-beam data collected primarily between 2001 and 2013. The DEM was constructed to define the shape of nearshore, beach, and cliff surfaces as accurately as possible, utilizing dozens of bathymetric and topographic data sets. These data were used to populate the majority of the Tier I and II grids. To describe and include impacts from long-term shoreline evolution, including cumulative storm activity, seasonal trends, ENSO, and SLR, the DEM was modified for each SLR scenario. Long-term shoreline (Vitousek and Barnard, 2015) and cliff (Limber and others, 2015) erosion projections were efficiently combined along the cross-shore transects to evolve the shore-normal profiles. Elevation changes from the profiles were spatially-merged for a cohesive, 3D depiction of coastal evolution used to modify the DEM. These data are used to generate initial profiles of the 4,802 CSTs used for Phase 2 Tier III XBeach modeling and determining final projected flood depths in each SLR scenario. All data are referenced to NAD83 horizontal datum and NAVD88 vertical datum. Data for Tiers II and III are projected in UTM, zone 11. Outputs include: Projected flood-hazard depth and duration for the storm and sea-level rise indicated. Data correspond to the areas vulnerable to coastal flooding due to storm surge, sea-level anomalies, tide elevation, and wave run-up during the same storm and sea-level rise simulation. References Cited: Howell, S., Smith-Konter, B., Frazer, N., Tong, X., and Sandwell, D., 2016, The vertical fingerprint of earthquake cycle loading in southern California: Nature Geoscience, v. 9, p. 611-614, doi:10.1038/ngeo2741. Limber, P., Barnard, P.L. and Hapke., C., 2015, Towards projecting the retreat of California’s coastal cliffs during the 21st Century: in, Wang, P., Rosati, J.D., and Cheng, J., (eds.), The Proceedings of the Coastal Sediments: 2015, World Scientific, 14 p., doi:10.1142/9789814689977_0245 Roelvink, J.A., Reniers, A., van Dongeren, A.R., van Thiel de Vries, J., McCall, R., and Lescinski, J., 2009, Modeling storm impacts on beaches, dunes and barrier islands: Coastal Engineering, v. 56, p. 1,133–1,152, doi:10.1016/j.coastaleng.2009.08.006. Tolman, H.L., Balasubramaniyan, B., Burroughs, L.D., Chalikov, D.V., Chao, Y.Y., Chen H.S., Gerald, V.M., 2002, Development and implementation of wind generated ocean surface wave models at NCEP: Weather and Forecasting, v. 17, p. 311-333. Vitousek, S. and Barnard, P.L., 2015, A non-linear, implicit one-line model to predict long-term shoreline change: in, Wang, P., Rosati, J.D., and Cheng, J., (eds.), The Proceedings of the Coastal Sediments: 2015, World Scientific, 14 p., doi:10.1142/9789814689977_0215.

Projected Hazard: Maximum depth of flooding surface (in cm) in the region landward of the present day shoreline that is inundated for the storm condition and sea-level rise (SLR) scenario indicated. Note: Duration datasets may have occasional gaps in open-coast sections. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the model summary and inspect output carefully. Data are complete for the information presented. Details: Model background: The CoSMoS model comprises three tiers. Tier I consists of one Delft3D hydrodynamics FLOW grid for computation of tides, water level variations, flows, and currents and one SWAN grid for computation of wave generation and propagation across the continental shelf. The FLOW and SWAN models are two-way coupled so that tidal currents are accounted for in wave propagation and growth and conversely, so that orbital velocities generated by waves impart changes on tidal currents. The Tier I SWAN and FLOW models consist of identical structured curvilinear grids that extend from far offshore to the shore and range in resolution from 0.5 km in the offshore to 0.2 km in the nearshore. Spatially varying astronomic tidal amplitudes and phases and steric rises in water levels due to large-scale effects (for example, a prolonged rise in sea level) are applied along all open boundaries of the Tier I FLOW grid. Winds (split into eastward and northward components) and sea-level pressure (SLP) fields from CaRD10 (Dr. Dan Cayan, Scripps Institute of Oceanography, Los Angeles, California, written commun., 2014) that vary in both space and time are applied to all grid cells at each model time-step. Deep-water wave conditions, applied at the open boundaries of the Tier I SWAN model runs, were projected for the 21st century Representative Concentration Pathway (RCP) 4.5 climate scenario (2011-2100) using the WaveWatch III numerical wave model (Tolman and others, 2002) and 3-hourly winds from the GFDL-ESM2M Global Climate Model (GCM). Tier II provides higher resolution near the shore and in areas that require greater resolution of physical processes (such as bays, harbors, and estuaries). A single nested outer grid and multiple two-way coupled domain decomposition (DD) structured grids allow for local grid refinement and higher resolution where needed. Tier II was segmented into 11 sections along the Southern California Bight, to reduce computation time and complete runs within computational limitations. Water-level and Neumann time-series, extracted from Tier I simulations, are applied to the shore-parallel and lateral open boundaries of each Tier II sub-model outer grid respectively. Several of the sub-models proved to be unstable with lateral Neumann boundaries; for those cases one or both of the lateral boundaries were converted to water-level time-series or left unassigned. The open-boundary time-series are extracted from completed Tier I simulations so that there is no communication from Tier II to Tier I. Because this one-way nesting could produce erroneous results near the boundaries of Tier II and because data near any model boundary are always suspect, Tier II sub-model extents were designed to overlap in the along-coast direction. In the landward direction, Tier II DD grids extend to the 10-m topographic contour; exceptions exist where channels (such as the Los Angeles River) or other low-lying regions extend very far inland. Space- and time-varying wind and SLP fields, identical to those used in Tier I simulations, are applied to all Tier II DD grids to allow for wind-setup and local inverse barometer effects (IBE, rise or depression of water levels in response to atmospheric pressure gradients). A total of 42 time-series fluvial discharges are included in the Tier II FLOW domains in an effort to simulate exacerbated flooding caused by backflow at the confluence of high river seaward flows and elevated coastal surge levels migrating inland. Time-varying fluvial discharges are applied either at the closed boundaries or distributed as point sources within the relevant model domains. Wave computations are accomplished with the SWAN model using two grids for each Tier II sub-model: one larger grid covering the same area as the outer FLOW grid and a second finer resolution two-way coupled nearshore nested grid. The nearshore grid extends from approximately 800-1,000 m water depth up to 8-10 m elevations onshore. The landward extension is included to allow for wave computations of the higher SLR scenarios. Time- and space-varying 2D wave spectra extracted from previously completed Tier I simulations are applied approximately every kilometer along the open boundaries of the outer Tier II sub-model SWAN grids. The same space- and time-varying wind fields used in Tier I simulations are also applied to both Tier II SWAN grids to allow for computation of local wave generation. Tier III for the entire Southern California Bight consists of 4,802 cross-shore transects (CST) spaced approximately 100 m apart in the along-shore direction. The profiles extend from the -15 m isobath to at least 10 m above NAVD88. The CSTs are truncated for cases where a lagoon or other waterway exists on the landward end of the profile. Time-varying water levels and wave parameters (significant wave heights, Hs; peak periods, Tp; and peak incident wave directions, Dp), extracted from Tier II grid cells that coincide with the seaward end of the CSTs, are applied at the open boundary of each CST. The XBeach model is run in a hydrostatic (no vertical pressure gradients) mode including event-based morphodynamic change. Wave propagation, two-way wave-current interaction, water-level variations, and wave runup are computed at each transect. XBeach simulations are included in the CoSMoS model to account for infragravity waves that can significantly extend the reach of wave runup (Roelvink and others, 2009) compared to short-wave incident waves. The U.S. west coast is particularly susceptible to infragravity waves at the shore due to breaking of long-period swell waves (Tp > 15). Resulting water levels (WLs) from both Delft3D (high interest bays and marshes) and open-coast XBeach (CSTs) were spatially combined and interpolated to a 10 m grid. These WL elevations are differenced from the originating 2 m digital elevation model (DEM) to determine final flooding extent and depth of flooding. Events: The model system is run for pre-determined scenarios of interest such as the 1-yr or 100-yr storm event in combination with sea-level rise. Storms are first identified from time-series of total water level proxies (TWLpx) at the shore. TWLpx are computed for the majority of the 21st century (2010-2100), assuming a linear super-position of the major processes that contribute to the overall total water level. TWLpx time-series are then evaluated for extreme events, which define the boundary conditions for subsequent modeling with CoSMoS. Multiple 100-yr events are determined (varying Hs, Tp, Dp) and used for multiple model runs to better account for regional and directional flooding affects. Model results are combined and compiled into scenario-specific composites of flood projection. Digital Elevation Model (DEM): Our seamless, topobathymetric digital elevation model (DEM) was based largely upon the Coastal California TopoBathy Merge Project DEM, with some modifications performed by the USGS Earth Resources Observation and Science (EROS) Center to incorporate the most recent, high-resolution topographic and bathymetric datasets available. Topography is derived from bare-earth light detection and ranging (lidar) data collected in 2009-2011 for the CA Coastal Conservancy Lidar Project and bathymetry from 2009-2010 bathymetric lidar as well as acoustic multi- and single-beam data collected primarily between 2001 and 2013. The DEM was constructed to define the shape of nearshore, beach, and cliff surfaces as accurately as possible, utilizing dozens of bathymetric and topographic data sets. These data were used to populate the majority of the Tier I and II grids. To describe and include impacts from long-term shoreline evolution, including cumulative storm activity, seasonal trends, ENSO, and SLR, the DEM was modified for each SLR scenario. Long-term shoreline (Vitousek and Barnard, 2015) and cliff (Limber and others, 2015) erosion projections were efficiently combined along the cross-shore transects to evolve the shore-normal profiles. Elevation changes from the profiles were spatially-merged for a cohesive, 3D depiction of coastal evolution used to modify the DEM. These data are used to generate initial profiles of the 4,802 CSTs used for Phase 2 Tier III XBeach modeling and determining final projected flood depths in each SLR scenario. All data are referenced to NAD83 horizontal datum and NAVD88 vertical datum. Data for Tiers II and III are projected in UTM, zone 11. Outputs include: Projected flood-hazard depth and duration for the storm and sea-level rise indicated. Data correspond to the areas vulnerable to coastal flooding due to storm surge, sea-level anomalies, tide elevation, and wave run-up during the same storm and sea-level rise simulation. References Cited: Howell, S., Smith-Konter, B., Frazer, N., Tong, X., and Sandwell, D., 2016, The vertical fingerprint of earthquake cycle loading in southern California: Nature Geoscience, v. 9, p. 611-614, doi:10.1038/ngeo2741. Limber, P., Barnard, P.L. and Hapke., C., 2015, Towards projecting the retreat of California’s coastal cliffs during the 21st Century: in, Wang, P., Rosati, J.D., and Cheng, J., (eds.), The Proceedings of the Coastal Sediments: 2015, World Scientific, 14 p., doi:10.1142/9789814689977_0245 Roelvink, J.A., Reniers, A., van Dongeren, A.R., van Thiel de Vries, J., McCall, R., and Lescinski, J., 2009, Modeling storm impacts on beaches, dunes and barrier islands: Coastal Engineering, v. 56, p. 1,133–1,152, doi:10.1016/j.coastaleng.2009.08.006. Tolman, H.L., Balasubramaniyan, B., Burroughs, L.D., Chalikov, D.V., Chao, Y.Y., Chen H.S., Gerald, V.M., 2002, Development and implementation of wind generated ocean surface wave models at NCEP: Weather and Forecasting, v. 17, p. 311-333. Vitousek, S. and Barnard, P.L., 2015, A non-linear, implicit one-line model to predict long-term shoreline change: in, Wang, P., Rosati, J.D., and Cheng, J., (eds.), The Proceedings of the Coastal Sediments: 2015, World Scientific, 14 p., doi:10.1142/9789814689977_0215.

Projected Hazard: Maximum depth of flooding surface (in cm) in the region landward of the present day shoreline that is inundated for the storm condition and sea-level rise (SLR) scenario indicated. Note: Duration datasets may have occasional gaps in open-coast sections. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the model summary and inspect output carefully. Data are complete for the information presented. Details: Model background: The CoSMoS model comprises three tiers. Tier I consists of one Delft3D hydrodynamics FLOW grid for computation of tides, water level variations, flows, and currents and one SWAN grid for computation of wave generation and propagation across the continental shelf. The FLOW and SWAN models are two-way coupled so that tidal currents are accounted for in wave propagation and growth and conversely, so that orbital velocities generated by waves impart changes on tidal currents. The Tier I SWAN and FLOW models consist of identical structured curvilinear grids that extend from far offshore to the shore and range in resolution from 0.5 km in the offshore to 0.2 km in the nearshore. Spatially varying astronomic tidal amplitudes and phases and steric rises in water levels due to large-scale effects (for example, a prolonged rise in sea level) are applied along all open boundaries of the Tier I FLOW grid. Winds (split into eastward and northward components) and sea-level pressure (SLP) fields from CaRD10 (Dr. Dan Cayan, Scripps Institute of Oceanography, Los Angeles, California, written commun., 2014) that vary in both space and time are applied to all grid cells at each model time-step. Deep-water wave conditions, applied at the open boundaries of the Tier I SWAN model runs, were projected for the 21st century Representative Concentration Pathway (RCP) 4.5 climate scenario (2011-2100) using the WaveWatch III numerical wave model (Tolman and others, 2002) and 3-hourly winds from the GFDL-ESM2M Global Climate Model (GCM). Tier II provides higher resolution near the shore and in areas that require greater resolution of physical processes (such as bays, harbors, and estuaries). A single nested outer grid and multiple two-way coupled domain decomposition (DD) structured grids allow for local grid refinement and higher resolution where needed. Tier II was segmented into 11 sections along the Southern California Bight, to reduce computation time and complete runs within computational limitations. Water-level and Neumann time-series, extracted from Tier I simulations, are applied to the shore-parallel and lateral open boundaries of each Tier II sub-model outer grid respectively. Several of the sub-models proved to be unstable with lateral Neumann boundaries; for those cases one or both of the lateral boundaries were converted to water-level time-series or left unassigned. The open-boundary time-series are extracted from completed Tier I simulations so that there is no communication from Tier II to Tier I. Because this one-way nesting could produce erroneous results near the boundaries of Tier II and because data near any model boundary are always suspect, Tier II sub-model extents were designed to overlap in the along-coast direction. In the landward direction, Tier II DD grids extend to the 10-m topographic contour; exceptions exist where channels (such as the Los Angeles River) or other low-lying regions extend very far inland. Space- and time-varying wind and SLP fields, identical to those used in Tier I simulations, are applied to all Tier II DD grids to allow for wind-setup and local inverse barometer effects (IBE, rise or depression of water levels in response to atmospheric pressure gradients). A total of 42 time-series fluvial discharges are included in the Tier II FLOW domains in an effort to simulate exacerbated flooding caused by backflow at the confluence of high river seaward flows and elevated coastal surge levels migrating inland. Time-varying fluvial discharges are applied either at the closed boundaries or distributed as point sources within the relevant model domains. Wave computations are accomplished with the SWAN model using two grids for each Tier II sub-model: one larger grid covering the same area as the outer FLOW grid and a second finer resolution two-way coupled nearshore nested grid. The nearshore grid extends from approximately 800-1,000 m water depth up to 8-10 m elevations onshore. The landward extension is included to allow for wave computations of the higher SLR scenarios. Time- and space-varying 2D wave spectra extracted from previously completed Tier I simulations are applied approximately every kilometer along the open boundaries of the outer Tier II sub-model SWAN grids. The same space- and time-varying wind fields used in Tier I simulations are also applied to both Tier II SWAN grids to allow for computation of local wave generation. Tier III for the entire Southern California Bight consists of 4,802 cross-shore transects (CST) spaced approximately 100 m apart in the along-shore direction. The profiles extend from the -15 m isobath to at least 10 m above NAVD88. The CSTs are truncated for cases where a lagoon or other waterway exists on the landward end of the profile. Time-varying water levels and wave parameters (significant wave heights, Hs; peak periods, Tp; and peak incident wave directions, Dp), extracted from Tier II grid cells that coincide with the seaward end of the CSTs, are applied at the open boundary of each CST. The XBeach model is run in a hydrostatic (no vertical pressure gradients) mode including event-based morphodynamic change. Wave propagation, two-way wave-current interaction, water-level variations, and wave runup are computed at each transect. XBeach simulations are included in the CoSMoS model to account for infragravity waves that can significantly extend the reach of wave runup (Roelvink and others, 2009) compared to short-wave incident waves. The U.S. west coast is particularly susceptible to infragravity waves at the shore due to breaking of long-period swell waves (Tp > 15). Resulting water levels (WLs) from both Delft3D (high interest bays and marshes) and open-coast XBeach (CSTs) were spatially combined and interpolated to a 10 m grid. These WL elevations are differenced from the originating 2 m digital elevation model (DEM) to determine final flooding extent and depth of flooding. Events: The model system is run for pre-determined scenarios of interest such as the 1-yr or 100-yr storm event in combination with sea-level rise. Storms are first identified from time-series of total water level proxies (TWLpx) at the shore. TWLpx are computed for the majority of the 21st century (2010-2100), assuming a linear super-position of the major processes that contribute to the overall total water level. TWLpx time-series are then evaluated for extreme events, which define the boundary conditions for subsequent modeling with CoSMoS. Multiple 100-yr events are determined (varying Hs, Tp, Dp) and used for multiple model runs to better account for regional and directional flooding affects. Model results are combined and compiled into scenario-specific composites of flood projection. Digital Elevation Model (DEM): Our seamless, topobathymetric digital elevation model (DEM) was based largely upon the Coastal California TopoBathy Merge Project DEM, with some modifications performed by the USGS Earth Resources Observation and Science (EROS) Center to incorporate the most recent, high-resolution topographic and bathymetric datasets available. Topography is derived from bare-earth light detection and ranging (lidar) data collected in 2009-2011 for the CA Coastal Conservancy Lidar Project and bathymetry from 2009-2010 bathymetric lidar as well as acoustic multi- and single-beam data collected primarily between 2001 and 2013. The DEM was constructed to define the shape of nearshore, beach, and cliff surfaces as accurately as possible, utilizing dozens of bathymetric and topographic data sets. These data were used to populate the majority of the Tier I and II grids. To describe and include impacts from long-term shoreline evolution, including cumulative storm activity, seasonal trends, ENSO, and SLR, the DEM was modified for each SLR scenario. Long-term shoreline (Vitousek and Barnard, 2015) and cliff (Limber and others, 2015) erosion projections were efficiently combined along the cross-shore transects to evolve the shore-normal profiles. Elevation changes from the profiles were spatially-merged for a cohesive, 3D depiction of coastal evolution used to modify the DEM. These data are used to generate initial profiles of the 4,802 CSTs used for Phase 2 Tier III XBeach modeling and determining final projected flood depths in each SLR scenario. All data are referenced to NAD83 horizontal datum and NAVD88 vertical datum. Data for Tiers II and III are projected in UTM, zone 11. Outputs include: Projected flood-hazard depth and duration for the storm and sea-level rise indicated. Data correspond to the areas vulnerable to coastal flooding due to storm surge, sea-level anomalies, tide elevation, and wave run-up during the same storm and sea-level rise simulation. References Cited: Howell, S., Smith-Konter, B., Frazer, N., Tong, X., and Sandwell, D., 2016, The vertical fingerprint of earthquake cycle loading in southern California: Nature Geoscience, v. 9, p. 611-614, doi:10.1038/ngeo2741. Limber, P., Barnard, P.L. and Hapke., C., 2015, Towards projecting the retreat of California’s coastal cliffs during the 21st Century: in, Wang, P., Rosati, J.D., and Cheng, J., (eds.), The Proceedings of the Coastal Sediments: 2015, World Scientific, 14 p., doi:10.1142/9789814689977_0245 Roelvink, J.A., Reniers, A., van Dongeren, A.R., van Thiel de Vries, J., McCall, R., and Lescinski, J., 2009, Modeling storm impacts on beaches, dunes and barrier islands: Coastal Engineering, v. 56, p. 1,133–1,152, doi:10.1016/j.coastaleng.2009.08.006. Tolman, H.L., Balasubramaniyan, B., Burroughs, L.D., Chalikov, D.V., Chao, Y.Y., Chen H.S., Gerald, V.M., 2002, Development and implementation of wind generated ocean surface wave models at NCEP: Weather and Forecasting, v. 17, p. 311-333. Vitousek, S. and Barnard, P.L., 2015, A non-linear, implicit one-line model to predict long-term shoreline change: in, Wang, P., Rosati, J.D., and Cheng, J., (eds.), The Proceedings of the Coastal Sediments: 2015, World Scientific, 14 p., doi:10.1142/9789814689977_0215.

Projected Hazard: Maximum depth of flooding surface (in cm) in the region landward of the present day shoreline that is inundated for the storm condition and sea-level rise (SLR) scenario indicated. Note: Duration datasets may have occasional gaps in open-coast sections. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the model summary and inspect output carefully. Data are complete for the information presented. Details: Model background: The CoSMoS model comprises three tiers. Tier I consists of one Delft3D hydrodynamics FLOW grid for computation of tides, water level variations, flows, and currents and one SWAN grid for computation of wave generation and propagation across the continental shelf. The FLOW and SWAN models are two-way coupled so that tidal currents are accounted for in wave propagation and growth and conversely, so that orbital velocities generated by waves impart changes on tidal currents. The Tier I SWAN and FLOW models consist of identical structured curvilinear grids that extend from far offshore to the shore and range in resolution from 0.5 km in the offshore to 0.2 km in the nearshore. Spatially varying astronomic tidal amplitudes and phases and steric rises in water levels due to large-scale effects (for example, a prolonged rise in sea level) are applied along all open boundaries of the Tier I FLOW grid. Winds (split into eastward and northward components) and sea-level pressure (SLP) fields from CaRD10 (Dr. Dan Cayan, Scripps Institute of Oceanography, Los Angeles, California, written commun., 2014) that vary in both space and time are applied to all grid cells at each model time-step. Deep-water wave conditions, applied at the open boundaries of the Tier I SWAN model runs, were projected for the 21st century Representative Concentration Pathway (RCP) 4.5 climate scenario (2011-2100) using the WaveWatch III numerical wave model (Tolman and others, 2002) and 3-hourly winds from the GFDL-ESM2M Global Climate Model (GCM). Tier II provides higher resolution near the shore and in areas that require greater resolution of physical processes (such as bays, harbors, and estuaries). A single nested outer grid and multiple two-way coupled domain decomposition (DD) structured grids allow for local grid refinement and higher resolution where needed. Tier II was segmented into 11 sections along the Southern California Bight, to reduce computation time and complete runs within computational limitations. Water-level and Neumann time-series, extracted from Tier I simulations, are applied to the shore-parallel and lateral open boundaries of each Tier II sub-model outer grid respectively. Several of the sub-models proved to be unstable with lateral Neumann boundaries; for those cases one or both of the lateral boundaries were converted to water-level time-series or left unassigned. The open-boundary time-series are extracted from completed Tier I simulations so that there is no communication from Tier II to Tier I. Because this one-way nesting could produce erroneous results near the boundaries of Tier II and because data near any model boundary are always suspect, Tier II sub-model extents were designed to overlap in the along-coast direction. In the landward direction, Tier II DD grids extend to the 10-m topographic contour; exceptions exist where channels (such as the Los Angeles River) or other low-lying regions extend very far inland. Space- and time-varying wind and SLP fields, identical to those used in Tier I simulations, are applied to all Tier II DD grids to allow for wind-setup and local inverse barometer effects (IBE, rise or depression of water levels in response to atmospheric pressure gradients). A total of 42 time-series fluvial discharges are included in the Tier II FLOW domains in an effort to simulate exacerbated flooding caused by backflow at the confluence of high river seaward flows and elevated coastal surge levels migrating inland. Time-varying fluvial discharges are applied either at the closed boundaries or distributed as point sources within the relevant model domains. Wave computations are accomplished with the SWAN model using two grids for each Tier II sub-model: one larger grid covering the same area as the outer FLOW grid and a second finer resolution two-way coupled nearshore nested grid. The nearshore grid extends from approximately 800-1,000 m water depth up to 8-10 m elevations onshore. The landward extension is included to allow for wave computations of the higher SLR scenarios. Time- and space-varying 2D wave spectra extracted from previously completed Tier I simulations are applied approximately every kilometer along the open boundaries of the outer Tier II sub-model SWAN grids. The same space- and time-varying wind fields used in Tier I simulations are also applied to both Tier II SWAN grids to allow for computation of local wave generation. Tier III for the entire Southern California Bight consists of 4,802 cross-shore transects (CST) spaced approximately 100 m apart in the along-shore direction. The profiles extend from the -15 m isobath to at least 10 m above NAVD88. The CSTs are truncated for cases where a lagoon or other waterway exists on the landward end of the profile. Time-varying water levels and wave parameters (significant wave heights, Hs; peak periods, Tp; and peak incident wave directions, Dp), extracted from Tier II grid cells that coincide with the seaward end of the CSTs, are applied at the open boundary of each CST. The XBeach model is run in a hydrostatic (no vertical pressure gradients) mode including event-based morphodynamic change. Wave propagation, two-way wave-current interaction, water-level variations, and wave runup are computed at each transect. XBeach simulations are included in the CoSMoS model to account for infragravity waves that can significantly extend the reach of wave runup (Roelvink and others, 2009) compared to short-wave incident waves. The U.S. west coast is particularly susceptible to infragravity waves at the shore due to breaking of long-period swell waves (Tp > 15). Resulting water levels (WLs) from both Delft3D (high interest bays and marshes) and open-coast XBeach (CSTs) were spatially combined and interpolated to a 10 m grid. These WL elevations are differenced from the originating 2 m digital elevation model (DEM) to determine final flooding extent and depth of flooding. Events: The model system is run for pre-determined scenarios of interest such as the 1-yr or 100-yr storm event in combination with sea-level rise. Storms are first identified from time-series of total water level proxies (TWLpx) at the shore. TWLpx are computed for the majority of the 21st century (2010-2100), assuming a linear super-position of the major processes that contribute to the overall total water level. TWLpx time-series are then evaluated for extreme events, which define the boundary conditions for subsequent modeling with CoSMoS. Multiple 100-yr events are determined (varying Hs, Tp, Dp) and used for multiple model runs to better account for regional and directional flooding affects. Model results are combined and compiled into scenario-specific composites of flood projection. Digital Elevation Model (DEM): Our seamless, topobathymetric digital elevation model (DEM) was based largely upon the Coastal California TopoBathy Merge Project DEM, with some modifications performed by the USGS Earth Resources Observation and Science (EROS) Center to incorporate the most recent, high-resolution topographic and bathymetric datasets available. Topography is derived from bare-earth light detection and ranging (lidar) data collected in 2009-2011 for the CA Coastal Conservancy Lidar Project and bathymetry from 2009-2010 bathymetric lidar as well as acoustic multi- and single-beam data collected primarily between 2001 and 2013. The DEM was constructed to define the shape of nearshore, beach, and cliff surfaces as accurately as possible, utilizing dozens of bathymetric and topographic data sets. These data were used to populate the majority of the Tier I and II grids. To describe and include impacts from long-term shoreline evolution, including cumulative storm activity, seasonal trends, ENSO, and SLR, the DEM was modified for each SLR scenario. Long-term shoreline (Vitousek and Barnard, 2015) and cliff (Limber and others, 2015) erosion projections were efficiently combined along the cross-shore transects to evolve the shore-normal profiles. Elevation changes from the profiles were spatially-merged for a cohesive, 3D depiction of coastal evolution used to modify the DEM. These data are used to generate initial profiles of the 4,802 CSTs used for Phase 2 Tier III XBeach modeling and determining final projected flood depths in each SLR scenario. All data are referenced to NAD83 horizontal datum and NAVD88 vertical datum. Data for Tiers II and III are projected in UTM, zone 11. Outputs include: Projected flood-hazard depth and duration for the storm and sea-level rise indicated. Data correspond to the areas vulnerable to coastal flooding due to storm surge, sea-level anomalies, tide elevation, and wave run-up during the same storm and sea-level rise simulation. References Cited: Howell, S., Smith-Konter, B., Frazer, N., Tong, X., and Sandwell, D., 2016, The vertical fingerprint of earthquake cycle loading in southern California: Nature Geoscience, v. 9, p. 611-614, doi:10.1038/ngeo2741. Limber, P., Barnard, P.L. and Hapke., C., 2015, Towards projecting the retreat of California’s coastal cliffs during the 21st Century: in, Wang, P., Rosati, J.D., and Cheng, J., (eds.), The Proceedings of the Coastal Sediments: 2015, World Scientific, 14 p., doi:10.1142/9789814689977_0245 Roelvink, J.A., Reniers, A., van Dongeren, A.R., van Thiel de Vries, J., McCall, R., and Lescinski, J., 2009, Modeling storm impacts on beaches, dunes and barrier islands: Coastal Engineering, v. 56, p. 1,133–1,152, doi:10.1016/j.coastaleng.2009.08.006. Tolman, H.L., Balasubramaniyan, B., Burroughs, L.D., Chalikov, D.V., Chao, Y.Y., Chen H.S., Gerald, V.M., 2002, Development and implementation of wind generated ocean surface wave models at NCEP: Weather and Forecasting, v. 17, p. 311-333. Vitousek, S. and Barnard, P.L., 2015, A non-linear, implicit one-line model to predict long-term shoreline change: in, Wang, P., Rosati, J.D., and Cheng, J., (eds.), The Proceedings of the Coastal Sediments: 2015, World Scientific, 14 p., doi:10.1142/9789814689977_0215.

Projected Hazard: Geographic extent of projected coastal flooding, low-lying vulnerable areas, and maxium/minimum flood potential (flood uncertainty) associated with the sea-level rise and storm condition indicated. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the model summary and inspect output carefully. Data are complete for the information presented. Details: Model background: The CoSMoS model comprises three tiers. Tier I consists of one Delft3D hydrodynamics FLOW grid for computation of tides, water level variations, flows, and currents and one SWAN grid for computation of wave generation and propagation across the continental shelf. The FLOW and SWAN models are two-way coupled so that tidal currents are accounted for in wave propagation and growth and conversely, so that orbital velocities generated by waves impart changes on tidal currents. The Tier I SWAN and FLOW models consist of identical structured curvilinear grids that extend from far offshore to the shore and range in resolution from 0.5 km in the offshore to 0.2 km in the nearshore. Spatially varying astronomic tidal amplitudes and phases and steric rises in water levels due to large-scale effects (for example, a prolonged rise in sea level) are applied along all open boundaries of the Tier I FLOW grid. Winds (split into eastward and northward components) and sea-level pressure (SLP) fields from CaRD10 (Dr. Dan Cayan, Scripps Institute of Oceanography, Los Angeles, California, written commun., 2014) that vary in both space and time are applied to all grid cells at each model time-step. Deep-water wave conditions, applied at the open boundaries of the Tier I SWAN model runs, were projected for the 21st century Representative Concentration Pathway (RCP) 4.5 climate scenario (2011-2100) using the WaveWatch III numerical wave model (Tolman and others, 2002) and 3-hourly winds from the GFDL-ESM2M Global Climate Model (GCM). Tier II provides higher resolution near the shore and in areas that require greater resolution of physical processes (such as bays, harbors, and estuaries). A single nested outer grid and multiple two-way coupled domain decomposition (DD) structured grids allow for local grid refinement and higher resolution where needed. Tier II was segmented into 11 sections along the Southern California Bight, to reduce computation time and complete runs within computational limitations. Water-level and Neumann time-series, extracted from Tier I simulations, are applied to the shore-parallel and lateral open boundaries of each Tier II sub-model outer grid respectively. Several of the sub-models proved to be unstable with lateral Neumann boundaries; for those cases one or both of the lateral boundaries were converted to water-level time-series or left unassigned. The open-boundary time-series are extracted from completed Tier I simulations so that there is no communication from Tier II to Tier I. Because this one-way nesting could produce erroneous results near the boundaries of Tier II and because data near any model boundary are always suspect, Tier II sub-model extents were designed to overlap in the along-coast direction. In the landward direction, Tier II DD grids extend to the 10-m topographic contour; exceptions exist where channels (such as the Los Angeles River) or other low-lying regions extend very far inland. Space- and time-varying wind and SLP fields, identical to those used in Tier I simulations, are applied to all Tier II DD grids to allow for wind-setup and local inverse barometer effects (IBE, rise or depression of water levels in response to atmospheric pressure gradients). A total of 42 time-series fluvial discharges are included in the Tier II FLOW domains in an effort to simulate exacerbated flooding caused by backflow at the confluence of high river seaward flows and elevated coastal surge levels migrating inland. Time-varying fluvial discharges are applied either at the closed boundaries or distributed as point sources within the relevant model domains. Wave computations are accomplished with the SWAN model using two grids for each Tier II sub-model: one larger grid covering the same area as the outer FLOW grid and a second finer resolution two-way coupled nearshore nested grid. The nearshore grid extends from approximately 800-1,000 m water depth up to 8-10 m elevations onshore. The landward extension is included to allow for wave computations of the higher SLR scenarios. Time- and space-varying 2D wave spectra extracted from previously completed Tier I simulations are applied approximately every kilometer along the open boundaries of the outer Tier II sub-model SWAN grids. The same space- and time-varying wind fields used in Tier I simulations are also applied to both Tier II SWAN grids to allow for computation of local wave generation. Tier III for the entire Southern California Bight consists of 4,802 cross-shore transects (CST) spaced approximately 100 m apart in the along-shore direction. The profiles extend from the -15 m isobath to at least 10 m above NAVD88. The CSTs are truncated for cases where a lagoon or other waterway exists on the landward end of the profile. Time-varying water levels and wave parameters (significant wave heights, Hs; peak periods, Tp; and peak incident wave directions, Dp), extracted from Tier II grid cells that coincide with the seaward end of the CSTs, are applied at the open boundary of each CST. The XBeach model is run in a hydrostatic (no vertical pressure gradients) mode including event-based morphodynamic change. Wave propagation, two-way wave-current interaction, water-level variations, and wave runup are computed at each transect. XBeach simulations are included in the CoSMoS model to account for infragravity waves that can significantly extend the reach of wave runup (Roelvink and others, 2009) compared to short-wave incident waves. The U.S. west coast is particularly susceptible to infragravity waves at the shore due to breaking of long-period swell waves (Tp > 15). Resulting water levels (WLs) from both Delft3D (high interest bays and marshes) and open-coast XBeach (CSTs) were spatially combined and interpolated to a 10 m grid. These WL elevations are differenced from the originating 2 m digital elevation model (DEM) to determine final flooding extent and depth of flooding. Events: The model system is run for pre-determined scenarios of interest such as the 1-yr or 100-yr storm event in combination with sea-level rise. Storms are first identified from time-series of total water level proxies (TWLpx) at the shore. TWLpx are computed for the majority of the 21st century (2010-2100), assuming a linear super-position of the major processes that contribute to the overall total water level. TWLpx time-series are then evaluated for extreme events, which define the boundary conditions for subsequent modeling with CoSMoS. Multiple 100-yr events are determined (varying Hs, Tp, Dp) and used for multiple model runs to better account for regional and directional flooding affects. Model results are combined and compiled into scenario-specific composites of flood projection. Digital Elevation Model (DEM): Our seamless, topobathymetric digital elevation model (DEM) was based largely upon the Coastal California TopoBathy Merge Project DEM, with some modifications performed by the USGS Earth Resources Observation and Science (EROS) Center to incorporate the most recent, high-resolution topographic and bathymetric datasets available. Topography is derived from bare-earth light detection and ranging (lidar) data collected in 2009-2011 for the CA Coastal Conservancy Lidar Project and bathymetry from 2009-2010 bathymetric lidar as well as acoustic multi- and single-beam data collected primarily between 2001 and 2013. The DEM was constructed to define the shape of nearshore, beach, and cliff surfaces as accurately as possible, utilizing dozens of bathymetric and topographic data sets. These data were used to populate the majority of the tier I and II grids. To describe and include impacts from long-term shoreline evolution, including cumulative storm activity, seasonal trends, ENSO, and SLR, the DEM was modified for each SLR scenario. Long-term shoreline (Vitousek and Barnard, 2015) and cliff (Limber et al., 2015) erosion projections were efficiently combined along the cross-shore transects to evolve the shore-normal profiles. Elevation changes from the profiles were spatially-merged for a cohesive, 3D depiction of coastal evolution used to modify the DEM. These data are used to generate initial profiles of the 4,802 CSTs used for Phase 2 tier III XBeach modeling and determining final projected flood depths in each SLR scenario. All data are referenced to NAD83 horizontal datum and NAVD88 vertical datum. Data for Tiers II and III are projected in UTM, zone 11. Outputs include: Areas of projected flood hazards: The area vulnerable to coastal flooding due to storm surge, sea-level anomalies, tide elevation, and wave run-up during the storm simulation, based on the maximum elevation of still-water level (inundation for several minutes) at each CST profile. Enclosed areas illustrate the projected water surface and is shown extending from offshore to the extent of coastal flooding for different SLR scenarios between 0 - 2.0 m (0.25 m increments), and at 5.0 m. Low-lying vulnerable areas depict locations where projections indicate flood potential but are not connected to the primary flood surface. Flood potential indicates the maximum and minimum areas of flooding extent considering accuracy of the DEM, hydrodynamic model accuracy, and vertical land motion (Howell et al., 2016). References Cited: Howell, S., Smith-Konter, B., Frazer, N., Tong, X., and Sandwell, D., 2016, The vertical fingerprint of earthquake cycle loading in southern California: Nature Geoscience, v. 9, p. 611-614, doi:10.1038/ngeo2741. Limber, P., Barnard, P.L. and Hapke., C., 2015, Towards projecting the retreat of California’s coastal cliffs during the 21st Century: in, Wang, P., Rosati, J.D., and Cheng, J., (eds.), The Proceedings of the Coastal Sediments: 2015, World Scientific, 14 p., doi:10.1142/9789814689977_0245 Roelvink, J.A., Reniers, A., van Dongeren, A.R., van Thiel de Vries, J., McCall, R., and Lescinski, J., 2009, Modeling storm impacts on beaches, dunes and barrier islands: Coastal Engineering, v. 56, p. 1,133–1,152, doi:10.1016/j.coastaleng.2009.08.006. Tolman, H.L., Balasubramaniyan, B., Burroughs, L.D., Chalikov, D.V., Chao, Y.Y., Chen H.S., Gerald, V.M., 2002, Development and implementation of wind generated ocean surface wave models at NCEP: Weather and Forecasting, v. 17, p. 311-333. Vitousek, S. and Barnard, P.L., 2015, A non-linear, implicit one-line model to predict long-term shoreline change: in, Wang, P., Rosati, J.D., and Cheng, J., (eds.), The Proceedings of the Coastal Sediments: 2015, World Scientific, 14 p., doi:10.1142/9789814689977_0215.

Projected Hazard: Geographic extent of projected coastal flooding, low-lying vulnerable areas, and maxium/minimum flood potential (flood uncertainty) associated with the sea-level rise and storm condition indicated. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the model summary and inspect output carefully. Data are complete for the information presented. Details: Model background: The CoSMoS model comprises three tiers. Tier I consists of one Delft3D hydrodynamics FLOW grid for computation of tides, water level variations, flows, and currents and one SWAN grid for computation of wave generation and propagation across the continental shelf. The FLOW and SWAN models are two-way coupled so that tidal currents are accounted for in wave propagation and growth and conversely, so that orbital velocities generated by waves impart changes on tidal currents. The Tier I SWAN and FLOW models consist of identical structured curvilinear grids that extend from far offshore to the shore and range in resolution from 0.5 km in the offshore to 0.2 km in the nearshore. Spatially varying astronomic tidal amplitudes and phases and steric rises in water levels due to large-scale effects (for example, a prolonged rise in sea level) are applied along all open boundaries of the Tier I FLOW grid. Winds (split into eastward and northward components) and sea-level pressure (SLP) fields from CaRD10 (Dr. Dan Cayan, Scripps Institute of Oceanography, Los Angeles, California, written commun., 2014) that vary in both space and time are applied to all grid cells at each model time-step. Deep-water wave conditions, applied at the open boundaries of the Tier I SWAN model runs, were projected for the 21st century Representative Concentration Pathway (RCP) 4.5 climate scenario (2011-2100) using the WaveWatch III numerical wave model (Tolman and others, 2002) and 3-hourly winds from the GFDL-ESM2M Global Climate Model (GCM). Tier II provides higher resolution near the shore and in areas that require greater resolution of physical processes (such as bays, harbors, and estuaries). A single nested outer grid and multiple two-way coupled domain decomposition (DD) structured grids allow for local grid refinement and higher resolution where needed. Tier II was segmented into 11 sections along the Southern California Bight, to reduce computation time and complete runs within computational limitations. Water-level and Neumann time-series, extracted from Tier I simulations, are applied to the shore-parallel and lateral open boundaries of each Tier II sub-model outer grid respectively. Several of the sub-models proved to be unstable with lateral Neumann boundaries; for those cases one or both of the lateral boundaries were converted to water-level time-series or left unassigned. The open-boundary time-series are extracted from completed Tier I simulations so that there is no communication from Tier II to Tier I. Because this one-way nesting could produce erroneous results near the boundaries of Tier II and because data near any model boundary are always suspect, Tier II sub-model extents were designed to overlap in the along-coast direction. In the landward direction, Tier II DD grids extend to the 10-m topographic contour; exceptions exist where channels (such as the Los Angeles River) or other low-lying regions extend very far inland. Space- and time-varying wind and SLP fields, identical to those used in Tier I simulations, are applied to all Tier II DD grids to allow for wind-setup and local inverse barometer effects (IBE, rise or depression of water levels in response to atmospheric pressure gradients). A total of 42 time-series fluvial discharges are included in the Tier II FLOW domains in an effort to simulate exacerbated flooding caused by backflow at the confluence of high river seaward flows and elevated coastal surge levels migrating inland. Time-varying fluvial discharges are applied either at the closed boundaries or distributed as point sources within the relevant model domains. Wave computations are accomplished with the SWAN model using two grids for each Tier II sub-model: one larger grid covering the same area as the outer FLOW grid and a second finer resolution two-way coupled nearshore nested grid. The nearshore grid extends from approximately 800-1,000 m water depth up to 8-10 m elevations onshore. The landward extension is included to allow for wave computations of the higher SLR scenarios. Time- and space-varying 2D wave spectra extracted from previously completed Tier I simulations are applied approximately every kilometer along the open boundaries of the outer Tier II sub-model SWAN grids. The same space- and time-varying wind fields used in Tier I simulations are also applied to both Tier II SWAN grids to allow for computation of local wave generation. Tier III for the entire Southern California Bight consists of 4,802 cross-shore transects (CST) spaced approximately 100 m apart in the along-shore direction. The profiles extend from the -15 m isobath to at least 10 m above NAVD88. The CSTs are truncated for cases where a lagoon or other waterway exists on the landward end of the profile. Time-varying water levels and wave parameters (significant wave heights, Hs; peak periods, Tp; and peak incident wave directions, Dp), extracted from Tier II grid cells that coincide with the seaward end of the CSTs, are applied at the open boundary of each CST. The XBeach model is run in a hydrostatic (no vertical pressure gradients) mode including event-based morphodynamic change. Wave propagation, two-way wave-current interaction, water-level variations, and wave runup are computed at each transect. XBeach simulations are included in the CoSMoS model to account for infragravity waves that can significantly extend the reach of wave runup (Roelvink and others, 2009) compared to short-wave incident waves. The U.S. west coast is particularly susceptible to infragravity waves at the shore due to breaking of long-period swell waves (Tp > 15). Resulting water levels (WLs) from both Delft3D (high interest bays and marshes) and open-coast XBeach (CSTs) were spatially combined and interpolated to a 10 m grid. These WL elevations are differenced from the originating 2 m digital elevation model (DEM) to determine final flooding extent and depth of flooding. Events: The model system is run for pre-determined scenarios of interest such as the 1-yr or 100-yr storm event in combination with sea-level rise. Storms are first identified from time-series of total water level proxies (TWLpx) at the shore. TWLpx are computed for the majority of the 21st century (2010-2100), assuming a linear super-position of the major processes that contribute to the overall total water level. TWLpx time-series are then evaluated for extreme events, which define the boundary conditions for subsequent modeling with CoSMoS. Multiple 100-yr events are determined (varying Hs, Tp, Dp) and used for multiple model runs to better account for regional and directional flooding affects. Model results are combined and compiled into scenario-specific composites of flood projection. Digital Elevation Model (DEM): Our seamless, topobathymetric digital elevation model (DEM) was based largely upon the Coastal California TopoBathy Merge Project DEM, with some modifications performed by the USGS Earth Resources Observation and Science (EROS) Center to incorporate the most recent, high-resolution topographic and bathymetric datasets available. Topography is derived from bare-earth light detection and ranging (lidar) data collected in 2009-2011 for the CA Coastal Conservancy Lidar Project and bathymetry from 2009-2010 bathymetric lidar as well as acoustic multi- and single-beam data collected primarily between 2001 and 2013. The DEM was constructed to define the shape of nearshore, beach, and cliff surfaces as accurately as possible, utilizing dozens of bathymetric and topographic data sets. These data were used to populate the majority of the tier I and II grids. To describe and include impacts from long-term shoreline evolution, including cumulative storm activity, seasonal trends, ENSO, and SLR, the DEM was modified for each SLR scenario. Long-term shoreline (Vitousek and Barnard, 2015) and cliff (Limber et al., 2015) erosion projections were efficiently combined along the cross-shore transects to evolve the shore-normal profiles. Elevation changes from the profiles were spatially-merged for a cohesive, 3D depiction of coastal evolution used to modify the DEM. These data are used to generate initial profiles of the 4,802 CSTs used for Phase 2 tier III XBeach modeling and determining final projected flood depths in each SLR scenario. All data are referenced to NAD83 horizontal datum and NAVD88 vertical datum. Data for Tiers II and III are projected in UTM, zone 11. Outputs include: Areas of projected flood hazards: The area vulnerable to coastal flooding due to storm surge, sea-level anomalies, tide elevation, and wave run-up during the storm simulation, based on the maximum elevation of still-water level (inundation for several minutes) at each CST profile. Enclosed areas illustrate the projected water surface and is shown extending from offshore to the extent of coastal flooding for different SLR scenarios between 0 - 2.0 m (0.25 m increments), and at 5.0 m. Low-lying vulnerable areas depict locations where projections indicate flood potential but are not connected to the primary flood surface. Flood potential indicates the maximum and minimum areas of flooding extent considering accuracy of the DEM, hydrodynamic model accuracy, and vertical land motion (Howell et al., 2016). References Cited: Howell, S., Smith-Konter, B., Frazer, N., Tong, X., and Sandwell, D., 2016, The vertical fingerprint of earthquake cycle loading in southern California: Nature Geoscience, v. 9, p. 611-614, doi:10.1038/ngeo2741. Limber, P., Barnard, P.L. and Hapke., C., 2015, Towards projecting the retreat of California’s coastal cliffs during the 21st Century: in, Wang, P., Rosati, J.D., and Cheng, J., (eds.), The Proceedings of the Coastal Sediments: 2015, World Scientific, 14 p., doi:10.1142/9789814689977_0245 Roelvink, J.A., Reniers, A., van Dongeren, A.R., van Thiel de Vries, J., McCall, R., and Lescinski, J., 2009, Modeling storm impacts on beaches, dunes and barrier islands: Coastal Engineering, v. 56, p. 1,133–1,152, doi:10.1016/j.coastaleng.2009.08.006. Tolman, H.L., Balasubramaniyan, B., Burroughs, L.D., Chalikov, D.V., Chao, Y.Y., Chen H.S., Gerald, V.M., 2002, Development and implementation of wind generated ocean surface wave models at NCEP: Weather and Forecasting, v. 17, p. 311-333. Vitousek, S. and Barnard, P.L., 2015, A non-linear, implicit one-line model to predict long-term shoreline change: in, Wang, P., Rosati, J.D., and Cheng, J., (eds.), The Proceedings of the Coastal Sediments: 2015, World Scientific, 14 p., doi:10.1142/9789814689977_0215.

Projected Hazard: Geographic extent of projected coastal flooding, low-lying vulnerable areas, and maxium/minimum flood potential (flood uncertainty) associated with the sea-level rise and storm condition indicated. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the model summary and inspect output carefully. Data are complete for the information presented. Details: Model background: The CoSMoS model comprises three tiers. Tier I consists of one Delft3D hydrodynamics FLOW grid for computation of tides, water level variations, flows, and currents and one SWAN grid for computation of wave generation and propagation across the continental shelf. The FLOW and SWAN models are two-way coupled so that tidal currents are accounted for in wave propagation and growth and conversely, so that orbital velocities generated by waves impart changes on tidal currents. The Tier I SWAN and FLOW models consist of identical structured curvilinear grids that extend from far offshore to the shore and range in resolution from 0.5 km in the offshore to 0.2 km in the nearshore. Spatially varying astronomic tidal amplitudes and phases and steric rises in water levels due to large-scale effects (for example, a prolonged rise in sea level) are applied along all open boundaries of the Tier I FLOW grid. Winds (split into eastward and northward components) and sea-level pressure (SLP) fields from CaRD10 (Dr. Dan Cayan, Scripps Institute of Oceanography, Los Angeles, California, written commun., 2014) that vary in both space and time are applied to all grid cells at each model time-step. Deep-water wave conditions, applied at the open boundaries of the Tier I SWAN model runs, were projected for the 21st century Representative Concentration Pathway (RCP) 4.5 climate scenario (2011-2100) using the WaveWatch III numerical wave model (Tolman and others, 2002) and 3-hourly winds from the GFDL-ESM2M Global Climate Model (GCM). Tier II provides higher resolution near the shore and in areas that require greater resolution of physical processes (such as bays, harbors, and estuaries). A single nested outer grid and multiple two-way coupled domain decomposition (DD) structured grids allow for local grid refinement and higher resolution where needed. Tier II was segmented into 11 sections along the Southern California Bight, to reduce computation time and complete runs within computational limitations. Water-level and Neumann time-series, extracted from Tier I simulations, are applied to the shore-parallel and lateral open boundaries of each Tier II sub-model outer grid respectively. Several of the sub-models proved to be unstable with lateral Neumann boundaries; for those cases one or both of the lateral boundaries were converted to water-level time-series or left unassigned. The open-boundary time-series are extracted from completed Tier I simulations so that there is no communication from Tier II to Tier I. Because this one-way nesting could produce erroneous results near the boundaries of Tier II and because data near any model boundary are always suspect, Tier II sub-model extents were designed to overlap in the along-coast direction. In the landward direction, Tier II DD grids extend to the 10-m topographic contour; exceptions exist where channels (such as the Los Angeles River) or other low-lying regions extend very far inland. Space- and time-varying wind and SLP fields, identical to those used in Tier I simulations, are applied to all Tier II DD grids to allow for wind-setup and local inverse barometer effects (IBE, rise or depression of water levels in response to atmospheric pressure gradients). A total of 42 time-series fluvial discharges are included in the Tier II FLOW domains in an effort to simulate exacerbated flooding caused by backflow at the confluence of high river seaward flows and elevated coastal surge levels migrating inland. Time-varying fluvial discharges are applied either at the closed boundaries or distributed as point sources within the relevant model domains. Wave computations are accomplished with the SWAN model using two grids for each Tier II sub-model: one larger grid covering the same area as the outer FLOW grid and a second finer resolution two-way coupled nearshore nested grid. The nearshore grid extends from approximately 800-1,000 m water depth up to 8-10 m elevations onshore. The landward extension is included to allow for wave computations of the higher SLR scenarios. Time- and space-varying 2D wave spectra extracted from previously completed Tier I simulations are applied approximately every kilometer along the open boundaries of the outer Tier II sub-model SWAN grids. The same space- and time-varying wind fields used in Tier I simulations are also applied to both Tier II SWAN grids to allow for computation of local wave generation. Tier III for the entire Southern California Bight consists of 4,802 cross-shore transects (CST) spaced approximately 100 m apart in the along-shore direction. The profiles extend from the -15 m isobath to at least 10 m above NAVD88. The CSTs are truncated for cases where a lagoon or other waterway exists on the landward end of the profile. Time-varying water levels and wave parameters (significant wave heights, Hs; peak periods, Tp; and peak incident wave directions, Dp), extracted from Tier II grid cells that coincide with the seaward end of the CSTs, are applied at the open boundary of each CST. The XBeach model is run in a hydrostatic (no vertical pressure gradients) mode including event-based morphodynamic change. Wave propagation, two-way wave-current interaction, water-level variations, and wave runup are computed at each transect. XBeach simulations are included in the CoSMoS model to account for infragravity waves that can significantly extend the reach of wave runup (Roelvink and others, 2009) compared to short-wave incident waves. The U.S. west coast is particularly susceptible to infragravity waves at the shore due to breaking of long-period swell waves (Tp > 15). Resulting water levels (WLs) from both Delft3D (high interest bays and marshes) and open-coast XBeach (CSTs) were spatially combined and interpolated to a 10 m grid. These WL elevations are differenced from the originating 2 m digital elevation model (DEM) to determine final flooding extent and depth of flooding. Events: The model system is run for pre-determined scenarios of interest such as the 1-yr or 100-yr storm event in combination with sea-level rise. Storms are first identified from time-series of total water level proxies (TWLpx) at the shore. TWLpx are computed for the majority of the 21st century (2010-2100), assuming a linear super-position of the major processes that contribute to the overall total water level. TWLpx time-series are then evaluated for extreme events, which define the boundary conditions for subsequent modeling with CoSMoS. Multiple 100-yr events are determined (varying Hs, Tp, Dp) and used for multiple model runs to better account for regional and directional flooding affects. Model results are combined and compiled into scenario-specific composites of flood projection. Digital Elevation Model (DEM): Our seamless, topobathymetric digital elevation model (DEM) was based largely upon the Coastal California TopoBathy Merge Project DEM, with some modifications performed by the USGS Earth Resources Observation and Science (EROS) Center to incorporate the most recent, high-resolution topographic and bathymetric datasets available. Topography is derived from bare-earth light detection and ranging (lidar) data collected in 2009-2011 for the CA Coastal Conservancy Lidar Project and bathymetry from 2009-2010 bathymetric lidar as well as acoustic multi- and single-beam data collected primarily between 2001 and 2013. The DEM was constructed to define the shape of nearshore, beach, and cliff surfaces as accurately as possible, utilizing dozens of bathymetric and topographic data sets. These data were used to populate the majority of the tier I and II grids. To describe and include impacts from long-term shoreline evolution, including cumulative storm activity, seasonal trends, ENSO, and SLR, the DEM was modified for each SLR scenario. Long-term shoreline (Vitousek and Barnard, 2015) and cliff (Limber et al., 2015) erosion projections were efficiently combined along the cross-shore transects to evolve the shore-normal profiles. Elevation changes from the profiles were spatially-merged for a cohesive, 3D depiction of coastal evolution used to modify the DEM. These data are used to generate initial profiles of the 4,802 CSTs used for Phase 2 tier III XBeach modeling and determining final projected flood depths in each SLR scenario. All data are referenced to NAD83 horizontal datum and NAVD88 vertical datum. Data for Tiers II and III are projected in UTM, zone 11. Outputs include: Areas of projected flood hazards: The area vulnerable to coastal flooding due to storm surge, sea-level anomalies, tide elevation, and wave run-up during the storm simulation, based on the maximum elevation of still-water level (inundation for several minutes) at each CST profile. Enclosed areas illustrate the projected water surface and is shown extending from offshore to the extent of coastal flooding for different SLR scenarios between 0 - 2.0 m (0.25 m increments), and at 5.0 m. Low-lying vulnerable areas depict locations where projections indicate flood potential but are not connected to the primary flood surface. Flood potential indicates the maximum and minimum areas of flooding extent considering accuracy of the DEM, hydrodynamic model accuracy, and vertical land motion (Howell et al., 2016). References Cited: Howell, S., Smith-Konter, B., Frazer, N., Tong, X., and Sandwell, D., 2016, The vertical fingerprint of earthquake cycle loading in southern California: Nature Geoscience, v. 9, p. 611-614, doi:10.1038/ngeo2741. Limber, P., Barnard, P.L. and Hapke., C., 2015, Towards projecting the retreat of California’s coastal cliffs during the 21st Century: in, Wang, P., Rosati, J.D., and Cheng, J., (eds.), The Proceedings of the Coastal Sediments: 2015, World Scientific, 14 p., doi:10.1142/9789814689977_0245 Roelvink, J.A., Reniers, A., van Dongeren, A.R., van Thiel de Vries, J., McCall, R., and Lescinski, J., 2009, Modeling storm impacts on beaches, dunes and barrier islands: Coastal Engineering, v. 56, p. 1,133–1,152, doi:10.1016/j.coastaleng.2009.08.006. Tolman, H.L., Balasubramaniyan, B., Burroughs, L.D., Chalikov, D.V., Chao, Y.Y., Chen H.S., Gerald, V.M., 2002, Development and implementation of wind generated ocean surface wave models at NCEP: Weather and Forecasting, v. 17, p. 311-333. Vitousek, S. and Barnard, P.L., 2015, A non-linear, implicit one-line model to predict long-term shoreline change: in, Wang, P., Rosati, J.D., and Cheng, J., (eds.), The Proceedings of the Coastal Sediments: 2015, World Scientific, 14 p., doi:10.1142/9789814689977_0215.

Projected Hazard: Geographic extent of projected coastal flooding, low-lying vulnerable areas, and maxium/minimum flood potential (flood uncertainty) associated with the sea-level rise and storm condition indicated. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the model summary and inspect output carefully. Data are complete for the information presented. Details: Model background: The CoSMoS model comprises three tiers. Tier I consists of one Delft3D hydrodynamics FLOW grid for computation of tides, water level variations, flows, and currents and one SWAN grid for computation of wave generation and propagation across the continental shelf. The FLOW and SWAN models are two-way coupled so that tidal currents are accounted for in wave propagation and growth and conversely, so that orbital velocities generated by waves impart changes on tidal currents. The Tier I SWAN and FLOW models consist of identical structured curvilinear grids that extend from far offshore to the shore and range in resolution from 0.5 km in the offshore to 0.2 km in the nearshore. Spatially varying astronomic tidal amplitudes and phases and steric rises in water levels due to large-scale effects (for example, a prolonged rise in sea level) are applied along all open boundaries of the Tier I FLOW grid. Winds (split into eastward and northward components) and sea-level pressure (SLP) fields from CaRD10 (Dr. Dan Cayan, Scripps Institute of Oceanography, Los Angeles, California, written commun., 2014) that vary in both space and time are applied to all grid cells at each model time-step. Deep-water wave conditions, applied at the open boundaries of the Tier I SWAN model runs, were projected for the 21st century Representative Concentration Pathway (RCP) 4.5 climate scenario (2011-2100) using the WaveWatch III numerical wave model (Tolman and others, 2002) and 3-hourly winds from the GFDL-ESM2M Global Climate Model (GCM). Tier II provides higher resolution near the shore and in areas that require greater resolution of physical processes (such as bays, harbors, and estuaries). A single nested outer grid and multiple two-way coupled domain decomposition (DD) structured grids allow for local grid refinement and higher resolution where needed. Tier II was segmented into 11 sections along the Southern California Bight, to reduce computation time and complete runs within computational limitations. Water-level and Neumann time-series, extracted from Tier I simulations, are applied to the shore-parallel and lateral open boundaries of each Tier II sub-model outer grid respectively. Several of the sub-models proved to be unstable with lateral Neumann boundaries; for those cases one or both of the lateral boundaries were converted to water-level time-series or left unassigned. The open-boundary time-series are extracted from completed Tier I simulations so that there is no communication from Tier II to Tier I. Because this one-way nesting could produce erroneous results near the boundaries of Tier II and because data near any model boundary are always suspect, Tier II sub-model extents were designed to overlap in the along-coast direction. In the landward direction, Tier II DD grids extend to the 10-m topographic contour; exceptions exist where channels (such as the Los Angeles River) or other low-lying regions extend very far inland. Space- and time-varying wind and SLP fields, identical to those used in Tier I simulations, are applied to all Tier II DD grids to allow for wind-setup and local inverse barometer effects (IBE, rise or depression of water levels in response to atmospheric pressure gradients). A total of 42 time-series fluvial discharges are included in the Tier II FLOW domains in an effort to simulate exacerbated flooding caused by backflow at the confluence of high river seaward flows and elevated coastal surge levels migrating inland. Time-varying fluvial discharges are applied either at the closed boundaries or distributed as point sources within the relevant model domains. Wave computations are accomplished with the SWAN model using two grids for each Tier II sub-model: one larger grid covering the same area as the outer FLOW grid and a second finer resolution two-way coupled nearshore nested grid. The nearshore grid extends from approximately 800-1,000 m water depth up to 8-10 m elevations onshore. The landward extension is included to allow for wave computations of the higher SLR scenarios. Time- and space-varying 2D wave spectra extracted from previously completed Tier I simulations are applied approximately every kilometer along the open boundaries of the outer Tier II sub-model SWAN grids. The same space- and time-varying wind fields used in Tier I simulations are also applied to both Tier II SWAN grids to allow for computation of local wave generation. Tier III for the entire Southern California Bight consists of 4,802 cross-shore transects (CST) spaced approximately 100 m apart in the along-shore direction. The profiles extend from the -15 m isobath to at least 10 m above NAVD88. The CSTs are truncated for cases where a lagoon or other waterway exists on the landward end of the profile. Time-varying water levels and wave parameters (significant wave heights, Hs; peak periods, Tp; and peak incident wave directions, Dp), extracted from Tier II grid cells that coincide with the seaward end of the CSTs, are applied at the open boundary of each CST. The XBeach model is run in a hydrostatic (no vertical pressure gradients) mode including event-based morphodynamic change. Wave propagation, two-way wave-current interaction, water-level variations, and wave runup are computed at each transect. XBeach simulations are included in the CoSMoS model to account for infragravity waves that can significantly extend the reach of wave runup (Roelvink and others, 2009) compared to short-wave incident waves. The U.S. west coast is particularly susceptible to infragravity waves at the shore due to breaking of long-period swell waves (Tp > 15). Resulting water levels (WLs) from both Delft3D (high interest bays and marshes) and open-coast XBeach (CSTs) were spatially combined and interpolated to a 10 m grid. These WL elevations are differenced from the originating 2 m digital elevation model (DEM) to determine final flooding extent and depth of flooding. Events: The model system is run for pre-determined scenarios of interest such as the 1-yr or 100-yr storm event in combination with sea-level rise. Storms are first identified from time-series of total water level proxies (TWLpx) at the shore. TWLpx are computed for the majority of the 21st century (2010-2100), assuming a linear super-position of the major processes that contribute to the overall total water level. TWLpx time-series are then evaluated for extreme events, which define the boundary conditions for subsequent modeling with CoSMoS. Multiple 100-yr events are determined (varying Hs, Tp, Dp) and used for multiple model runs to better account for regional and directional flooding affects. Model results are combined and compiled into scenario-specific composites of flood projection. Digital Elevation Model (DEM): Our seamless, topobathymetric digital elevation model (DEM) was based largely upon the Coastal California TopoBathy Merge Project DEM, with some modifications performed by the USGS Earth Resources Observation and Science (EROS) Center to incorporate the most recent, high-resolution topographic and bathymetric datasets available. Topography is derived from bare-earth light detection and ranging (lidar) data collected in 2009-2011 for the CA Coastal Conservancy Lidar Project and bathymetry from 2009-2010 bathymetric lidar as well as acoustic multi- and single-beam data collected primarily between 2001 and 2013. The DEM was constructed to define the shape of nearshore, beach, and cliff surfaces as accurately as possible, utilizing dozens of bathymetric and topographic data sets. These data were used to populate the majority of the tier I and II grids. To describe and include impacts from long-term shoreline evolution, including cumulative storm activity, seasonal trends, ENSO, and SLR, the DEM was modified for each SLR scenario. Long-term shoreline (Vitousek and Barnard, 2015) and cliff (Limber et al., 2015) erosion projections were efficiently combined along the cross-shore transects to evolve the shore-normal profiles. Elevation changes from the profiles were spatially-merged for a cohesive, 3D depiction of coastal evolution used to modify the DEM. These data are used to generate initial profiles of the 4,802 CSTs used for Phase 2 tier III XBeach modeling and determining final projected flood depths in each SLR scenario. All data are referenced to NAD83 horizontal datum and NAVD88 vertical datum. Data for Tiers II and III are projected in UTM, zone 11. Outputs include: Areas of projected flood hazards: The area vulnerable to coastal flooding due to storm surge, sea-level anomalies, tide elevation, and wave run-up during the storm simulation, based on the maximum elevation of still-water level (inundation for several minutes) at each CST profile. Enclosed areas illustrate the projected water surface and is shown extending from offshore to the extent of coastal flooding for different SLR scenarios between 0 - 2.0 m (0.25 m increments), and at 5.0 m. Low-lying vulnerable areas depict locations where projections indicate flood potential but are not connected to the primary flood surface. Flood potential indicates the maximum and minimum areas of flooding extent considering accuracy of the DEM, hydrodynamic model accuracy, and vertical land motion (Howell et al., 2016). References Cited: Howell, S., Smith-Konter, B., Frazer, N., Tong, X., and Sandwell, D., 2016, The vertical fingerprint of earthquake cycle loading in southern California: Nature Geoscience, v. 9, p. 611-614, doi:10.1038/ngeo2741. Limber, P., Barnard, P.L. and Hapke., C., 2015, Towards projecting the retreat of California’s coastal cliffs during the 21st Century: in, Wang, P., Rosati, J.D., and Cheng, J., (eds.), The Proceedings of the Coastal Sediments: 2015, World Scientific, 14 p., doi:10.1142/9789814689977_0245 Roelvink, J.A., Reniers, A., van Dongeren, A.R., van Thiel de Vries, J., McCall, R., and Lescinski, J., 2009, Modeling storm impacts on beaches, dunes and barrier islands: Coastal Engineering, v. 56, p. 1,133–1,152, doi:10.1016/j.coastaleng.2009.08.006. Tolman, H.L., Balasubramaniyan, B., Burroughs, L.D., Chalikov, D.V., Chao, Y.Y., Chen H.S., Gerald, V.M., 2002, Development and implementation of wind generated ocean surface wave models at NCEP: Weather and Forecasting, v. 17, p. 311-333. Vitousek, S. and Barnard, P.L., 2015, A non-linear, implicit one-line model to predict long-term shoreline change: in, Wang, P., Rosati, J.D., and Cheng, J., (eds.), The Proceedings of the Coastal Sediments: 2015, World Scientific, 14 p., doi:10.1142/9789814689977_0215.

Projected Hazard: Model-derived ocean current velocities (in meters per second) for the given storm condition and sea-level rise (SLR) scenario. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the model summary and inspect output carefully. Data are complete for the information presented. Details: Model background: The CoSMoS model comprises three tiers. Tier I consists of one Delft3D hydrodynamics FLOW grid for computation of tides, water level variations, flows, and currents and one SWAN grid for computation of wave generation and propagation across the continental shelf. The FLOW and SWAN models are two-way coupled so that tidal currents are accounted for in wave propagation and growth and conversely, so that orbital velocities generated by waves impart changes on tidal currents. The Tier I SWAN and FLOW models consist of identical structured curvilinear grids that extend from far offshore to the shore and range in resolution from 0.5 km in the offshore to 0.2 km in the nearshore. Spatially varying astronomic tidal amplitudes and phases and steric rises in water levels due to large-scale effects (for example, a prolonged rise in sea level) are applied along all open boundaries of the Tier I FLOW grid. Winds (split into eastward and northward components) and sea-level pressure (SLP) fields from CaRD10 (Dr. Dan Cayan, Scripps Institute of Oceanography, Los Angeles, California, written commun., 2014) that vary in both space and time are applied to all grid cells at each model time-step. Deep-water wave conditions, applied at the open boundaries of the Tier I SWAN model runs, were projected for the 21st century Representative Concentration Pathway (RCP) 4.5 climate scenario (2011-2100) using the WaveWatch III numerical wave model (Tolman and others, 2002) and 3-hourly winds from the GFDL-ESM2M Global Climate Model (GCM). Tier II provides higher resolution near the shore and in areas that require greater resolution of physical processes (such as bays, harbors, and estuaries). A single nested outer grid and multiple two-way coupled domain decomposition (DD) structured grids allow for local grid refinement and higher resolution where needed. Tier II was segmented into 11 sections along the Southern California Bight, to reduce computation time and complete runs within computational limitations. Water-level and Neumann time-series, extracted from Tier I simulations, are applied to the shore-parallel and lateral open boundaries of each Tier II sub-model outer grid respectively. Several of the sub-models proved to be unstable with lateral Neumann boundaries; for those cases one or both of the lateral boundaries were converted to water-level time-series or left unassigned. The open-boundary time-series are extracted from completed Tier I simulations so that there is no communication from Tier II to Tier I. Because this one-way nesting could produce erroneous results near the boundaries of Tier II and because data near any model boundary are always suspect, Tier II sub-model extents were designed to overlap in the along-coast direction. In the landward direction, Tier II DD grids extend to the 10-m topographic contour; exceptions exist where channels (such as the Los Angeles River) or other low-lying regions extend very far inland. Space- and time-varying wind and SLP fields, identical to those used in Tier I simulations, are applied to all Tier II DD grids to allow for wind-setup and local inverse barometer effects (IBE, rise or depression of water levels in response to atmospheric pressure gradients). A total of 42 time-series fluvial discharges are included in the Tier II FLOW domains in an effort to simulate exacerbated flooding caused by backflow at the confluence of high river seaward flows and elevated coastal surge levels migrating inland. Time-varying fluvial discharges are applied either at the closed boundaries or distributed as point sources within the relevant model domains. Wave computations are accomplished with the SWAN model using two grids for each Tier II sub-model: one larger grid covering the same area as the outer FLOW grid and a second finer resolution two-way coupled nearshore nested grid. The nearshore grid extends from approximately 800-1,000 m water depth up to 8-10 m elevations onshore. The landward extension is included to allow for wave computations of the higher SLR scenarios. Time- and space-varying 2D wave spectra extracted from previously completed Tier I simulations are applied approximately every kilometer along the open boundaries of the outer Tier II sub-model SWAN grids. The same space- and time-varying wind fields used in Tier I simulations are also applied to both Tier II SWAN grids to allow for computation of local wave generation. Tier III for the entire Southern California Bight consists of 4,802 cross-shore transects (CST) spaced approximately 100 m apart in the along-shore direction. The profiles extend from the -15 m isobath to at least 10 m above NAVD88. The CSTs are truncated for cases where a lagoon or other waterway exists on the landward end of the profile. Time-varying water levels and wave parameters (significant wave heights, Hs; peak periods, Tp; and peak incident wave directions, Dp), extracted from Tier II grid cells that coincide with the seaward end of the CSTs, are applied at the open boundary of each CST. The XBeach model is run in a hydrostatic (no vertical pressure gradients) mode including event-based morphodynamic change. Wave propagation, two-way wave-current interaction, water-level variations, and wave runup are computed at each transect. XBeach simulations are included in the CoSMoS model to account for infragravity waves that can significantly extend the reach of wave runup (Roelvink and others, 2009) compared to short-wave incident waves. The U.S. west coast is particularly susceptible to infragravity waves at the shore due to breaking of long-period swell waves (Tp > 15). Resulting water levels (WLs) from both Delft3D (high interest bays and marshes) and open-coast XBeach (CSTs) were spatially combined and interpolated to a 10 m grid. These WL elevations are differenced from the originating 2 m digital elevation model (DEM) to determine final flooding extent and depth of flooding. Events: The model system is run for pre-determined scenarios of interest such as the 1-yr or 100-yr storm event in combination with sea-level rise. Storms are first identified from time-series of total water level proxies (TWLpx) at the shore. TWLpx are computed for the majority of the 21st century (2010-2100), assuming a linear super-position of the major processes that contribute to the overall total water level. TWLpx time-series are then evaluated for extreme events, which define the boundary conditions for subsequent modeling with CoSMoS. Multiple 100-yr events are determined (varying Hs, Tp, Dp) and used for multiple model runs to better account for regional and directional flooding affects. Model results are combined and compiled into scenario-specific composites of flood projection. Digital Elevation Model (DEM): Our seamless, topobathymetric digital elevation model (DEM) was based largely upon the Coastal California TopoBathy Merge Project DEM, with some modifications performed by the USGS Earth Resources Observation and Science (EROS) Center to incorporate the most recent, high-resolution topographic and bathymetric datasets available. Topography is derived from bare-earth light detection and ranging (lidar) data collected in 2009-2011 for the CA Coastal Conservancy Lidar Project and bathymetry from 2009-2010 bathymetric lidar as well as acoustic multi- and single-beam data collected primarily between 2001 and 2013. The DEM was constructed to define the shape of nearshore, beach, and cliff surfaces as accurately as possible, utilizing dozens of bathymetric and topographic data sets. These data were used to populate the majority of the Tier I and II grids. To describe and include impacts from long-term shoreline evolution, including cumulative storm activity, seasonal trends, ENSO, and SLR, the DEM was modified for each SLR scenario. Long-term shoreline (Vitousek and Barnard, 2015) and cliff (Limber and others, 2015) erosion projections were efficiently combined along the cross-shore transects to evolve the shore-normal profiles. Elevation changes from the profiles were spatially-merged for a cohesive, 3D depiction of coastal evolution used to modify the DEM. These data are used to generate initial profiles of the 4,802 CSTs used for Phase 2 Tier III XBeach modeling and determining final projected flood depths in each SLR scenario. All data are referenced to NAD83 horizontal datum and NAVD88 vertical datum. Data for Tiers II and III are projected in UTM, zone 11. Outputs include: Projected ocean current velocities for the 100-year storm and 0.0 m sea-level rise scenario. Data correspond to the near-shore region including areas vulnerable to coastal flooding due to storm surge, sea-level anomalies, tide elevation, and wave run-up during the same storm and sea-level rise simulation. References Cited: Howell, S., Smith-Konter, B., Frazer, N., Tong, X., and Sandwell, D., 2016, The vertical fingerprint of earthquake cycle loading in southern California: Nature Geoscience, v. 9, p. 611-614, doi:10.1038/ngeo2741. Limber, P., Barnard, P.L. and Hapke., C., 2015, Towards projecting the retreat of California’s coastal cliffs during the 21st Century: in, Wang, P., Rosati, J.D., and Cheng, J., (eds.), The Proceedings of the Coastal Sediments: 2015, World Scientific, 14 p., doi:10.1142/9789814689977_0245 Roelvink, J.A., Reniers, A., van Dongeren, A.R., van Thiel de Vries, J., McCall, R., and Lescinski, J., 2009, Modeling storm impacts on beaches, dunes and barrier islands: Coastal Engineering, v. 56, p. 1,133–1,152, doi:10.1016/j.coastaleng.2009.08.006. Tolman, H.L., Balasubramaniyan, B., Burroughs, L.D., Chalikov, D.V., Chao, Y.Y., Chen H.S., Gerald, V.M., 2002, Development and implementation of wind generated ocean surface wave models at NCEP: Weather and Forecasting, v. 17, p. 311-333. Vitousek, S. and Barnard, P.L., 2015, A non-linear, implicit one-line model to predict long-term shoreline change: in, Wang, P., Rosati, J.D., and Cheng, J., (eds.), The Proceedings of the Coastal Sediments: 2015, World Scientific, 14 p., doi:10.1142/9789814689977_0215.

Projected Hazard: Model-derived ocean current velocities (in meters per second) for the given storm condition and sea-level rise (SLR) scenario. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the model summary and inspect output carefully. Data are complete for the information presented. Details: Model background: The CoSMoS model comprises three tiers. Tier I consists of one Delft3D hydrodynamics FLOW grid for computation of tides, water level variations, flows, and currents and one SWAN grid for computation of wave generation and propagation across the continental shelf. The FLOW and SWAN models are two-way coupled so that tidal currents are accounted for in wave propagation and growth and conversely, so that orbital velocities generated by waves impart changes on tidal currents. The Tier I SWAN and FLOW models consist of identical structured curvilinear grids that extend from far offshore to the shore and range in resolution from 0.5 km in the offshore to 0.2 km in the nearshore. Spatially varying astronomic tidal amplitudes and phases and steric rises in water levels due to large-scale effects (for example, a prolonged rise in sea level) are applied along all open boundaries of the Tier I FLOW grid. Winds (split into eastward and northward components) and sea-level pressure (SLP) fields from CaRD10 (Dr. Dan Cayan, Scripps Institute of Oceanography, Los Angeles, California, written commun., 2014) that vary in both space and time are applied to all grid cells at each model time-step. Deep-water wave conditions, applied at the open boundaries of the Tier I SWAN model runs, were projected for the 21st century Representative Concentration Pathway (RCP) 4.5 climate scenario (2011-2100) using the WaveWatch III numerical wave model (Tolman and others, 2002) and 3-hourly winds from the GFDL-ESM2M Global Climate Model (GCM). Tier II provides higher resolution near the shore and in areas that require greater resolution of physical processes (such as bays, harbors, and estuaries). A single nested outer grid and multiple two-way coupled domain decomposition (DD) structured grids allow for local grid refinement and higher resolution where needed. Tier II was segmented into 11 sections along the Southern California Bight, to reduce computation time and complete runs within computational limitations. Water-level and Neumann time-series, extracted from Tier I simulations, are applied to the shore-parallel and lateral open boundaries of each Tier II sub-model outer grid respectively. Several of the sub-models proved to be unstable with lateral Neumann boundaries; for those cases one or both of the lateral boundaries were converted to water-level time-series or left unassigned. The open-boundary time-series are extracted from completed Tier I simulations so that there is no communication from Tier II to Tier I. Because this one-way nesting could produce erroneous results near the boundaries of Tier II and because data near any model boundary are always suspect, Tier II sub-model extents were designed to overlap in the along-coast direction. In the landward direction, Tier II DD grids extend to the 10-m topographic contour; exceptions exist where channels (such as the Los Angeles River) or other low-lying regions extend very far inland. Space- and time-varying wind and SLP fields, identical to those used in Tier I simulations, are applied to all Tier II DD grids to allow for wind-setup and local inverse barometer effects (IBE, rise or depression of water levels in response to atmospheric pressure gradients). A total of 42 time-series fluvial discharges are included in the Tier II FLOW domains in an effort to simulate exacerbated flooding caused by backflow at the confluence of high river seaward flows and elevated coastal surge levels migrating inland. Time-varying fluvial discharges are applied either at the closed boundaries or distributed as point sources within the relevant model domains. Wave computations are accomplished with the SWAN model using two grids for each Tier II sub-model: one larger grid covering the same area as the outer FLOW grid and a second finer resolution two-way coupled nearshore nested grid. The nearshore grid extends from approximately 800-1,000 m water depth up to 8-10 m elevations onshore. The landward extension is included to allow for wave computations of the higher SLR scenarios. Time- and space-varying 2D wave spectra extracted from previously completed Tier I simulations are applied approximately every kilometer along the open boundaries of the outer Tier II sub-model SWAN grids. The same space- and time-varying wind fields used in Tier I simulations are also applied to both Tier II SWAN grids to allow for computation of local wave generation. Tier III for the entire Southern California Bight consists of 4,802 cross-shore transects (CST) spaced approximately 100 m apart in the along-shore direction. The profiles extend from the -15 m isobath to at least 10 m above NAVD88. The CSTs are truncated for cases where a lagoon or other waterway exists on the landward end of the profile. Time-varying water levels and wave parameters (significant wave heights, Hs; peak periods, Tp; and peak incident wave directions, Dp), extracted from Tier II grid cells that coincide with the seaward end of the CSTs, are applied at the open boundary of each CST. The XBeach model is run in a hydrostatic (no vertical pressure gradients) mode including event-based morphodynamic change. Wave propagation, two-way wave-current interaction, water-level variations, and wave runup are computed at each transect. XBeach simulations are included in the CoSMoS model to account for infragravity waves that can significantly extend the reach of wave runup (Roelvink and others, 2009) compared to short-wave incident waves. The U.S. west coast is particularly susceptible to infragravity waves at the shore due to breaking of long-period swell waves (Tp > 15). Resulting water levels (WLs) from both Delft3D (high interest bays and marshes) and open-coast XBeach (CSTs) were spatially combined and interpolated to a 10 m grid. These WL elevations are differenced from the originating 2 m digital elevation model (DEM) to determine final flooding extent and depth of flooding. Events: The model system is run for pre-determined scenarios of interest such as the 1-yr or 100-yr storm event in combination with sea-level rise. Storms are first identified from time-series of total water level proxies (TWLpx) at the shore. TWLpx are computed for the majority of the 21st century (2010-2100), assuming a linear super-position of the major processes that contribute to the overall total water level. TWLpx time-series are then evaluated for extreme events, which define the boundary conditions for subsequent modeling with CoSMoS. Multiple 100-yr events are determined (varying Hs, Tp, Dp) and used for multiple model runs to better account for regional and directional flooding affects. Model results are combined and compiled into scenario-specific composites of flood projection. Digital Elevation Model (DEM): Our seamless, topobathymetric digital elevation model (DEM) was based largely upon the Coastal California TopoBathy Merge Project DEM, with some modifications performed by the USGS Earth Resources Observation and Science (EROS) Center to incorporate the most recent, high-resolution topographic and bathymetric datasets available. Topography is derived from bare-earth light detection and ranging (lidar) data collected in 2009-2011 for the CA Coastal Conservancy Lidar Project and bathymetry from 2009-2010 bathymetric lidar as well as acoustic multi- and single-beam data collected primarily between 2001 and 2013. The DEM was constructed to define the shape of nearshore, beach, and cliff surfaces as accurately as possible, utilizing dozens of bathymetric and topographic data sets. These data were used to populate the majority of the Tier I and II grids. To describe and include impacts from long-term shoreline evolution, including cumulative storm activity, seasonal trends, ENSO, and SLR, the DEM was modified for each SLR scenario. Long-term shoreline (Vitousek and Barnard, 2015) and cliff (Limber and others, 2015) erosion projections were efficiently combined along the cross-shore transects to evolve the shore-normal profiles. Elevation changes from the profiles were spatially-merged for a cohesive, 3D depiction of coastal evolution used to modify the DEM. These data are used to generate initial profiles of the 4,802 CSTs used for Phase 2 Tier III XBeach modeling and determining final projected flood depths in each SLR scenario. All data are referenced to NAD83 horizontal datum and NAVD88 vertical datum. Data for Tiers II and III are projected in UTM, zone 11. Outputs include: Projected ocean current velocities for the 100-year storm and 0.0 m sea-level rise scenario. Data correspond to the near-shore region including areas vulnerable to coastal flooding due to storm surge, sea-level anomalies, tide elevation, and wave run-up during the same storm and sea-level rise simulation. References Cited: Howell, S., Smith-Konter, B., Frazer, N., Tong, X., and Sandwell, D., 2016, The vertical fingerprint of earthquake cycle loading in southern California: Nature Geoscience, v. 9, p. 611-614, doi:10.1038/ngeo2741. Limber, P., Barnard, P.L. and Hapke., C., 2015, Towards projecting the retreat of California’s coastal cliffs during the 21st Century: in, Wang, P., Rosati, J.D., and Cheng, J., (eds.), The Proceedings of the Coastal Sediments: 2015, World Scientific, 14 p., doi:10.1142/9789814689977_0245 Roelvink, J.A., Reniers, A., van Dongeren, A.R., van Thiel de Vries, J., McCall, R., and Lescinski, J., 2009, Modeling storm impacts on beaches, dunes and barrier islands: Coastal Engineering, v. 56, p. 1,133–1,152, doi:10.1016/j.coastaleng.2009.08.006. Tolman, H.L., Balasubramaniyan, B., Burroughs, L.D., Chalikov, D.V., Chao, Y.Y., Chen H.S., Gerald, V.M., 2002, Development and implementation of wind generated ocean surface wave models at NCEP: Weather and Forecasting, v. 17, p. 311-333. Vitousek, S. and Barnard, P.L., 2015, A non-linear, implicit one-line model to predict long-term shoreline change: in, Wang, P., Rosati, J.D., and Cheng, J., (eds.), The Proceedings of the Coastal Sediments: 2015, World Scientific, 14 p., doi:10.1142/9789814689977_0215.

Projected Hazard: Model-derived ocean current velocities (in meters per second) for the given storm condition and sea-level rise (SLR) scenario. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the model summary and inspect output carefully. Data are complete for the information presented. Details: Model background: The CoSMoS model comprises three tiers. Tier I consists of one Delft3D hydrodynamics FLOW grid for computation of tides, water level variations, flows, and currents and one SWAN grid for computation of wave generation and propagation across the continental shelf. The FLOW and SWAN models are two-way coupled so that tidal currents are accounted for in wave propagation and growth and conversely, so that orbital velocities generated by waves impart changes on tidal currents. The Tier I SWAN and FLOW models consist of identical structured curvilinear grids that extend from far offshore to the shore and range in resolution from 0.5 km in the offshore to 0.2 km in the nearshore. Spatially varying astronomic tidal amplitudes and phases and steric rises in water levels due to large-scale effects (for example, a prolonged rise in sea level) are applied along all open boundaries of the Tier I FLOW grid. Winds (split into eastward and northward components) and sea-level pressure (SLP) fields from CaRD10 (Dr. Dan Cayan, Scripps Institute of Oceanography, Los Angeles, California, written commun., 2014) that vary in both space and time are applied to all grid cells at each model time-step. Deep-water wave conditions, applied at the open boundaries of the Tier I SWAN model runs, were projected for the 21st century Representative Concentration Pathway (RCP) 4.5 climate scenario (2011-2100) using the WaveWatch III numerical wave model (Tolman and others, 2002) and 3-hourly winds from the GFDL-ESM2M Global Climate Model (GCM). Tier II provides higher resolution near the shore and in areas that require greater resolution of physical processes (such as bays, harbors, and estuaries). A single nested outer grid and multiple two-way coupled domain decomposition (DD) structured grids allow for local grid refinement and higher resolution where needed. Tier II was segmented into 11 sections along the Southern California Bight, to reduce computation time and complete runs within computational limitations. Water-level and Neumann time-series, extracted from Tier I simulations, are applied to the shore-parallel and lateral open boundaries of each Tier II sub-model outer grid respectively. Several of the sub-models proved to be unstable with lateral Neumann boundaries; for those cases one or both of the lateral boundaries were converted to water-level time-series or left unassigned. The open-boundary time-series are extracted from completed Tier I simulations so that there is no communication from Tier II to Tier I. Because this one-way nesting could produce erroneous results near the boundaries of Tier II and because data near any model boundary are always suspect, Tier II sub-model extents were designed to overlap in the along-coast direction. In the landward direction, Tier II DD grids extend to the 10-m topographic contour; exceptions exist where channels (such as the Los Angeles River) or other low-lying regions extend very far inland. Space- and time-varying wind and SLP fields, identical to those used in Tier I simulations, are applied to all Tier II DD grids to allow for wind-setup and local inverse barometer effects (IBE, rise or depression of water levels in response to atmospheric pressure gradients). A total of 42 time-series fluvial discharges are included in the Tier II FLOW domains in an effort to simulate exacerbated flooding caused by backflow at the confluence of high river seaward flows and elevated coastal surge levels migrating inland. Time-varying fluvial discharges are applied either at the closed boundaries or distributed as point sources within the relevant model domains. Wave computations are accomplished with the SWAN model using two grids for each Tier II sub-model: one larger grid covering the same area as the outer FLOW grid and a second finer resolution two-way coupled nearshore nested grid. The nearshore grid extends from approximately 800-1,000 m water depth up to 8-10 m elevations onshore. The landward extension is included to allow for wave computations of the higher SLR scenarios. Time- and space-varying 2D wave spectra extracted from previously completed Tier I simulations are applied approximately every kilometer along the open boundaries of the outer Tier II sub-model SWAN grids. The same space- and time-varying wind fields used in Tier I simulations are also applied to both Tier II SWAN grids to allow for computation of local wave generation. Tier III for the entire Southern California Bight consists of 4,802 cross-shore transects (CST) spaced approximately 100 m apart in the along-shore direction. The profiles extend from the -15 m isobath to at least 10 m above NAVD88. The CSTs are truncated for cases where a lagoon or other waterway exists on the landward end of the profile. Time-varying water levels and wave parameters (significant wave heights, Hs; peak periods, Tp; and peak incident wave directions, Dp), extracted from Tier II grid cells that coincide with the seaward end of the CSTs, are applied at the open boundary of each CST. The XBeach model is run in a hydrostatic (no vertical pressure gradients) mode including event-based morphodynamic change. Wave propagation, two-way wave-current interaction, water-level variations, and wave runup are computed at each transect. XBeach simulations are included in the CoSMoS model to account for infragravity waves that can significantly extend the reach of wave runup (Roelvink and others, 2009) compared to short-wave incident waves. The U.S. west coast is particularly susceptible to infragravity waves at the shore due to breaking of long-period swell waves (Tp > 15). Resulting water levels (WLs) from both Delft3D (high interest bays and marshes) and open-coast XBeach (CSTs) were spatially combined and interpolated to a 10 m grid. These WL elevations are differenced from the originating 2 m digital elevation model (DEM) to determine final flooding extent and depth of flooding. Events: The model system is run for pre-determined scenarios of interest such as the 1-yr or 100-yr storm event in combination with sea-level rise. Storms are first identified from time-series of total water level proxies (TWLpx) at the shore. TWLpx are computed for the majority of the 21st century (2010-2100), assuming a linear super-position of the major processes that contribute to the overall total water level. TWLpx time-series are then evaluated for extreme events, which define the boundary conditions for subsequent modeling with CoSMoS. Multiple 100-yr events are determined (varying Hs, Tp, Dp) and used for multiple model runs to better account for regional and directional flooding affects. Model results are combined and compiled into scenario-specific composites of flood projection. Digital Elevation Model (DEM): Our seamless, topobathymetric digital elevation model (DEM) was based largely upon the Coastal California TopoBathy Merge Project DEM, with some modifications performed by the USGS Earth Resources Observation and Science (EROS) Center to incorporate the most recent, high-resolution topographic and bathymetric datasets available. Topography is derived from bare-earth light detection and ranging (lidar) data collected in 2009-2011 for the CA Coastal Conservancy Lidar Project and bathymetry from 2009-2010 bathymetric lidar as well as acoustic multi- and single-beam data collected primarily between 2001 and 2013. The DEM was constructed to define the shape of nearshore, beach, and cliff surfaces as accurately as possible, utilizing dozens of bathymetric and topographic data sets. These data were used to populate the majority of the Tier I and II grids. To describe and include impacts from long-term shoreline evolution, including cumulative storm activity, seasonal trends, ENSO, and SLR, the DEM was modified for each SLR scenario. Long-term shoreline (Vitousek and Barnard, 2015) and cliff (Limber and others, 2015) erosion projections were efficiently combined along the cross-shore transects to evolve the shore-normal profiles. Elevation changes from the profiles were spatially-merged for a cohesive, 3D depiction of coastal evolution used to modify the DEM. These data are used to generate initial profiles of the 4,802 CSTs used for Phase 2 Tier III XBeach modeling and determining final projected flood depths in each SLR scenario. All data are referenced to NAD83 horizontal datum and NAVD88 vertical datum. Data for Tiers II and III are projected in UTM, zone 11. Outputs include: Projected ocean current velocities for the 100-year storm and 0.0 m sea-level rise scenario. Data correspond to the near-shore region including areas vulnerable to coastal flooding due to storm surge, sea-level anomalies, tide elevation, and wave run-up during the same storm and sea-level rise simulation. References Cited: Howell, S., Smith-Konter, B., Frazer, N., Tong, X., and Sandwell, D., 2016, The vertical fingerprint of earthquake cycle loading in southern California: Nature Geoscience, v. 9, p. 611-614, doi:10.1038/ngeo2741. Limber, P., Barnard, P.L. and Hapke., C., 2015, Towards projecting the retreat of California’s coastal cliffs during the 21st Century: in, Wang, P., Rosati, J.D., and Cheng, J., (eds.), The Proceedings of the Coastal Sediments: 2015, World Scientific, 14 p., doi:10.1142/9789814689977_0245 Roelvink, J.A., Reniers, A., van Dongeren, A.R., van Thiel de Vries, J., McCall, R., and Lescinski, J., 2009, Modeling storm impacts on beaches, dunes and barrier islands: Coastal Engineering, v. 56, p. 1,133–1,152, doi:10.1016/j.coastaleng.2009.08.006. Tolman, H.L., Balasubramaniyan, B., Burroughs, L.D., Chalikov, D.V., Chao, Y.Y., Chen H.S., Gerald, V.M., 2002, Development and implementation of wind generated ocean surface wave models at NCEP: Weather and Forecasting, v. 17, p. 311-333. Vitousek, S. and Barnard, P.L., 2015, A non-linear, implicit one-line model to predict long-term shoreline change: in, Wang, P., Rosati, J.D., and Cheng, J., (eds.), The Proceedings of the Coastal Sediments: 2015, World Scientific, 14 p., doi:10.1142/9789814689977_0215.

Projected Hazard: Model-derived ocean current velocities (in meters per second) for the given storm condition and sea-level rise (SLR) scenario. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the model summary and inspect output carefully. Data are complete for the information presented. Details: Model background: The CoSMoS model comprises three tiers. Tier I consists of one Delft3D hydrodynamics FLOW grid for computation of tides, water level variations, flows, and currents and one SWAN grid for computation of wave generation and propagation across the continental shelf. The FLOW and SWAN models are two-way coupled so that tidal currents are accounted for in wave propagation and growth and conversely, so that orbital velocities generated by waves impart changes on tidal currents. The Tier I SWAN and FLOW models consist of identical structured curvilinear grids that extend from far offshore to the shore and range in resolution from 0.5 km in the offshore to 0.2 km in the nearshore. Spatially varying astronomic tidal amplitudes and phases and steric rises in water levels due to large-scale effects (for example, a prolonged rise in sea level) are applied along all open boundaries of the Tier I FLOW grid. Winds (split into eastward and northward components) and sea-level pressure (SLP) fields from CaRD10 (Dr. Dan Cayan, Scripps Institute of Oceanography, Los Angeles, California, written commun., 2014) that vary in both space and time are applied to all grid cells at each model time-step. Deep-water wave conditions, applied at the open boundaries of the Tier I SWAN model runs, were projected for the 21st century Representative Concentration Pathway (RCP) 4.5 climate scenario (2011-2100) using the WaveWatch III numerical wave model (Tolman and others, 2002) and 3-hourly winds from the GFDL-ESM2M Global Climate Model (GCM). Tier II provides higher resolution near the shore and in areas that require greater resolution of physical processes (such as bays, harbors, and estuaries). A single nested outer grid and multiple two-way coupled domain decomposition (DD) structured grids allow for local grid refinement and higher resolution where needed. Tier II was segmented into 11 sections along the Southern California Bight, to reduce computation time and complete runs within computational limitations. Water-level and Neumann time-series, extracted from Tier I simulations, are applied to the shore-parallel and lateral open boundaries of each Tier II sub-model outer grid respectively. Several of the sub-models proved to be unstable with lateral Neumann boundaries; for those cases one or both of the lateral boundaries were converted to water-level time-series or left unassigned. The open-boundary time-series are extracted from completed Tier I simulations so that there is no communication from Tier II to Tier I. Because this one-way nesting could produce erroneous results near the boundaries of Tier II and because data near any model boundary are always suspect, Tier II sub-model extents were designed to overlap in the along-coast direction. In the landward direction, Tier II DD grids extend to the 10-m topographic contour; exceptions exist where channels (such as the Los Angeles River) or other low-lying regions extend very far inland. Space- and time-varying wind and SLP fields, identical to those used in Tier I simulations, are applied to all Tier II DD grids to allow for wind-setup and local inverse barometer effects (IBE, rise or depression of water levels in response to atmospheric pressure gradients). A total of 42 time-series fluvial discharges are included in the Tier II FLOW domains in an effort to simulate exacerbated flooding caused by backflow at the confluence of high river seaward flows and elevated coastal surge levels migrating inland. Time-varying fluvial discharges are applied either at the closed boundaries or distributed as point sources within the relevant model domains. Wave computations are accomplished with the SWAN model using two grids for each Tier II sub-model: one larger grid covering the same area as the outer FLOW grid and a second finer resolution two-way coupled nearshore nested grid. The nearshore grid extends from approximately 800-1,000 m water depth up to 8-10 m elevations onshore. The landward extension is included to allow for wave computations of the higher SLR scenarios. Time- and space-varying 2D wave spectra extracted from previously completed Tier I simulations are applied approximately every kilometer along the open boundaries of the outer Tier II sub-model SWAN grids. The same space- and time-varying wind fields used in Tier I simulations are also applied to both Tier II SWAN grids to allow for computation of local wave generation. Tier III for the entire Southern California Bight consists of 4,802 cross-shore transects (CST) spaced approximately 100 m apart in the along-shore direction. The profiles extend from the -15 m isobath to at least 10 m above NAVD88. The CSTs are truncated for cases where a lagoon or other waterway exists on the landward end of the profile. Time-varying water levels and wave parameters (significant wave heights, Hs; peak periods, Tp; and peak incident wave directions, Dp), extracted from Tier II grid cells that coincide with the seaward end of the CSTs, are applied at the open boundary of each CST. The XBeach model is run in a hydrostatic (no vertical pressure gradients) mode including event-based morphodynamic change. Wave propagation, two-way wave-current interaction, water-level variations, and wave runup are computed at each transect. XBeach simulations are included in the CoSMoS model to account for infragravity waves that can significantly extend the reach of wave runup (Roelvink and others, 2009) compared to short-wave incident waves. The U.S. west coast is particularly susceptible to infragravity waves at the shore due to breaking of long-period swell waves (Tp > 15). Resulting water levels (WLs) from both Delft3D (high interest bays and marshes) and open-coast XBeach (CSTs) were spatially combined and interpolated to a 10 m grid. These WL elevations are differenced from the originating 2 m digital elevation model (DEM) to determine final flooding extent and depth of flooding. Events: The model system is run for pre-determined scenarios of interest such as the 1-yr or 100-yr storm event in combination with sea-level rise. Storms are first identified from time-series of total water level proxies (TWLpx) at the shore. TWLpx are computed for the majority of the 21st century (2010-2100), assuming a linear super-position of the major processes that contribute to the overall total water level. TWLpx time-series are then evaluated for extreme events, which define the boundary conditions for subsequent modeling with CoSMoS. Multiple 100-yr events are determined (varying Hs, Tp, Dp) and used for multiple model runs to better account for regional and directional flooding affects. Model results are combined and compiled into scenario-specific composites of flood projection. Digital Elevation Model (DEM): Our seamless, topobathymetric digital elevation model (DEM) was based largely upon the Coastal California TopoBathy Merge Project DEM, with some modifications performed by the USGS Earth Resources Observation and Science (EROS) Center to incorporate the most recent, high-resolution topographic and bathymetric datasets available. Topography is derived from bare-earth light detection and ranging (lidar) data collected in 2009-2011 for the CA Coastal Conservancy Lidar Project and bathymetry from 2009-2010 bathymetric lidar as well as acoustic multi- and single-beam data collected primarily between 2001 and 2013. The DEM was constructed to define the shape of nearshore, beach, and cliff surfaces as accurately as possible, utilizing dozens of bathymetric and topographic data sets. These data were used to populate the majority of the Tier I and II grids. To describe and include impacts from long-term shoreline evolution, including cumulative storm activity, seasonal trends, ENSO, and SLR, the DEM was modified for each SLR scenario. Long-term shoreline (Vitousek and Barnard, 2015) and cliff (Limber and others, 2015) erosion projections were efficiently combined along the cross-shore transects to evolve the shore-normal profiles. Elevation changes from the profiles were spatially-merged for a cohesive, 3D depiction of coastal evolution used to modify the DEM. These data are used to generate initial profiles of the 4,802 CSTs used for Phase 2 Tier III XBeach modeling and determining final projected flood depths in each SLR scenario. All data are referenced to NAD83 horizontal datum and NAVD88 vertical datum. Data for Tiers II and III are projected in UTM, zone 11. Outputs include: Projected ocean current velocities for the 100-year storm and 0.0 m sea-level rise scenario. Data correspond to the near-shore region including areas vulnerable to coastal flooding due to storm surge, sea-level anomalies, tide elevation, and wave run-up during the same storm and sea-level rise simulation. References Cited: Howell, S., Smith-Konter, B., Frazer, N., Tong, X., and Sandwell, D., 2016, The vertical fingerprint of earthquake cycle loading in southern California: Nature Geoscience, v. 9, p. 611-614, doi:10.1038/ngeo2741. Limber, P., Barnard, P.L. and Hapke., C., 2015, Towards projecting the retreat of California’s coastal cliffs during the 21st Century: in, Wang, P., Rosati, J.D., and Cheng, J., (eds.), The Proceedings of the Coastal Sediments: 2015, World Scientific, 14 p., doi:10.1142/9789814689977_0245 Roelvink, J.A., Reniers, A., van Dongeren, A.R., van Thiel de Vries, J., McCall, R., and Lescinski, J., 2009, Modeling storm impacts on beaches, dunes and barrier islands: Coastal Engineering, v. 56, p. 1,133–1,152, doi:10.1016/j.coastaleng.2009.08.006. Tolman, H.L., Balasubramaniyan, B., Burroughs, L.D., Chalikov, D.V., Chao, Y.Y., Chen H.S., Gerald, V.M., 2002, Development and implementation of wind generated ocean surface wave models at NCEP: Weather and Forecasting, v. 17, p. 311-333. Vitousek, S. and Barnard, P.L., 2015, A non-linear, implicit one-line model to predict long-term shoreline change: in, Wang, P., Rosati, J.D., and Cheng, J., (eds.), The Proceedings of the Coastal Sediments: 2015, World Scientific, 14 p., doi:10.1142/9789814689977_0215.

Projected Hazard: Model-derived total water levels (in meters) for the given storm condition and sea-level rise (SLR) scenario. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the model summary and inspect output carefully. Data are complete for the information presented. Details: Model background: The CoSMoS model comprises three tiers. Tier I consists of one Delft3D hydrodynamics FLOW grid for computation of tides, water level variations, flows, and currents and one SWAN grid for computation of wave generation and propagation across the continental shelf. The FLOW and SWAN models are two-way coupled so that tidal currents are accounted for in wave propagation and growth and conversely, so that orbital velocities generated by waves impart changes on tidal currents. The Tier I SWAN and FLOW models consist of identical structured curvilinear grids that extend from far offshore to the shore and range in resolution from 0.5 km in the offshore to 0.2 km in the nearshore. Spatially varying astronomic tidal amplitudes and phases and steric rises in water levels due to large-scale effects (for example, a prolonged rise in sea level) are applied along all open boundaries of the Tier I FLOW grid. Winds (split into eastward and northward components) and sea-level pressure (SLP) fields from CaRD10 (Dr. Dan Cayan, Scripps Institute of Oceanography, Los Angeles, California, written commun., 2014) that vary in both space and time are applied to all grid cells at each model time-step. Deep-water wave conditions, applied at the open boundaries of the Tier I SWAN model runs, were projected for the 21st century Representative Concentration Pathway (RCP) 4.5 climate scenario (2011-2100) using the WaveWatch III numerical wave model (Tolman and others, 2002) and 3-hourly winds from the GFDL-ESM2M Global Climate Model (GCM). Tier II provides higher resolution near the shore and in areas that require greater resolution of physical processes (such as bays, harbors, and estuaries). A single nested outer grid and multiple two-way coupled domain decomposition (DD) structured grids allow for local grid refinement and higher resolution where needed. Tier II was segmented into 11 sections along the Southern California Bight, to reduce computation time and complete runs within computational limitations. Water-level and Neumann time-series, extracted from Tier I simulations, are applied to the shore-parallel and lateral open boundaries of each Tier II sub-model outer grid respectively. Several of the sub-models proved to be unstable with lateral Neumann boundaries; for those cases one or both of the lateral boundaries were converted to water-level time-series or left unassigned. The open-boundary time-series are extracted from completed Tier I simulations so that there is no communication from Tier II to Tier I. Because this one-way nesting could produce erroneous results near the boundaries of Tier II and because data near any model boundary are always suspect, Tier II sub-model extents were designed to overlap in the along-coast direction. In the landward direction, Tier II DD grids extend to the 10-m topographic contour; exceptions exist where channels (such as the Los Angeles River) or other low-lying regions extend very far inland. Space- and time-varying wind and SLP fields, identical to those used in Tier I simulations, are applied to all Tier II DD grids to allow for wind-setup and local inverse barometer effects (IBE, rise or depression of water levels in response to atmospheric pressure gradients). A total of 42 time-series fluvial discharges are included in the Tier II FLOW domains in an effort to simulate exacerbated flooding caused by backflow at the confluence of high river seaward flows and elevated coastal surge levels migrating inland. Time-varying fluvial discharges are applied either at the closed boundaries or distributed as point sources within the relevant model domains. Wave computations are accomplished with the SWAN model using two grids for each Tier II sub-model: one larger grid covering the same area as the outer FLOW grid and a second finer resolution two-way coupled nearshore nested grid. The nearshore grid extends from approximately 800-1,000 m water depth up to 8-10 m elevations onshore. The landward extension is included to allow for wave computations of the higher SLR scenarios. Time- and space-varying 2D wave spectra extracted from previously completed Tier I simulations are applied approximately every kilometer along the open boundaries of the outer Tier II sub-model SWAN grids. The same space- and time-varying wind fields used in Tier I simulations are also applied to both Tier II SWAN grids to allow for computation of local wave generation. Tier III for the entire Southern California Bight consists of 4,802 cross-shore transects (CST) spaced approximately 100 m apart in the along-shore direction. The profiles extend from the -15 m isobath to at least 10 m above NAVD88. The CSTs are truncated for cases where a lagoon or other waterway exists on the landward end of the profile. Time-varying water levels and wave parameters (significant wave heights, Hs; peak periods, Tp; and peak incident wave directions, Dp), extracted from Tier II grid cells that coincide with the seaward end of the CSTs, are applied at the open boundary of each CST. The XBeach model is run in a hydrostatic (no vertical pressure gradients) mode including event-based morphodynamic change. Wave propagation, two-way wave-current interaction, water-level variations, and wave runup are computed at each transect. XBeach simulations are included in the CoSMoS model to account for infragravity waves that can significantly extend the reach of wave runup (Roelvink and others, 2009) compared to short-wave incident waves. The U.S. west coast is particularly susceptible to infragravity waves at the shore due to breaking of long-period swell waves (Tp > 15). Resulting water levels (WLs) from both Delft3D (high interest bays and marshes) and open-coast XBeach (CSTs) were spatially combined and interpolated to a 10 m grid. These WL elevations are differenced from the originating 2 m digital elevation model (DEM) to determine final flooding extent and depth of flooding. Events: The model system is run for pre-determined scenarios of interest such as the 1-yr or 100-yr storm event in combination with sea-level rise. Storms are first identified from time-series of total water level proxies (TWLpx) at the shore. TWLpx are computed for the majority of the 21st century (2010-2100), assuming a linear super-position of the major processes that contribute to the overall total water level. TWLpx time-series are then evaluated for extreme events, which define the boundary conditions for subsequent modeling with CoSMoS. Multiple 100-yr events are determined (varying Hs, Tp, Dp) and used for multiple model runs to better account for regional and directional flooding affects. Model results are combined and compiled into scenario-specific composites of flood projection. Digital Elevation Model (DEM): Our seamless, topobathymetric digital elevation model (DEM) was based largely upon the Coastal California TopoBathy Merge Project DEM, with some modifications performed by the USGS Earth Resources Observation and Science (EROS) Center to incorporate the most recent, high-resolution topographic and bathymetric datasets available. Topography is derived from bare-earth light detection and ranging (lidar) data collected in 2009-2011 for the CA Coastal Conservancy Lidar Project and bathymetry from 2009-2010 bathymetric lidar as well as acoustic multi- and single-beam data collected primarily between 2001 and 2013. The DEM was constructed to define the shape of nearshore, beach, and cliff surfaces as accurately as possible, utilizing dozens of bathymetric and topographic data sets. These data were used to populate the majority of the Tier I and II grids. To describe and include impacts from long-term shoreline evolution, including cumulative storm activity, seasonal trends, ENSO, and SLR, the DEM was modified for each SLR scenario. Long-term shoreline (Vitousek and Barnard, 2015) and cliff (Limber and others, 2015) erosion projections were efficiently combined along the cross-shore transects to evolve the shore-normal profiles. Elevation changes from the profiles were spatially-merged for a cohesive, 3D depiction of coastal evolution used to modify the DEM. These data are used to generate initial profiles of the 4,802 CSTs used for Phase 2 Tier III XBeach modeling and determining final projected flood depths in each SLR scenario. All data are referenced to NAD83 horizontal datum and NAVD88 vertical datum. Data for Tiers II and III are projected in UTM, zone 11. Outputs include: Projected water levels for the storm and sea-level rise scenario indicated. Data correspond to the near-shore region including areas vulnerable to coastal flooding due to storm surge, sea-level anomalies, tide elevation, and wave run-up during the same storm and sea-level rise simulation. References Cited: Howell, S., Smith-Konter, B., Frazer, N., Tong, X., and Sandwell, D., 2016, The vertical fingerprint of earthquake cycle loading in southern California: Nature Geoscience, v. 9, p. 611-614, doi:10.1038/ngeo2741. Limber, P., Barnard, P.L. and Hapke., C., 2015, Towards projecting the retreat of California’s coastal cliffs during the 21st Century: in, Wang, P., Rosati, J.D., and Cheng, J., (eds.), The Proceedings of the Coastal Sediments: 2015, World Scientific, 14 p., doi:10.1142/9789814689977_0245 Roelvink, J.A., Reniers, A., van Dongeren, A.R., van Thiel de Vries, J., McCall, R., and Lescinski, J., 2009, Modeling storm impacts on beaches, dunes and barrier islands: Coastal Engineering, v. 56, p. 1,133–1,152, doi:10.1016/j.coastaleng.2009.08.006. Tolman, H.L., Balasubramaniyan, B., Burroughs, L.D., Chalikov, D.V., Chao, Y.Y., Chen H.S., Gerald, V.M., 2002, Development and implementation of wind generated ocean surface wave models at NCEP: Weather and Forecasting, v. 17, p. 311-333. Vitousek, S. and Barnard, P.L., 2015, A non-linear, implicit one-line model to predict long-term shoreline change: in, Wang, P., Rosati, J.D., and Cheng, J., (eds.), The Proceedings of the Coastal Sediments: 2015, World Scientific, 14 p., doi:10.1142/9789814689977_0215.

Projected Hazard: Model-derived total water levels (in meters) for the given storm condition and sea-level rise (SLR) scenario. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the model summary and inspect output carefully. Data are complete for the information presented. Details: Model background: The CoSMoS model comprises three tiers. Tier I consists of one Delft3D hydrodynamics FLOW grid for computation of tides, water level variations, flows, and currents and one SWAN grid for computation of wave generation and propagation across the continental shelf. The FLOW and SWAN models are two-way coupled so that tidal currents are accounted for in wave propagation and growth and conversely, so that orbital velocities generated by waves impart changes on tidal currents. The Tier I SWAN and FLOW models consist of identical structured curvilinear grids that extend from far offshore to the shore and range in resolution from 0.5 km in the offshore to 0.2 km in the nearshore. Spatially varying astronomic tidal amplitudes and phases and steric rises in water levels due to large-scale effects (for example, a prolonged rise in sea level) are applied along all open boundaries of the Tier I FLOW grid. Winds (split into eastward and northward components) and sea-level pressure (SLP) fields from CaRD10 (Dr. Dan Cayan, Scripps Institute of Oceanography, Los Angeles, California, written commun., 2014) that vary in both space and time are applied to all grid cells at each model time-step. Deep-water wave conditions, applied at the open boundaries of the Tier I SWAN model runs, were projected for the 21st century Representative Concentration Pathway (RCP) 4.5 climate scenario (2011-2100) using the WaveWatch III numerical wave model (Tolman and others, 2002) and 3-hourly winds from the GFDL-ESM2M Global Climate Model (GCM). Tier II provides higher resolution near the shore and in areas that require greater resolution of physical processes (such as bays, harbors, and estuaries). A single nested outer grid and multiple two-way coupled domain decomposition (DD) structured grids allow for local grid refinement and higher resolution where needed. Tier II was segmented into 11 sections along the Southern California Bight, to reduce computation time and complete runs within computational limitations. Water-level and Neumann time-series, extracted from Tier I simulations, are applied to the shore-parallel and lateral open boundaries of each Tier II sub-model outer grid respectively. Several of the sub-models proved to be unstable with lateral Neumann boundaries; for those cases one or both of the lateral boundaries were converted to water-level time-series or left unassigned. The open-boundary time-series are extracted from completed Tier I simulations so that there is no communication from Tier II to Tier I. Because this one-way nesting could produce erroneous results near the boundaries of Tier II and because data near any model boundary are always suspect, Tier II sub-model extents were designed to overlap in the along-coast direction. In the landward direction, Tier II DD grids extend to the 10-m topographic contour; exceptions exist where channels (such as the Los Angeles River) or other low-lying regions extend very far inland. Space- and time-varying wind and SLP fields, identical to those used in Tier I simulations, are applied to all Tier II DD grids to allow for wind-setup and local inverse barometer effects (IBE, rise or depression of water levels in response to atmospheric pressure gradients). A total of 42 time-series fluvial discharges are included in the Tier II FLOW domains in an effort to simulate exacerbated flooding caused by backflow at the confluence of high river seaward flows and elevated coastal surge levels migrating inland. Time-varying fluvial discharges are applied either at the closed boundaries or distributed as point sources within the relevant model domains. Wave computations are accomplished with the SWAN model using two grids for each Tier II sub-model: one larger grid covering the same area as the outer FLOW grid and a second finer resolution two-way coupled nearshore nested grid. The nearshore grid extends from approximately 800-1,000 m water depth up to 8-10 m elevations onshore. The landward extension is included to allow for wave computations of the higher SLR scenarios. Time- and space-varying 2D wave spectra extracted from previously completed Tier I simulations are applied approximately every kilometer along the open boundaries of the outer Tier II sub-model SWAN grids. The same space- and time-varying wind fields used in Tier I simulations are also applied to both Tier II SWAN grids to allow for computation of local wave generation. Tier III for the entire Southern California Bight consists of 4,802 cross-shore transects (CST) spaced approximately 100 m apart in the along-shore direction. The profiles extend from the -15 m isobath to at least 10 m above NAVD88. The CSTs are truncated for cases where a lagoon or other waterway exists on the landward end of the profile. Time-varying water levels and wave parameters (significant wave heights, Hs; peak periods, Tp; and peak incident wave directions, Dp), extracted from Tier II grid cells that coincide with the seaward end of the CSTs, are applied at the open boundary of each CST. The XBeach model is run in a hydrostatic (no vertical pressure gradients) mode including event-based morphodynamic change. Wave propagation, two-way wave-current interaction, water-level variations, and wave runup are computed at each transect. XBeach simulations are included in the CoSMoS model to account for infragravity waves that can significantly extend the reach of wave runup (Roelvink and others, 2009) compared to short-wave incident waves. The U.S. west coast is particularly susceptible to infragravity waves at the shore due to breaking of long-period swell waves (Tp > 15). Resulting water levels (WLs) from both Delft3D (high interest bays and marshes) and open-coast XBeach (CSTs) were spatially combined and interpolated to a 10 m grid. These WL elevations are differenced from the originating 2 m digital elevation model (DEM) to determine final flooding extent and depth of flooding. Events: The model system is run for pre-determined scenarios of interest such as the 1-yr or 100-yr storm event in combination with sea-level rise. Storms are first identified from time-series of total water level proxies (TWLpx) at the shore. TWLpx are computed for the majority of the 21st century (2010-2100), assuming a linear super-position of the major processes that contribute to the overall total water level. TWLpx time-series are then evaluated for extreme events, which define the boundary conditions for subsequent modeling with CoSMoS. Multiple 100-yr events are determined (varying Hs, Tp, Dp) and used for multiple model runs to better account for regional and directional flooding affects. Model results are combined and compiled into scenario-specific composites of flood projection. Digital Elevation Model (DEM): Our seamless, topobathymetric digital elevation model (DEM) was based largely upon the Coastal California TopoBathy Merge Project DEM, with some modifications performed by the USGS Earth Resources Observation and Science (EROS) Center to incorporate the most recent, high-resolution topographic and bathymetric datasets available. Topography is derived from bare-earth light detection and ranging (lidar) data collected in 2009-2011 for the CA Coastal Conservancy Lidar Project and bathymetry from 2009-2010 bathymetric lidar as well as acoustic multi- and single-beam data collected primarily between 2001 and 2013. The DEM was constructed to define the shape of nearshore, beach, and cliff surfaces as accurately as possible, utilizing dozens of bathymetric and topographic data sets. These data were used to populate the majority of the Tier I and II grids. To describe and include impacts from long-term shoreline evolution, including cumulative storm activity, seasonal trends, ENSO, and SLR, the DEM was modified for each SLR scenario. Long-term shoreline (Vitousek and Barnard, 2015) and cliff (Limber and others, 2015) erosion projections were efficiently combined along the cross-shore transects to evolve the shore-normal profiles. Elevation changes from the profiles were spatially-merged for a cohesive, 3D depiction of coastal evolution used to modify the DEM. These data are used to generate initial profiles of the 4,802 CSTs used for Phase 2 Tier III XBeach modeling and determining final projected flood depths in each SLR scenario. All data are referenced to NAD83 horizontal datum and NAVD88 vertical datum. Data for Tiers II and III are projected in UTM, zone 11. Outputs include: Projected water levels for the storm and sea-level rise scenario indicated. Data correspond to the near-shore region including areas vulnerable to coastal flooding due to storm surge, sea-level anomalies, tide elevation, and wave run-up during the same storm and sea-level rise simulation. References Cited: Howell, S., Smith-Konter, B., Frazer, N., Tong, X., and Sandwell, D., 2016, The vertical fingerprint of earthquake cycle loading in southern California: Nature Geoscience, v. 9, p. 611-614, doi:10.1038/ngeo2741. Limber, P., Barnard, P.L. and Hapke., C., 2015, Towards projecting the retreat of California’s coastal cliffs during the 21st Century: in, Wang, P., Rosati, J.D., and Cheng, J., (eds.), The Proceedings of the Coastal Sediments: 2015, World Scientific, 14 p., doi:10.1142/9789814689977_0245 Roelvink, J.A., Reniers, A., van Dongeren, A.R., van Thiel de Vries, J., McCall, R., and Lescinski, J., 2009, Modeling storm impacts on beaches, dunes and barrier islands: Coastal Engineering, v. 56, p. 1,133–1,152, doi:10.1016/j.coastaleng.2009.08.006. Tolman, H.L., Balasubramaniyan, B., Burroughs, L.D., Chalikov, D.V., Chao, Y.Y., Chen H.S., Gerald, V.M., 2002, Development and implementation of wind generated ocean surface wave models at NCEP: Weather and Forecasting, v. 17, p. 311-333. Vitousek, S. and Barnard, P.L., 2015, A non-linear, implicit one-line model to predict long-term shoreline change: in, Wang, P., Rosati, J.D., and Cheng, J., (eds.), The Proceedings of the Coastal Sediments: 2015, World Scientific, 14 p., doi:10.1142/9789814689977_0215.

Projected Hazard: Model-derived total water levels (in meters) for the given storm condition and sea-level rise (SLR) scenario. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the model summary and inspect output carefully. Data are complete for the information presented. Details: Model background: The CoSMoS model comprises three tiers. Tier I consists of one Delft3D hydrodynamics FLOW grid for computation of tides, water level variations, flows, and currents and one SWAN grid for computation of wave generation and propagation across the continental shelf. The FLOW and SWAN models are two-way coupled so that tidal currents are accounted for in wave propagation and growth and conversely, so that orbital velocities generated by waves impart changes on tidal currents. The Tier I SWAN and FLOW models consist of identical structured curvilinear grids that extend from far offshore to the shore and range in resolution from 0.5 km in the offshore to 0.2 km in the nearshore. Spatially varying astronomic tidal amplitudes and phases and steric rises in water levels due to large-scale effects (for example, a prolonged rise in sea level) are applied along all open boundaries of the Tier I FLOW grid. Winds (split into eastward and northward components) and sea-level pressure (SLP) fields from CaRD10 (Dr. Dan Cayan, Scripps Institute of Oceanography, Los Angeles, California, written commun., 2014) that vary in both space and time are applied to all grid cells at each model time-step. Deep-water wave conditions, applied at the open boundaries of the Tier I SWAN model runs, were projected for the 21st century Representative Concentration Pathway (RCP) 4.5 climate scenario (2011-2100) using the WaveWatch III numerical wave model (Tolman and others, 2002) and 3-hourly winds from the GFDL-ESM2M Global Climate Model (GCM). Tier II provides higher resolution near the shore and in areas that require greater resolution of physical processes (such as bays, harbors, and estuaries). A single nested outer grid and multiple two-way coupled domain decomposition (DD) structured grids allow for local grid refinement and higher resolution where needed. Tier II was segmented into 11 sections along the Southern California Bight, to reduce computation time and complete runs within computational limitations. Water-level and Neumann time-series, extracted from Tier I simulations, are applied to the shore-parallel and lateral open boundaries of each Tier II sub-model outer grid respectively. Several of the sub-models proved to be unstable with lateral Neumann boundaries; for those cases one or both of the lateral boundaries were converted to water-level time-series or left unassigned. The open-boundary time-series are extracted from completed Tier I simulations so that there is no communication from Tier II to Tier I. Because this one-way nesting could produce erroneous results near the boundaries of Tier II and because data near any model boundary are always suspect, Tier II sub-model extents were designed to overlap in the along-coast direction. In the landward direction, Tier II DD grids extend to the 10-m topographic contour; exceptions exist where channels (such as the Los Angeles River) or other low-lying regions extend very far inland. Space- and time-varying wind and SLP fields, identical to those used in Tier I simulations, are applied to all Tier II DD grids to allow for wind-setup and local inverse barometer effects (IBE, rise or depression of water levels in response to atmospheric pressure gradients). A total of 42 time-series fluvial discharges are included in the Tier II FLOW domains in an effort to simulate exacerbated flooding caused by backflow at the confluence of high river seaward flows and elevated coastal surge levels migrating inland. Time-varying fluvial discharges are applied either at the closed boundaries or distributed as point sources within the relevant model domains. Wave computations are accomplished with the SWAN model using two grids for each Tier II sub-model: one larger grid covering the same area as the outer FLOW grid and a second finer resolution two-way coupled nearshore nested grid. The nearshore grid extends from approximately 800-1,000 m water depth up to 8-10 m elevations onshore. The landward extension is included to allow for wave computations of the higher SLR scenarios. Time- and space-varying 2D wave spectra extracted from previously completed Tier I simulations are applied approximately every kilometer along the open boundaries of the outer Tier II sub-model SWAN grids. The same space- and time-varying wind fields used in Tier I simulations are also applied to both Tier II SWAN grids to allow for computation of local wave generation. Tier III for the entire Southern California Bight consists of 4,802 cross-shore transects (CST) spaced approximately 100 m apart in the along-shore direction. The profiles extend from the -15 m isobath to at least 10 m above NAVD88. The CSTs are truncated for cases where a lagoon or other waterway exists on the landward end of the profile. Time-varying water levels and wave parameters (significant wave heights, Hs; peak periods, Tp; and peak incident wave directions, Dp), extracted from Tier II grid cells that coincide with the seaward end of the CSTs, are applied at the open boundary of each CST. The XBeach model is run in a hydrostatic (no vertical pressure gradients) mode including event-based morphodynamic change. Wave propagation, two-way wave-current interaction, water-level variations, and wave runup are computed at each transect. XBeach simulations are included in the CoSMoS model to account for infragravity waves that can significantly extend the reach of wave runup (Roelvink and others, 2009) compared to short-wave incident waves. The U.S. west coast is particularly susceptible to infragravity waves at the shore due to breaking of long-period swell waves (Tp > 15). Resulting water levels (WLs) from both Delft3D (high interest bays and marshes) and open-coast XBeach (CSTs) were spatially combined and interpolated to a 10 m grid. These WL elevations are differenced from the originating 2 m digital elevation model (DEM) to determine final flooding extent and depth of flooding. Events: The model system is run for pre-determined scenarios of interest such as the 1-yr or 100-yr storm event in combination with sea-level rise. Storms are first identified from time-series of total water level proxies (TWLpx) at the shore. TWLpx are computed for the majority of the 21st century (2010-2100), assuming a linear super-position of the major processes that contribute to the overall total water level. TWLpx time-series are then evaluated for extreme events, which define the boundary conditions for subsequent modeling with CoSMoS. Multiple 100-yr events are determined (varying Hs, Tp, Dp) and used for multiple model runs to better account for regional and directional flooding affects. Model results are combined and compiled into scenario-specific composites of flood projection. Digital Elevation Model (DEM): Our seamless, topobathymetric digital elevation model (DEM) was based largely upon the Coastal California TopoBathy Merge Project DEM, with some modifications performed by the USGS Earth Resources Observation and Science (EROS) Center to incorporate the most recent, high-resolution topographic and bathymetric datasets available. Topography is derived from bare-earth light detection and ranging (lidar) data collected in 2009-2011 for the CA Coastal Conservancy Lidar Project and bathymetry from 2009-2010 bathymetric lidar as well as acoustic multi- and single-beam data collected primarily between 2001 and 2013. The DEM was constructed to define the shape of nearshore, beach, and cliff surfaces as accurately as possible, utilizing dozens of bathymetric and topographic data sets. These data were used to populate the majority of the Tier I and II grids. To describe and include impacts from long-term shoreline evolution, including cumulative storm activity, seasonal trends, ENSO, and SLR, the DEM was modified for each SLR scenario. Long-term shoreline (Vitousek and Barnard, 2015) and cliff (Limber and others, 2015) erosion projections were efficiently combined along the cross-shore transects to evolve the shore-normal profiles. Elevation changes from the profiles were spatially-merged for a cohesive, 3D depiction of coastal evolution used to modify the DEM. These data are used to generate initial profiles of the 4,802 CSTs used for Phase 2 Tier III XBeach modeling and determining final projected flood depths in each SLR scenario. All data are referenced to NAD83 horizontal datum and NAVD88 vertical datum. Data for Tiers II and III are projected in UTM, zone 11. Outputs include: Projected water levels for the storm and sea-level rise scenario indicated. Data correspond to the near-shore region including areas vulnerable to coastal flooding due to storm surge, sea-level anomalies, tide elevation, and wave run-up during the same storm and sea-level rise simulation. References Cited: Howell, S., Smith-Konter, B., Frazer, N., Tong, X., and Sandwell, D., 2016, The vertical fingerprint of earthquake cycle loading in southern California: Nature Geoscience, v. 9, p. 611-614, doi:10.1038/ngeo2741. Limber, P., Barnard, P.L. and Hapke., C., 2015, Towards projecting the retreat of California’s coastal cliffs during the 21st Century: in, Wang, P., Rosati, J.D., and Cheng, J., (eds.), The Proceedings of the Coastal Sediments: 2015, World Scientific, 14 p., doi:10.1142/9789814689977_0245 Roelvink, J.A., Reniers, A., van Dongeren, A.R., van Thiel de Vries, J., McCall, R., and Lescinski, J., 2009, Modeling storm impacts on beaches, dunes and barrier islands: Coastal Engineering, v. 56, p. 1,133–1,152, doi:10.1016/j.coastaleng.2009.08.006. Tolman, H.L., Balasubramaniyan, B., Burroughs, L.D., Chalikov, D.V., Chao, Y.Y., Chen H.S., Gerald, V.M., 2002, Development and implementation of wind generated ocean surface wave models at NCEP: Weather and Forecasting, v. 17, p. 311-333. Vitousek, S. and Barnard, P.L., 2015, A non-linear, implicit one-line model to predict long-term shoreline change: in, Wang, P., Rosati, J.D., and Cheng, J., (eds.), The Proceedings of the Coastal Sediments: 2015, World Scientific, 14 p., doi:10.1142/9789814689977_0215.

Projected Hazard: Model-derived total water levels (in meters) for the given storm condition and sea-level rise (SLR) scenario. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the model summary and inspect output carefully. Data are complete for the information presented. Details: Model background: The CoSMoS model comprises three tiers. Tier I consists of one Delft3D hydrodynamics FLOW grid for computation of tides, water level variations, flows, and currents and one SWAN grid for computation of wave generation and propagation across the continental shelf. The FLOW and SWAN models are two-way coupled so that tidal currents are accounted for in wave propagation and growth and conversely, so that orbital velocities generated by waves impart changes on tidal currents. The Tier I SWAN and FLOW models consist of identical structured curvilinear grids that extend from far offshore to the shore and range in resolution from 0.5 km in the offshore to 0.2 km in the nearshore. Spatially varying astronomic tidal amplitudes and phases and steric rises in water levels due to large-scale effects (for example, a prolonged rise in sea level) are applied along all open boundaries of the Tier I FLOW grid. Winds (split into eastward and northward components) and sea-level pressure (SLP) fields from CaRD10 (Dr. Dan Cayan, Scripps Institute of Oceanography, Los Angeles, California, written commun., 2014) that vary in both space and time are applied to all grid cells at each model time-step. Deep-water wave conditions, applied at the open boundaries of the Tier I SWAN model runs, were projected for the 21st century Representative Concentration Pathway (RCP) 4.5 climate scenario (2011-2100) using the WaveWatch III numerical wave model (Tolman and others, 2002) and 3-hourly winds from the GFDL-ESM2M Global Climate Model (GCM). Tier II provides higher resolution near the shore and in areas that require greater resolution of physical processes (such as bays, harbors, and estuaries). A single nested outer grid and multiple two-way coupled domain decomposition (DD) structured grids allow for local grid refinement and higher resolution where needed. Tier II was segmented into 11 sections along the Southern California Bight, to reduce computation time and complete runs within computational limitations. Water-level and Neumann time-series, extracted from Tier I simulations, are applied to the shore-parallel and lateral open boundaries of each Tier II sub-model outer grid respectively. Several of the sub-models proved to be unstable with lateral Neumann boundaries; for those cases one or both of the lateral boundaries were converted to water-level time-series or left unassigned. The open-boundary time-series are extracted from completed Tier I simulations so that there is no communication from Tier II to Tier I. Because this one-way nesting could produce erroneous results near the boundaries of Tier II and because data near any model boundary are always suspect, Tier II sub-model extents were designed to overlap in the along-coast direction. In the landward direction, Tier II DD grids extend to the 10-m topographic contour; exceptions exist where channels (such as the Los Angeles River) or other low-lying regions extend very far inland. Space- and time-varying wind and SLP fields, identical to those used in Tier I simulations, are applied to all Tier II DD grids to allow for wind-setup and local inverse barometer effects (IBE, rise or depression of water levels in response to atmospheric pressure gradients). A total of 42 time-series fluvial discharges are included in the Tier II FLOW domains in an effort to simulate exacerbated flooding caused by backflow at the confluence of high river seaward flows and elevated coastal surge levels migrating inland. Time-varying fluvial discharges are applied either at the closed boundaries or distributed as point sources within the relevant model domains. Wave computations are accomplished with the SWAN model using two grids for each Tier II sub-model: one larger grid covering the same area as the outer FLOW grid and a second finer resolution two-way coupled nearshore nested grid. The nearshore grid extends from approximately 800-1,000 m water depth up to 8-10 m elevations onshore. The landward extension is included to allow for wave computations of the higher SLR scenarios. Time- and space-varying 2D wave spectra extracted from previously completed Tier I simulations are applied approximately every kilometer along the open boundaries of the outer Tier II sub-model SWAN grids. The same space- and time-varying wind fields used in Tier I simulations are also applied to both Tier II SWAN grids to allow for computation of local wave generation. Tier III for the entire Southern California Bight consists of 4,802 cross-shore transects (CST) spaced approximately 100 m apart in the along-shore direction. The profiles extend from the -15 m isobath to at least 10 m above NAVD88. The CSTs are truncated for cases where a lagoon or other waterway exists on the landward end of the profile. Time-varying water levels and wave parameters (significant wave heights, Hs; peak periods, Tp; and peak incident wave directions, Dp), extracted from Tier II grid cells that coincide with the seaward end of the CSTs, are applied at the open boundary of each CST. The XBeach model is run in a hydrostatic (no vertical pressure gradients) mode including event-based morphodynamic change. Wave propagation, two-way wave-current interaction, water-level variations, and wave runup are computed at each transect. XBeach simulations are included in the CoSMoS model to account for infragravity waves that can significantly extend the reach of wave runup (Roelvink and others, 2009) compared to short-wave incident waves. The U.S. west coast is particularly susceptible to infragravity waves at the shore due to breaking of long-period swell waves (Tp > 15). Resulting water levels (WLs) from both Delft3D (high interest bays and marshes) and open-coast XBeach (CSTs) were spatially combined and interpolated to a 10 m grid. These WL elevations are differenced from the originating 2 m digital elevation model (DEM) to determine final flooding extent and depth of flooding. Events: The model system is run for pre-determined scenarios of interest such as the 1-yr or 100-yr storm event in combination with sea-level rise. Storms are first identified from time-series of total water level proxies (TWLpx) at the shore. TWLpx are computed for the majority of the 21st century (2010-2100), assuming a linear super-position of the major processes that contribute to the overall total water level. TWLpx time-series are then evaluated for extreme events, which define the boundary conditions for subsequent modeling with CoSMoS. Multiple 100-yr events are determined (varying Hs, Tp, Dp) and used for multiple model runs to better account for regional and directional flooding affects. Model results are combined and compiled into scenario-specific composites of flood projection. Digital Elevation Model (DEM): Our seamless, topobathymetric digital elevation model (DEM) was based largely upon the Coastal California TopoBathy Merge Project DEM, with some modifications performed by the USGS Earth Resources Observation and Science (EROS) Center to incorporate the most recent, high-resolution topographic and bathymetric datasets available. Topography is derived from bare-earth light detection and ranging (lidar) data collected in 2009-2011 for the CA Coastal Conservancy Lidar Project and bathymetry from 2009-2010 bathymetric lidar as well as acoustic multi- and single-beam data collected primarily between 2001 and 2013. The DEM was constructed to define the shape of nearshore, beach, and cliff surfaces as accurately as possible, utilizing dozens of bathymetric and topographic data sets. These data were used to populate the majority of the Tier I and II grids. To describe and include impacts from long-term shoreline evolution, including cumulative storm activity, seasonal trends, ENSO, and SLR, the DEM was modified for each SLR scenario. Long-term shoreline (Vitousek and Barnard, 2015) and cliff (Limber and others, 2015) erosion projections were efficiently combined along the cross-shore transects to evolve the shore-normal profiles. Elevation changes from the profiles were spatially-merged for a cohesive, 3D depiction of coastal evolution used to modify the DEM. These data are used to generate initial profiles of the 4,802 CSTs used for Phase 2 Tier III XBeach modeling and determining final projected flood depths in each SLR scenario. All data are referenced to NAD83 horizontal datum and NAVD88 vertical datum. Data for Tiers II and III are projected in UTM, zone 11. Outputs include: Projected water levels for the storm and sea-level rise scenario indicated. Data correspond to the near-shore region including areas vulnerable to coastal flooding due to storm surge, sea-level anomalies, tide elevation, and wave run-up during the same storm and sea-level rise simulation. References Cited: Howell, S., Smith-Konter, B., Frazer, N., Tong, X., and Sandwell, D., 2016, The vertical fingerprint of earthquake cycle loading in southern California: Nature Geoscience, v. 9, p. 611-614, doi:10.1038/ngeo2741. Limber, P., Barnard, P.L. and Hapke., C., 2015, Towards projecting the retreat of California’s coastal cliffs during the 21st Century: in, Wang, P., Rosati, J.D., and Cheng, J., (eds.), The Proceedings of the Coastal Sediments: 2015, World Scientific, 14 p., doi:10.1142/9789814689977_0245 Roelvink, J.A., Reniers, A., van Dongeren, A.R., van Thiel de Vries, J., McCall, R., and Lescinski, J., 2009, Modeling storm impacts on beaches, dunes and barrier islands: Coastal Engineering, v. 56, p. 1,133–1,152, doi:10.1016/j.coastaleng.2009.08.006. Tolman, H.L., Balasubramaniyan, B., Burroughs, L.D., Chalikov, D.V., Chao, Y.Y., Chen H.S., Gerald, V.M., 2002, Development and implementation of wind generated ocean surface wave models at NCEP: Weather and Forecasting, v. 17, p. 311-333. Vitousek, S. and Barnard, P.L., 2015, A non-linear, implicit one-line model to predict long-term shoreline change: in, Wang, P., Rosati, J.D., and Cheng, J., (eds.), The Proceedings of the Coastal Sediments: 2015, World Scientific, 14 p., doi:10.1142/9789814689977_0215.

Projected Hazard: Model-derived significant wave height (in meters) for the given storm condition and sea-level rise (SLR) scenario. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the model summary and inspect output carefully. Data are complete for the information presented. Details: Model background: The CoSMoS model comprises three tiers. Tier I consists of one Delft3D hydrodynamics FLOW grid for computation of tides, water level variations, flows, and currents and one SWAN grid for computation of wave generation and propagation across the continental shelf. The FLOW and SWAN models are two-way coupled so that tidal currents are accounted for in wave propagation and growth and conversely, so that orbital velocities generated by waves impart changes on tidal currents. The Tier I SWAN and FLOW models consist of identical structured curvilinear grids that extend from far offshore to the shore and range in resolution from 0.5 km in the offshore to 0.2 km in the nearshore. Spatially varying astronomic tidal amplitudes and phases and steric rises in water levels due to large-scale effects (for example, a prolonged rise in sea level) are applied along all open boundaries of the Tier I FLOW grid. Winds (split into eastward and northward components) and sea-level pressure (SLP) fields from CaRD10 (Dr. Dan Cayan, Scripps Institute of Oceanography, Los Angeles, California, written commun., 2014) that vary in both space and time are applied to all grid cells at each model time-step. Deep-water wave conditions, applied at the open boundaries of the Tier I SWAN model runs, were projected for the 21st century Representative Concentration Pathway (RCP) 4.5 climate scenario (2011-2100) using the WaveWatch III numerical wave model (Tolman and others, 2002) and 3-hourly winds from the GFDL-ESM2M Global Climate Model (GCM). Tier II provides higher resolution near the shore and in areas that require greater resolution of physical processes (such as bays, harbors, and estuaries). A single nested outer grid and multiple two-way coupled domain decomposition (DD) structured grids allow for local grid refinement and higher resolution where needed. Tier II was segmented into 11 sections along the Southern California Bight, to reduce computation time and complete runs within computational limitations. Water-level and Neumann time-series, extracted from Tier I simulations, are applied to the shore-parallel and lateral open boundaries of each Tier II sub-model outer grid respectively. Several of the sub-models proved to be unstable with lateral Neumann boundaries; for those cases one or both of the lateral boundaries were converted to water-level time-series or left unassigned. The open-boundary time-series are extracted from completed Tier I simulations so that there is no communication from Tier II to Tier I. Because this one-way nesting could produce erroneous results near the boundaries of Tier II and because data near any model boundary are always suspect, Tier II sub-model extents were designed to overlap in the along-coast direction. In the landward direction, Tier II DD grids extend to the 10-m topographic contour; exceptions exist where channels (such as the Los Angeles River) or other low-lying regions extend very far inland. Space- and time-varying wind and SLP fields, identical to those used in Tier I simulations, are applied to all Tier II DD grids to allow for wind-setup and local inverse barometer effects (IBE, rise or depression of water levels in response to atmospheric pressure gradients). A total of 42 time-series fluvial discharges are included in the Tier II FLOW domains in an effort to simulate exacerbated flooding caused by backflow at the confluence of high river seaward flows and elevated coastal surge levels migrating inland. Time-varying fluvial discharges are applied either at the closed boundaries or distributed as point sources within the relevant model domains. Wave computations are accomplished with the SWAN model using two grids for each Tier II sub-model: one larger grid covering the same area as the outer FLOW grid and a second finer resolution two-way coupled nearshore nested grid. The nearshore grid extends from approximately 800-1,000 m water depth up to 8-10 m elevations onshore. The landward extension is included to allow for wave computations of the higher SLR scenarios. Time- and space-varying 2D wave spectra extracted from previously completed Tier I simulations are applied approximately every kilometer along the open boundaries of the outer Tier II sub-model SWAN grids. The same space- and time-varying wind fields used in Tier I simulations are also applied to both Tier II SWAN grids to allow for computation of local wave generation. Tier III for the entire Southern California Bight consists of 4,802 cross-shore transects (CST) spaced approximately 100 m apart in the along-shore direction. The profiles extend from the -15 m isobath to at least 10 m above NAVD88. The CSTs are truncated for cases where a lagoon or other waterway exists on the landward end of the profile. Time-varying water levels and wave parameters (significant wave heights, Hs; peak periods, Tp; and peak incident wave directions, Dp), extracted from Tier II grid cells that coincide with the seaward end of the CSTs, are applied at the open boundary of each CST. The XBeach model is run in a hydrostatic (no vertical pressure gradients) mode including event-based morphodynamic change. Wave propagation, two-way wave-current interaction, water-level variations, and wave runup are computed at each transect. XBeach simulations are included in the CoSMoS model to account for infragravity waves that can significantly extend the reach of wave runup (Roelvink and others, 2009) compared to short-wave incident waves. The U.S. west coast is particularly susceptible to infragravity waves at the shore due to breaking of long-period swell waves (Tp > 15). Resulting water levels (WLs) from both Delft3D (high interest bays and marshes) and open-coast XBeach (CSTs) were spatially combined and interpolated to a 10 m grid. These WL elevations are differenced from the originating 2 m digital elevation model (DEM) to determine final flooding extent and depth of flooding. Events: The model system is run for pre-determined scenarios of interest such as the 1-yr or 100-yr storm event in combination with sea-level rise. Storms are first identified from time-series of total water level proxies (TWLpx) at the shore. TWLpx are computed for the majority of the 21st century (2010-2100), assuming a linear super-position of the major processes that contribute to the overall total water level. TWLpx time-series are then evaluated for extreme events, which define the boundary conditions for subsequent modeling with CoSMoS. Multiple 100-yr events are determined (varying Hs, Tp, Dp) and used for multiple model runs to better account for regional and directional flooding affects. Model results are combined and compiled into scenario-specific composites of flood projection. Digital Elevation Model (DEM): Our seamless, topobathymetric digital elevation model (DEM) was based largely upon the Coastal California TopoBathy Merge Project DEM, with some modifications performed by the USGS Earth Resources Observation and Science (EROS) Center to incorporate the most recent, high-resolution topographic and bathymetric datasets available. Topography is derived from bare-earth light detection and ranging (lidar) data collected in 2009-2011 for the CA Coastal Conservancy Lidar Project and bathymetry from 2009-2010 bathymetric lidar as well as acoustic multi- and single-beam data collected primarily between 2001 and 2013. The DEM was constructed to define the shape of nearshore, beach, and cliff surfaces as accurately as possible, utilizing dozens of bathymetric and topographic data sets. These data were used to populate the majority of the Tier I and II grids. To describe and include impacts from long-term shoreline evolution, including cumulative storm activity, seasonal trends, ENSO, and SLR, the DEM was modified for each SLR scenario. Long-term shoreline (Vitousek and Barnard, 2015) and cliff (Limber and others, 2015) erosion projections were efficiently combined along the cross-shore transects to evolve the shore-normal profiles. Elevation changes from the profiles were spatially-merged for a cohesive, 3D depiction of coastal evolution used to modify the DEM. These data are used to generate initial profiles of the 4,802 CSTs used for Phase 2 Tier III XBeach modeling and determining final projected flood depths in each SLR scenario. All data are referenced to NAD83 horizontal datum and NAVD88 vertical datum. Data for Tiers II and III are projected in UTM, zone 11. Outputs include: Projected wave height for the storm and sea-level rise scenario indicated. Data correspond to the near-shore region including areas vulnerable to coastal flooding due to storm surge, sea-level anomalies, tide elevation, and wave run-up during the same storm and sea-level rise simulation. References Cited: Howell, S., Smith-Konter, B., Frazer, N., Tong, X., and Sandwell, D., 2016, The vertical fingerprint of earthquake cycle loading in southern California: Nature Geoscience, v. 9, p. 611-614, doi:10.1038/ngeo2741. Limber, P., Barnard, P.L. and Hapke., C., 2015, Towards projecting the retreat of California’s coastal cliffs during the 21st Century: in, Wang, P., Rosati, J.D., and Cheng, J., (eds.), The Proceedings of the Coastal Sediments: 2015, World Scientific, 14 p., doi:10.1142/9789814689977_0245 Roelvink, J.A., Reniers, A., van Dongeren, A.R., van Thiel de Vries, J., McCall, R., and Lescinski, J., 2009, Modeling storm impacts on beaches, dunes and barrier islands: Coastal Engineering, v. 56, p. 1,133–1,152, doi:10.1016/j.coastaleng.2009.08.006. Tolman, H.L., Balasubramaniyan, B., Burroughs, L.D., Chalikov, D.V., Chao, Y.Y., Chen H.S., Gerald, V.M., 2002, Development and implementation of wind generated ocean surface wave models at NCEP: Weather and Forecasting, v. 17, p. 311-333. Vitousek, S. and Barnard, P.L., 2015, A non-linear, implicit one-line model to predict long-term shoreline change: in, Wang, P., Rosati, J.D., and Cheng, J., (eds.), The Proceedings of the Coastal Sediments: 2015, World Scientific, 14 p., doi:10.1142/9789814689977_0215.

Projected Hazard: Model-derived significant wave height (in meters) for the given storm condition and sea-level rise (SLR) scenario. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the model summary and inspect output carefully. Data are complete for the information presented. Details: Model background: The CoSMoS model comprises three tiers. Tier I consists of one Delft3D hydrodynamics FLOW grid for computation of tides, water level variations, flows, and currents and one SWAN grid for computation of wave generation and propagation across the continental shelf. The FLOW and SWAN models are two-way coupled so that tidal currents are accounted for in wave propagation and growth and conversely, so that orbital velocities generated by waves impart changes on tidal currents. The Tier I SWAN and FLOW models consist of identical structured curvilinear grids that extend from far offshore to the shore and range in resolution from 0.5 km in the offshore to 0.2 km in the nearshore. Spatially varying astronomic tidal amplitudes and phases and steric rises in water levels due to large-scale effects (for example, a prolonged rise in sea level) are applied along all open boundaries of the Tier I FLOW grid. Winds (split into eastward and northward components) and sea-level pressure (SLP) fields from CaRD10 (Dr. Dan Cayan, Scripps Institute of Oceanography, Los Angeles, California, written commun., 2014) that vary in both space and time are applied to all grid cells at each model time-step. Deep-water wave conditions, applied at the open boundaries of the Tier I SWAN model runs, were projected for the 21st century Representative Concentration Pathway (RCP) 4.5 climate scenario (2011-2100) using the WaveWatch III numerical wave model (Tolman and others, 2002) and 3-hourly winds from the GFDL-ESM2M Global Climate Model (GCM). Tier II provides higher resolution near the shore and in areas that require greater resolution of physical processes (such as bays, harbors, and estuaries). A single nested outer grid and multiple two-way coupled domain decomposition (DD) structured grids allow for local grid refinement and higher resolution where needed. Tier II was segmented into 11 sections along the Southern California Bight, to reduce computation time and complete runs within computational limitations. Water-level and Neumann time-series, extracted from Tier I simulations, are applied to the shore-parallel and lateral open boundaries of each Tier II sub-model outer grid respectively. Several of the sub-models proved to be unstable with lateral Neumann boundaries; for those cases one or both of the lateral boundaries were converted to water-level time-series or left unassigned. The open-boundary time-series are extracted from completed Tier I simulations so that there is no communication from Tier II to Tier I. Because this one-way nesting could produce erroneous results near the boundaries of Tier II and because data near any model boundary are always suspect, Tier II sub-model extents were designed to overlap in the along-coast direction. In the landward direction, Tier II DD grids extend to the 10-m topographic contour; exceptions exist where channels (such as the Los Angeles River) or other low-lying regions extend very far inland. Space- and time-varying wind and SLP fields, identical to those used in Tier I simulations, are applied to all Tier II DD grids to allow for wind-setup and local inverse barometer effects (IBE, rise or depression of water levels in response to atmospheric pressure gradients). A total of 42 time-series fluvial discharges are included in the Tier II FLOW domains in an effort to simulate exacerbated flooding caused by backflow at the confluence of high river seaward flows and elevated coastal surge levels migrating inland. Time-varying fluvial discharges are applied either at the closed boundaries or distributed as point sources within the relevant model domains. Wave computations are accomplished with the SWAN model using two grids for each Tier II sub-model: one larger grid covering the same area as the outer FLOW grid and a second finer resolution two-way coupled nearshore nested grid. The nearshore grid extends from approximately 800-1,000 m water depth up to 8-10 m elevations onshore. The landward extension is included to allow for wave computations of the higher SLR scenarios. Time- and space-varying 2D wave spectra extracted from previously completed Tier I simulations are applied approximately every kilometer along the open boundaries of the outer Tier II sub-model SWAN grids. The same space- and time-varying wind fields used in Tier I simulations are also applied to both Tier II SWAN grids to allow for computation of local wave generation. Tier III for the entire Southern California Bight consists of 4,802 cross-shore transects (CST) spaced approximately 100 m apart in the along-shore direction. The profiles extend from the -15 m isobath to at least 10 m above NAVD88. The CSTs are truncated for cases where a lagoon or other waterway exists on the landward end of the profile. Time-varying water levels and wave parameters (significant wave heights, Hs; peak periods, Tp; and peak incident wave directions, Dp), extracted from Tier II grid cells that coincide with the seaward end of the CSTs, are applied at the open boundary of each CST. The XBeach model is run in a hydrostatic (no vertical pressure gradients) mode including event-based morphodynamic change. Wave propagation, two-way wave-current interaction, water-level variations, and wave runup are computed at each transect. XBeach simulations are included in the CoSMoS model to account for infragravity waves that can significantly extend the reach of wave runup (Roelvink and others, 2009) compared to short-wave incident waves. The U.S. west coast is particularly susceptible to infragravity waves at the shore due to breaking of long-period swell waves (Tp > 15). Resulting water levels (WLs) from both Delft3D (high interest bays and marshes) and open-coast XBeach (CSTs) were spatially combined and interpolated to a 10 m grid. These WL elevations are differenced from the originating 2 m digital elevation model (DEM) to determine final flooding extent and depth of flooding. Events: The model system is run for pre-determined scenarios of interest such as the 1-yr or 100-yr storm event in combination with sea-level rise. Storms are first identified from time-series of total water level proxies (TWLpx) at the shore. TWLpx are computed for the majority of the 21st century (2010-2100), assuming a linear super-position of the major processes that contribute to the overall total water level. TWLpx time-series are then evaluated for extreme events, which define the boundary conditions for subsequent modeling with CoSMoS. Multiple 100-yr events are determined (varying Hs, Tp, Dp) and used for multiple model runs to better account for regional and directional flooding affects. Model results are combined and compiled into scenario-specific composites of flood projection. Digital Elevation Model (DEM): Our seamless, topobathymetric digital elevation model (DEM) was based largely upon the Coastal California TopoBathy Merge Project DEM, with some modifications performed by the USGS Earth Resources Observation and Science (EROS) Center to incorporate the most recent, high-resolution topographic and bathymetric datasets available. Topography is derived from bare-earth light detection and ranging (lidar) data collected in 2009-2011 for the CA Coastal Conservancy Lidar Project and bathymetry from 2009-2010 bathymetric lidar as well as acoustic multi- and single-beam data collected primarily between 2001 and 2013. The DEM was constructed to define the shape of nearshore, beach, and cliff surfaces as accurately as possible, utilizing dozens of bathymetric and topographic data sets. These data were used to populate the majority of the Tier I and II grids. To describe and include impacts from long-term shoreline evolution, including cumulative storm activity, seasonal trends, ENSO, and SLR, the DEM was modified for each SLR scenario. Long-term shoreline (Vitousek and Barnard, 2015) and cliff (Limber and others, 2015) erosion projections were efficiently combined along the cross-shore transects to evolve the shore-normal profiles. Elevation changes from the profiles were spatially-merged for a cohesive, 3D depiction of coastal evolution used to modify the DEM. These data are used to generate initial profiles of the 4,802 CSTs used for Phase 2 Tier III XBeach modeling and determining final projected flood depths in each SLR scenario. All data are referenced to NAD83 horizontal datum and NAVD88 vertical datum. Data for Tiers II and III are projected in UTM, zone 11. Outputs include: Projected wave height for the storm and sea-level rise scenario indicated. Data correspond to the near-shore region including areas vulnerable to coastal flooding due to storm surge, sea-level anomalies, tide elevation, and wave run-up during the same storm and sea-level rise simulation. References Cited: Howell, S., Smith-Konter, B., Frazer, N., Tong, X., and Sandwell, D., 2016, The vertical fingerprint of earthquake cycle loading in southern California: Nature Geoscience, v. 9, p. 611-614, doi:10.1038/ngeo2741. Limber, P., Barnard, P.L. and Hapke., C., 2015, Towards projecting the retreat of California’s coastal cliffs during the 21st Century: in, Wang, P., Rosati, J.D., and Cheng, J., (eds.), The Proceedings of the Coastal Sediments: 2015, World Scientific, 14 p., doi:10.1142/9789814689977_0245 Roelvink, J.A., Reniers, A., van Dongeren, A.R., van Thiel de Vries, J., McCall, R., and Lescinski, J., 2009, Modeling storm impacts on beaches, dunes and barrier islands: Coastal Engineering, v. 56, p. 1,133–1,152, doi:10.1016/j.coastaleng.2009.08.006. Tolman, H.L., Balasubramaniyan, B., Burroughs, L.D., Chalikov, D.V., Chao, Y.Y., Chen H.S., Gerald, V.M., 2002, Development and implementation of wind generated ocean surface wave models at NCEP: Weather and Forecasting, v. 17, p. 311-333. Vitousek, S. and Barnard, P.L., 2015, A non-linear, implicit one-line model to predict long-term shoreline change: in, Wang, P., Rosati, J.D., and Cheng, J., (eds.), The Proceedings of the Coastal Sediments: 2015, World Scientific, 14 p., doi:10.1142/9789814689977_0215.

Projected Hazard: Model-derived significant wave height (in meters) for the given storm condition and sea-level rise (SLR) scenario. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the model summary and inspect output carefully. Data are complete for the information presented. Details: Model background: The CoSMoS model comprises three tiers. Tier I consists of one Delft3D hydrodynamics FLOW grid for computation of tides, water level variations, flows, and currents and one SWAN grid for computation of wave generation and propagation across the continental shelf. The FLOW and SWAN models are two-way coupled so that tidal currents are accounted for in wave propagation and growth and conversely, so that orbital velocities generated by waves impart changes on tidal currents. The Tier I SWAN and FLOW models consist of identical structured curvilinear grids that extend from far offshore to the shore and range in resolution from 0.5 km in the offshore to 0.2 km in the nearshore. Spatially varying astronomic tidal amplitudes and phases and steric rises in water levels due to large-scale effects (for example, a prolonged rise in sea level) are applied along all open boundaries of the Tier I FLOW grid. Winds (split into eastward and northward components) and sea-level pressure (SLP) fields from CaRD10 (Dr. Dan Cayan, Scripps Institute of Oceanography, Los Angeles, California, written commun., 2014) that vary in both space and time are applied to all grid cells at each model time-step. Deep-water wave conditions, applied at the open boundaries of the Tier I SWAN model runs, were projected for the 21st century Representative Concentration Pathway (RCP) 4.5 climate scenario (2011-2100) using the WaveWatch III numerical wave model (Tolman and others, 2002) and 3-hourly winds from the GFDL-ESM2M Global Climate Model (GCM). Tier II provides higher resolution near the shore and in areas that require greater resolution of physical processes (such as bays, harbors, and estuaries). A single nested outer grid and multiple two-way coupled domain decomposition (DD) structured grids allow for local grid refinement and higher resolution where needed. Tier II was segmented into 11 sections along the Southern California Bight, to reduce computation time and complete runs within computational limitations. Water-level and Neumann time-series, extracted from Tier I simulations, are applied to the shore-parallel and lateral open boundaries of each Tier II sub-model outer grid respectively. Several of the sub-models proved to be unstable with lateral Neumann boundaries; for those cases one or both of the lateral boundaries were converted to water-level time-series or left unassigned. The open-boundary time-series are extracted from completed Tier I simulations so that there is no communication from Tier II to Tier I. Because this one-way nesting could produce erroneous results near the boundaries of Tier II and because data near any model boundary are always suspect, Tier II sub-model extents were designed to overlap in the along-coast direction. In the landward direction, Tier II DD grids extend to the 10-m topographic contour; exceptions exist where channels (such as the Los Angeles River) or other low-lying regions extend very far inland. Space- and time-varying wind and SLP fields, identical to those used in Tier I simulations, are applied to all Tier II DD grids to allow for wind-setup and local inverse barometer effects (IBE, rise or depression of water levels in response to atmospheric pressure gradients). A total of 42 time-series fluvial discharges are included in the Tier II FLOW domains in an effort to simulate exacerbated flooding caused by backflow at the confluence of high river seaward flows and elevated coastal surge levels migrating inland. Time-varying fluvial discharges are applied either at the closed boundaries or distributed as point sources within the relevant model domains. Wave computations are accomplished with the SWAN model using two grids for each Tier II sub-model: one larger grid covering the same area as the outer FLOW grid and a second finer resolution two-way coupled nearshore nested grid. The nearshore grid extends from approximately 800-1,000 m water depth up to 8-10 m elevations onshore. The landward extension is included to allow for wave computations of the higher SLR scenarios. Time- and space-varying 2D wave spectra extracted from previously completed Tier I simulations are applied approximately every kilometer along the open boundaries of the outer Tier II sub-model SWAN grids. The same space- and time-varying wind fields used in Tier I simulations are also applied to both Tier II SWAN grids to allow for computation of local wave generation. Tier III for the entire Southern California Bight consists of 4,802 cross-shore transects (CST) spaced approximately 100 m apart in the along-shore direction. The profiles extend from the -15 m isobath to at least 10 m above NAVD88. The CSTs are truncated for cases where a lagoon or other waterway exists on the landward end of the profile. Time-varying water levels and wave parameters (significant wave heights, Hs; peak periods, Tp; and peak incident wave directions, Dp), extracted from Tier II grid cells that coincide with the seaward end of the CSTs, are applied at the open boundary of each CST. The XBeach model is run in a hydrostatic (no vertical pressure gradients) mode including event-based morphodynamic change. Wave propagation, two-way wave-current interaction, water-level variations, and wave runup are computed at each transect. XBeach simulations are included in the CoSMoS model to account for infragravity waves that can significantly extend the reach of wave runup (Roelvink and others, 2009) compared to short-wave incident waves. The U.S. west coast is particularly susceptible to infragravity waves at the shore due to breaking of long-period swell waves (Tp > 15). Resulting water levels (WLs) from both Delft3D (high interest bays and marshes) and open-coast XBeach (CSTs) were spatially combined and interpolated to a 10 m grid. These WL elevations are differenced from the originating 2 m digital elevation model (DEM) to determine final flooding extent and depth of flooding. Events: The model system is run for pre-determined scenarios of interest such as the 1-yr or 100-yr storm event in combination with sea-level rise. Storms are first identified from time-series of total water level proxies (TWLpx) at the shore. TWLpx are computed for the majority of the 21st century (2010-2100), assuming a linear super-position of the major processes that contribute to the overall total water level. TWLpx time-series are then evaluated for extreme events, which define the boundary conditions for subsequent modeling with CoSMoS. Multiple 100-yr events are determined (varying Hs, Tp, Dp) and used for multiple model runs to better account for regional and directional flooding affects. Model results are combined and compiled into scenario-specific composites of flood projection. Digital Elevation Model (DEM): Our seamless, topobathymetric digital elevation model (DEM) was based largely upon the Coastal California TopoBathy Merge Project DEM, with some modifications performed by the USGS Earth Resources Observation and Science (EROS) Center to incorporate the most recent, high-resolution topographic and bathymetric datasets available. Topography is derived from bare-earth light detection and ranging (lidar) data collected in 2009-2011 for the CA Coastal Conservancy Lidar Project and bathymetry from 2009-2010 bathymetric lidar as well as acoustic multi- and single-beam data collected primarily between 2001 and 2013. The DEM was constructed to define the shape of nearshore, beach, and cliff surfaces as accurately as possible, utilizing dozens of bathymetric and topographic data sets. These data were used to populate the majority of the Tier I and II grids. To describe and include impacts from long-term shoreline evolution, including cumulative storm activity, seasonal trends, ENSO, and SLR, the DEM was modified for each SLR scenario. Long-term shoreline (Vitousek and Barnard, 2015) and cliff (Limber and others, 2015) erosion projections were efficiently combined along the cross-shore transects to evolve the shore-normal profiles. Elevation changes from the profiles were spatially-merged for a cohesive, 3D depiction of coastal evolution used to modify the DEM. These data are used to generate initial profiles of the 4,802 CSTs used for Phase 2 Tier III XBeach modeling and determining final projected flood depths in each SLR scenario. All data are referenced to NAD83 horizontal datum and NAVD88 vertical datum. Data for Tiers II and III are projected in UTM, zone 11. Outputs include: Projected wave height for the storm and sea-level rise scenario indicated. Data correspond to the near-shore region including areas vulnerable to coastal flooding due to storm surge, sea-level anomalies, tide elevation, and wave run-up during the same storm and sea-level rise simulation. References Cited: Howell, S., Smith-Konter, B., Frazer, N., Tong, X., and Sandwell, D., 2016, The vertical fingerprint of earthquake cycle loading in southern California: Nature Geoscience, v. 9, p. 611-614, doi:10.1038/ngeo2741. Limber, P., Barnard, P.L. and Hapke., C., 2015, Towards projecting the retreat of California’s coastal cliffs during the 21st Century: in, Wang, P., Rosati, J.D., and Cheng, J., (eds.), The Proceedings of the Coastal Sediments: 2015, World Scientific, 14 p., doi:10.1142/9789814689977_0245 Roelvink, J.A., Reniers, A., van Dongeren, A.R., van Thiel de Vries, J., McCall, R., and Lescinski, J., 2009, Modeling storm impacts on beaches, dunes and barrier islands: Coastal Engineering, v. 56, p. 1,133–1,152, doi:10.1016/j.coastaleng.2009.08.006. Tolman, H.L., Balasubramaniyan, B., Burroughs, L.D., Chalikov, D.V., Chao, Y.Y., Chen H.S., Gerald, V.M., 2002, Development and implementation of wind generated ocean surface wave models at NCEP: Weather and Forecasting, v. 17, p. 311-333. Vitousek, S. and Barnard, P.L., 2015, A non-linear, implicit one-line model to predict long-term shoreline change: in, Wang, P., Rosati, J.D., and Cheng, J., (eds.), The Proceedings of the Coastal Sediments: 2015, World Scientific, 14 p., doi:10.1142/9789814689977_0215.

Projected Hazard: Model-derived significant wave height (in meters) for the given storm condition and sea-level rise (SLR) scenario. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the model summary and inspect output carefully. Data are complete for the information presented. Details: Model background: The CoSMoS model comprises three tiers. Tier I consists of one Delft3D hydrodynamics FLOW grid for computation of tides, water level variations, flows, and currents and one SWAN grid for computation of wave generation and propagation across the continental shelf. The FLOW and SWAN models are two-way coupled so that tidal currents are accounted for in wave propagation and growth and conversely, so that orbital velocities generated by waves impart changes on tidal currents. The Tier I SWAN and FLOW models consist of identical structured curvilinear grids that extend from far offshore to the shore and range in resolution from 0.5 km in the offshore to 0.2 km in the nearshore. Spatially varying astronomic tidal amplitudes and phases and steric rises in water levels due to large-scale effects (for example, a prolonged rise in sea level) are applied along all open boundaries of the Tier I FLOW grid. Winds (split into eastward and northward components) and sea-level pressure (SLP) fields from CaRD10 (Dr. Dan Cayan, Scripps Institute of Oceanography, Los Angeles, California, written commun., 2014) that vary in both space and time are applied to all grid cells at each model time-step. Deep-water wave conditions, applied at the open boundaries of the Tier I SWAN model runs, were projected for the 21st century Representative Concentration Pathway (RCP) 4.5 climate scenario (2011-2100) using the WaveWatch III numerical wave model (Tolman and others, 2002) and 3-hourly winds from the GFDL-ESM2M Global Climate Model (GCM). Tier II provides higher resolution near the shore and in areas that require greater resolution of physical processes (such as bays, harbors, and estuaries). A single nested outer grid and multiple two-way coupled domain decomposition (DD) structured grids allow for local grid refinement and higher resolution where needed. Tier II was segmented into 11 sections along the Southern California Bight, to reduce computation time and complete runs within computational limitations. Water-level and Neumann time-series, extracted from Tier I simulations, are applied to the shore-parallel and lateral open boundaries of each Tier II sub-model outer grid respectively. Several of the sub-models proved to be unstable with lateral Neumann boundaries; for those cases one or both of the lateral boundaries were converted to water-level time-series or left unassigned. The open-boundary time-series are extracted from completed Tier I simulations so that there is no communication from Tier II to Tier I. Because this one-way nesting could produce erroneous results near the boundaries of Tier II and because data near any model boundary are always suspect, Tier II sub-model extents were designed to overlap in the along-coast direction. In the landward direction, Tier II DD grids extend to the 10-m topographic contour; exceptions exist where channels (such as the Los Angeles River) or other low-lying regions extend very far inland. Space- and time-varying wind and SLP fields, identical to those used in Tier I simulations, are applied to all Tier II DD grids to allow for wind-setup and local inverse barometer effects (IBE, rise or depression of water levels in response to atmospheric pressure gradients). A total of 42 time-series fluvial discharges are included in the Tier II FLOW domains in an effort to simulate exacerbated flooding caused by backflow at the confluence of high river seaward flows and elevated coastal surge levels migrating inland. Time-varying fluvial discharges are applied either at the closed boundaries or distributed as point sources within the relevant model domains. Wave computations are accomplished with the SWAN model using two grids for each Tier II sub-model: one larger grid covering the same area as the outer FLOW grid and a second finer resolution two-way coupled nearshore nested grid. The nearshore grid extends from approximately 800-1,000 m water depth up to 8-10 m elevations onshore. The landward extension is included to allow for wave computations of the higher SLR scenarios. Time- and space-varying 2D wave spectra extracted from previously completed Tier I simulations are applied approximately every kilometer along the open boundaries of the outer Tier II sub-model SWAN grids. The same space- and time-varying wind fields used in Tier I simulations are also applied to both Tier II SWAN grids to allow for computation of local wave generation. Tier III for the entire Southern California Bight consists of 4,802 cross-shore transects (CST) spaced approximately 100 m apart in the along-shore direction. The profiles extend from the -15 m isobath to at least 10 m above NAVD88. The CSTs are truncated for cases where a lagoon or other waterway exists on the landward end of the profile. Time-varying water levels and wave parameters (significant wave heights, Hs; peak periods, Tp; and peak incident wave directions, Dp), extracted from Tier II grid cells that coincide with the seaward end of the CSTs, are applied at the open boundary of each CST. The XBeach model is run in a hydrostatic (no vertical pressure gradients) mode including event-based morphodynamic change. Wave propagation, two-way wave-current interaction, water-level variations, and wave runup are computed at each transect. XBeach simulations are included in the CoSMoS model to account for infragravity waves that can significantly extend the reach of wave runup (Roelvink and others, 2009) compared to short-wave incident waves. The U.S. west coast is particularly susceptible to infragravity waves at the shore due to breaking of long-period swell waves (Tp > 15). Resulting water levels (WLs) from both Delft3D (high interest bays and marshes) and open-coast XBeach (CSTs) were spatially combined and interpolated to a 10 m grid. These WL elevations are differenced from the originating 2 m digital elevation model (DEM) to determine final flooding extent and depth of flooding. Events: The model system is run for pre-determined scenarios of interest such as the 1-yr or 100-yr storm event in combination with sea-level rise. Storms are first identified from time-series of total water level proxies (TWLpx) at the shore. TWLpx are computed for the majority of the 21st century (2010-2100), assuming a linear super-position of the major processes that contribute to the overall total water level. TWLpx time-series are then evaluated for extreme events, which define the boundary conditions for subsequent modeling with CoSMoS. Multiple 100-yr events are determined (varying Hs, Tp, Dp) and used for multiple model runs to better account for regional and directional flooding affects. Model results are combined and compiled into scenario-specific composites of flood projection. Digital Elevation Model (DEM): Our seamless, topobathymetric digital elevation model (DEM) was based largely upon the Coastal California TopoBathy Merge Project DEM, with some modifications performed by the USGS Earth Resources Observation and Science (EROS) Center to incorporate the most recent, high-resolution topographic and bathymetric datasets available. Topography is derived from bare-earth light detection and ranging (lidar) data collected in 2009-2011 for the CA Coastal Conservancy Lidar Project and bathymetry from 2009-2010 bathymetric lidar as well as acoustic multi- and single-beam data collected primarily between 2001 and 2013. The DEM was constructed to define the shape of nearshore, beach, and cliff surfaces as accurately as possible, utilizing dozens of bathymetric and topographic data sets. These data were used to populate the majority of the Tier I and II grids. To describe and include impacts from long-term shoreline evolution, including cumulative storm activity, seasonal trends, ENSO, and SLR, the DEM was modified for each SLR scenario. Long-term shoreline (Vitousek and Barnard, 2015) and cliff (Limber and others, 2015) erosion projections were efficiently combined along the cross-shore transects to evolve the shore-normal profiles. Elevation changes from the profiles were spatially-merged for a cohesive, 3D depiction of coastal evolution used to modify the DEM. These data are used to generate initial profiles of the 4,802 CSTs used for Phase 2 Tier III XBeach modeling and determining final projected flood depths in each SLR scenario. All data are referenced to NAD83 horizontal datum and NAVD88 vertical datum. Data for Tiers II and III are projected in UTM, zone 11. Outputs include: Projected wave height for the storm and sea-level rise scenario indicated. Data correspond to the near-shore region including areas vulnerable to coastal flooding due to storm surge, sea-level anomalies, tide elevation, and wave run-up during the same storm and sea-level rise simulation. References Cited: Howell, S., Smith-Konter, B., Frazer, N., Tong, X., and Sandwell, D., 2016, The vertical fingerprint of earthquake cycle loading in southern California: Nature Geoscience, v. 9, p. 611-614, doi:10.1038/ngeo2741. Limber, P., Barnard, P.L. and Hapke., C., 2015, Towards projecting the retreat of California’s coastal cliffs during the 21st Century: in, Wang, P., Rosati, J.D., and Cheng, J., (eds.), The Proceedings of the Coastal Sediments: 2015, World Scientific, 14 p., doi:10.1142/9789814689977_0245 Roelvink, J.A., Reniers, A., van Dongeren, A.R., van Thiel de Vries, J., McCall, R., and Lescinski, J., 2009, Modeling storm impacts on beaches, dunes and barrier islands: Coastal Engineering, v. 56, p. 1,133–1,152, doi:10.1016/j.coastaleng.2009.08.006. Tolman, H.L., Balasubramaniyan, B., Burroughs, L.D., Chalikov, D.V., Chao, Y.Y., Chen H.S., Gerald, V.M., 2002, Development and implementation of wind generated ocean surface wave models at NCEP: Weather and Forecasting, v. 17, p. 311-333. Vitousek, S. and Barnard, P.L., 2015, A non-linear, implicit one-line model to predict long-term shoreline change: in, Wang, P., Rosati, J.D., and Cheng, J., (eds.), The Proceedings of the Coastal Sediments: 2015, World Scientific, 14 p., doi:10.1142/9789814689977_0215.

Maximum depth of flooding surface (in cm) in the region landward of the present day shoreline that is inundated for the storm condition and sea-level rise (SLR) scenario indicated. Note: Duration datasets may have occasional gaps in open-coast sections. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Model details and data sources are outlined in CoSMoS_3.0_Phase_2_Southern_California_Bight:_Summary_of_data_and_methods (available at https://www.sciencebase.gov/catalog/file/get/57f1d4f3e4b0bc0bebfee139?name=CoSMoS_SoCalv3_Phase2_summary_of_methods.pdf). Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the Summary of methods and inspect output carefully. Data are complete for the information presented.

Maximum depth of flooding surface (in cm) in the region landward of the present day shoreline that is inundated for the storm condition and sea-level rise (SLR) scenario indicated. Note: Duration datasets may have occasional gaps in open-coast sections. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Model details and data sources are outlined in CoSMoS_3.0_Phase_2_Southern_California_Bight:_Summary_of_data_and_methods (available at https://www.sciencebase.gov/catalog/file/get/57f1d4f3e4b0bc0bebfee139?name=CoSMoS_SoCalv3_Phase2_summary_of_methods.pdf). Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the Summary of methods and inspect output carefully. Data are complete for the information presented.

Maximum depth of flooding surface (in cm) in the region landward of the present day shoreline that is inundated for the storm condition and sea-level rise (SLR) scenario indicated. Note: Duration datasets may have occasional gaps in open-coast sections. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Model details and data sources are outlined in CoSMoS_3.0_Phase_2_Southern_California_Bight:_Summary_of_data_and_methods (available at https://www.sciencebase.gov/catalog/file/get/57f1d4f3e4b0bc0bebfee139?name=CoSMoS_SoCalv3_Phase2_summary_of_methods.pdf). Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the Summary of methods and inspect output carefully. Data are complete for the information presented.

Maximum depth of flooding surface (in cm) in the region landward of the present day shoreline that is inundated for the storm condition and sea-level rise (SLR) scenario indicated. Note: Duration datasets may have occasional gaps in open-coast sections. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Model details and data sources are outlined in CoSMoS_3.0_Phase_2_Southern_California_Bight:_Summary_of_data_and_methods (available at https://www.sciencebase.gov/catalog/file/get/57f1d4f3e4b0bc0bebfee139?name=CoSMoS_SoCalv3_Phase2_summary_of_methods.pdf). Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the Summary of methods and inspect output carefully. Data are complete for the information presented.

Geographic extent of projected coastal flooding, low-lying vulnerable areas, and maxium/minimum flood potential (flood uncertainty) associated with the sea-level rise and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Model details and data sources are outlined in CoSMoS_3.0_Phase_2_Southern_California_Bight:_Summary_of_data_and_methods (available at https://www.sciencebase.gov/catalog/file/get/57f1d4f3e4b0bc0bebfee139?name=CoSMoS_SoCalv3_Phase2_summary_of_methods.pdf). Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the Summary of methods and inspect output carefully. Data are complete for the information presented.

Geographic extent of projected coastal flooding, low-lying vulnerable areas, and maxium/minimum flood potential (flood uncertainty) associated with the sea-level rise and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Model details and data sources are outlined in CoSMoS_3.0_Phase_2_Southern_California_Bight:_Summary_of_data_and_methods (available at https://www.sciencebase.gov/catalog/file/get/57f1d4f3e4b0bc0bebfee139?name=CoSMoS_SoCalv3_Phase2_summary_of_methods.pdf). Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the Summary of methods and inspect output carefully. Data are complete for the information presented.

Geographic extent of projected coastal flooding, low-lying vulnerable areas, and maxium/minimum flood potential (flood uncertainty) associated with the sea-level rise and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Model details and data sources are outlined in CoSMoS_3.0_Phase_2_Southern_California_Bight:_Summary_of_data_and_methods (available at https://www.sciencebase.gov/catalog/file/get/57f1d4f3e4b0bc0bebfee139?name=CoSMoS_SoCalv3_Phase2_summary_of_methods.pdf). Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the Summary of methods and inspect output carefully. Data are complete for the information presented.

Geographic extent of projected coastal flooding, low-lying vulnerable areas, and maxium/minimum flood potential (flood uncertainty) associated with the sea-level rise and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Model details and data sources are outlined in CoSMoS_3.0_Phase_2_Southern_California_Bight:_Summary_of_data_and_methods (available at https://www.sciencebase.gov/catalog/file/get/57f1d4f3e4b0bc0bebfee139?name=CoSMoS_SoCalv3_Phase2_summary_of_methods.pdf). Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the Summary of methods and inspect output carefully. Data are complete for the information presented.

Model-derived ocean current velocities (in meters per second) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Model details and data sources are outlined in CoSMoS_3.0_Phase_2_Southern_California_Bight:_Summary_of_data_and_methods (available at https://www.sciencebase.gov/catalog/file/get/57f1d4f3e4b0bc0bebfee139?name=CoSMoS_SoCalv3_Phase2_summary_of_methods.pdf). Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the Summary of methods and inspect output carefully. Data are complete for the information presented.

Model-derived ocean current velocities (in meters per second) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Model details and data sources are outlined in CoSMoS_3.0_Phase_2_Southern_California_Bight:_Summary_of_data_and_methods (available at https://www.sciencebase.gov/catalog/file/get/57f1d4f3e4b0bc0bebfee139?name=CoSMoS_SoCalv3_Phase2_summary_of_methods.pdf). Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the Summary of methods and inspect output carefully. Data are complete for the information presented.

Model-derived ocean current velocities (in meters per second) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Model details and data sources are outlined in CoSMoS_3.0_Phase_2_Southern_California_Bight:_Summary_of_data_and_methods (available at https://www.sciencebase.gov/catalog/file/get/57f1d4f3e4b0bc0bebfee139?name=CoSMoS_SoCalv3_Phase2_summary_of_methods.pdf). Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the Summary of methods and inspect output carefully. Data are complete for the information presented.

Model-derived ocean current velocities (in meters per second) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Model details and data sources are outlined in CoSMoS_3.0_Phase_2_Southern_California_Bight:_Summary_of_data_and_methods (available at https://www.sciencebase.gov/catalog/file/get/57f1d4f3e4b0bc0bebfee139?name=CoSMoS_SoCalv3_Phase2_summary_of_methods.pdf). Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the Summary of methods and inspect output carefully. Data are complete for the information presented.

Model-derived total water levels (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Model details and data sources are outlined in CoSMoS_3.0_Phase_2_Southern_California_Bight:_Summary_of_data_and_methods (available at https://www.sciencebase.gov/catalog/file/get/57f1d4f3e4b0bc0bebfee139?name=CoSMoS_SoCalv3_Phase2_summary_of_methods.pdf). Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the Summary of methods and inspect output carefully. Data are complete for the information presented.

Model-derived total water levels (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Model details and data sources are outlined in CoSMoS_3.0_Phase_2_Southern_California_Bight:_Summary_of_data_and_methods (available at https://www.sciencebase.gov/catalog/file/get/57f1d4f3e4b0bc0bebfee139?name=CoSMoS_SoCalv3_Phase2_summary_of_methods.pdf). Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the Summary of methods and inspect output carefully. Data are complete for the information presented.

Model-derived total water levels (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Model details and data sources are outlined in CoSMoS_3.0_Phase_2_Southern_California_Bight:_Summary_of_data_and_methods (available at https://www.sciencebase.gov/catalog/file/get/57f1d4f3e4b0bc0bebfee139?name=CoSMoS_SoCalv3_Phase2_summary_of_methods.pdf). Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the Summary of methods and inspect output carefully. Data are complete for the information presented.

Model-derived total water levels (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Model details and data sources are outlined in CoSMoS_3.0_Phase_2_Southern_California_Bight:_Summary_of_data_and_methods (available at https://www.sciencebase.gov/catalog/file/get/57f1d4f3e4b0bc0bebfee139?name=CoSMoS_SoCalv3_Phase2_summary_of_methods.pdf). Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the Summary of methods and inspect output carefully. Data are complete for the information presented.

Model-derived significant wave height (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Model details and data sources are outlined in CoSMoS_3.0_Phase_2_Southern_California_Bight:_Summary_of_data_and_methods (available at https://www.sciencebase.gov/catalog/file/get/57f1d4f3e4b0bc0bebfee139?name=CoSMoS_SoCalv3_Phase2_summary_of_methods.pdf). Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the Summary of methods and inspect output carefully. Data are complete for the information presented.

Model-derived significant wave height (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Model details and data sources are outlined in CoSMoS_3.0_Phase_2_Southern_California_Bight:_Summary_of_data_and_methods (available at https://www.sciencebase.gov/catalog/file/get/57f1d4f3e4b0bc0bebfee139?name=CoSMoS_SoCalv3_Phase2_summary_of_methods.pdf). Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the Summary of methods and inspect output carefully. Data are complete for the information presented.

Model-derived significant wave height (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Model details and data sources are outlined in CoSMoS_3.0_Phase_2_Southern_California_Bight:_Summary_of_data_and_methods (available at https://www.sciencebase.gov/catalog/file/get/57f1d4f3e4b0bc0bebfee139?name=CoSMoS_SoCalv3_Phase2_summary_of_methods.pdf). Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the Summary of methods and inspect output carefully. Data are complete for the information presented.

Model-derived significant wave height (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Model details and data sources are outlined in CoSMoS_3.0_Phase_2_Southern_California_Bight:_Summary_of_data_and_methods (available at https://www.sciencebase.gov/catalog/file/get/57f1d4f3e4b0bc0bebfee139?name=CoSMoS_SoCalv3_Phase2_summary_of_methods.pdf). Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the Summary of methods and inspect output carefully. Data are complete for the information presented.

Projected Hazard: Maximum depth of flooding surface (in cm) in the region landward of the present day shoreline that is inundated for the storm condition and sea-level rise (SLR) scenario indicated. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the model summary and inspect output carefully. Data are complete for the information presented. Details: Model background: The CoSMoS model comprises three tiers. Tier I consists of one Delft3D hydrodynamics FLOW grid for computation of tides, water level variations, flows, and currents and one SWAN grid for computation of wave generation and propagation across the continental shelf. The FLOW and SWAN models are two-way coupled so that tidal currents are accounted for in wave propagation and growth and conversely, so that orbital velocities generated by waves impart changes on tidal currents. The Tier I SWAN and FLOW models consist of identical structured curvilinear grids that extend from far offshore to the shore and range in resolution from 0.5 km in the offshore to 0.2 km in the nearshore. Spatially varying astronomic tidal amplitudes and phases and steric rises in water levels due to large-scale effects (for example, a prolonged rise in sea level) are applied along all open boundaries of the Tier I FLOW grid. Winds (split into eastward and northward components) and sea-level pressure (SLP) fields from CaRD10 (Dr. Dan Cayan, Scripps Institute of Oceanography, San Diego, California, written commun., 2014) that vary in both space and time are applied to all grid cells at each model time-step. Deep-water wave conditions, applied at the open boundaries of the Tier I SWAN model runs, were projected for the 21st century Representative Concentration Pathway (RCP) 4.5 climate scenario (2011-2100) using the WaveWatch III numerical wave model (Tolman and others, 2002) and 3-hourly winds from the GFDL-ESM2M Global Climate Model (GCM). Tier II provides higher resolution near the shore and in areas that require greater resolution of physical processes (such as bays, harbors, and estuaries). A single nested outer grid and multiple two-way coupled domain decomposition (DD) structured grids allow for local grid refinement and higher resolution where needed. Tier II was segmented into 11 sections along the Southern California Bight, to reduce computation time and complete runs within computational limitations. Water-level and Neumann time-series, extracted from Tier I simulations, are applied to the shore-parallel and lateral open boundaries of each Tier II sub-model outer grid respectively. Several of the sub-models proved to be unstable with lateral Neumann boundaries; for those cases one or both of the lateral boundaries were converted to water-level time-series or left unassigned. The open-boundary time-series are extracted from completed Tier I simulations so that there is no communication from Tier II to Tier I. Because this one-way nesting could produce erroneous results near the boundaries of Tier II and because data near any model boundary are always suspect, Tier II sub-model extents were designed to overlap in the along-coast direction. In the landward direction, Tier II DD grids extend to the 10-m topographic contour; exceptions exist where channels (such as the Los Angeles River) or other low-lying regions extend very far inland. Space- and time-varying wind and SLP fields, identical to those used in Tier I simulations, are applied to all Tier II DD grids to allow for wind-setup and local inverse barometer effects (IBE, rise or depression of water levels in response to atmospheric pressure gradients). A total of 42 time-series fluvial discharges are included in the Tier II FLOW domains in an effort to simulate exacerbated flooding caused by backflow at the confluence of high river seaward flows and elevated coastal surge levels migrating inland. Time-varying fluvial discharges are applied either at the closed boundaries or distributed as point sources within the relevant model domains. Wave computations are accomplished with the SWAN model using two grids for each Tier II sub-model: one larger grid covering the same area as the outer FLOW grid and a second finer resolution two-way coupled nearshore nested grid. The nearshore grid extends from approximately 800-1,000 m water depth up to 8-10 m elevations onshore. The landward extension is included to allow for wave computations of the higher SLR scenarios. Time- and space-varying 2D wave spectra extracted from previously completed Tier I simulations are applied approximately every kilometer along the open boundaries of the outer Tier II sub-model SWAN grids. The same space- and time-varying wind fields used in Tier I simulations are also applied to both Tier II SWAN grids to allow for computation of local wave generation. Tier III for the entire Southern California Bight consists of 4,802 cross-shore transects (CST) spaced approximately 100 m apart in the along-shore direction. The profiles extend from the -15 m isobath to at least 10 m above NAVD88. The CSTs are truncated for cases where a lagoon or other waterway exists on the landward end of the profile. Time-varying water levels and wave parameters (significant wave heights, Hs; peak periods, Tp; and peak incident wave directions, Dp), extracted from Tier II grid cells that coincide with the seaward end of the CSTs, are applied at the open boundary of each CST. The XBeach model is run in a hydrostatic (no vertical pressure gradients) mode including event-based morphodynamic change. Wave propagation, two-way wave-current interaction, water-level variations, and wave runup are computed at each transect. XBeach simulations are included in the CoSMoS model to account for infragravity waves that can significantly extend the reach of wave runup (Roelvink and others, 2009) compared to short-wave incident waves. The U.S. west coast is particularly susceptible to infragravity waves at the shore due to breaking of long-period swell waves (Tp > 15). Resulting water levels (WLs) from both Delft3D (high interest bays and marshes) and open-coast XBeach (CSTs) were spatially combined and interpolated to a 10 m grid. These WL elevations are differenced from the originating 2 m digital elevation model (DEM) to determine final flooding extent and depth of flooding. Events: The model system is run for pre-determined scenarios of interest such as the 1-yr or 100-yr storm event in combination with sea-level rise. Storms are first identified from time-series of total water level proxies (TWLpx) at the shore. TWLpx are computed for the majority of the 21st century (2010-2100), assuming a linear super-position of the major processes that contribute to the overall total water level. TWLpx time-series are then evaluated for extreme events, which define the boundary conditions for subsequent modeling with CoSMoS. Multiple 100-yr events are determined (varying Hs, Tp, Dp) and used for multiple model runs to better account for regional and directional flooding affects. Model results are combined and compiled into scenario-specific composites of flood projection. Digital Elevation Model (DEM): Our seamless, topobathymetric digital elevation model (DEM) was based largely upon the Coastal California TopoBathy Merge Project DEM, with some modifications performed by the USGS Earth Resources Observation and Science (EROS) Center to incorporate the most recent, high-resolution topographic and bathymetric datasets available. Topography is derived from bare-earth light detection and ranging (lidar) data collected in 2009-2011 for the CA Coastal Conservancy Lidar Project and bathymetry from 2009-2010 bathymetric lidar as well as acoustic multi- and single-beam data collected primarily between 2001 and 2013. The DEM was constructed to define the shape of nearshore, beach, and cliff surfaces as accurately as possible, utilizing dozens of bathymetric and topographic data sets. These data were used to populate the majority of the Tier I and II grids. To describe and include impacts from long-term shoreline evolution, including cumulative storm activity, seasonal trends, ENSO, and SLR, the DEM was modified for each SLR scenario. Long-term shoreline (Vitousek and Barnard, 2015) and cliff (Limber and others, 2015) erosion projections were efficiently combined along the cross-shore transects to evolve the shore-normal profiles. Elevation changes from the profiles were spatially-merged for a cohesive, 3D depiction of coastal evolution used to modify the DEM. These data are used to generate initial profiles of the 4,802 CSTs used for Phase 2 Tier III XBeach modeling and determining final projected flood depths in each SLR scenario. All data are referenced to NAD83 horizontal datum and NAVD88 vertical datum. Data for Tiers II and III are projected in UTM, zone 11. Outputs include: Projected flood-hazard depth and duration for the storm and sea-level rise indicated. Data correspond to the areas vulnerable to coastal flooding due to storm surge, sea-level anomalies, tide elevation, and wave run-up during the same storm and sea-level rise simulation. References Cited: Howell, S., Smith-Konter, B., Frazer, N., Tong, X., and Sandwell, D., 2016, The vertical fingerprint of earthquake cycle loading in southern California: Nature Geoscience, v. 9, p. 611-614, doi:10.1038/ngeo2741. Limber, P., Barnard, P.L. and Hapke., C., 2015, Towards projecting the retreat of California’s coastal cliffs during the 21st Century: in, Wang, P., Rosati, J.D., and Cheng, J., (eds.), The Proceedings of the Coastal Sediments: 2015, World Scientific, 14 p., doi:10.1142/9789814689977_0245 Roelvink, J.A., Reniers, A., van Dongeren, A.R., van Thiel de Vries, J., McCall, R., and Lescinski, J., 2009, Modeling storm impacts on beaches, dunes and barrier islands: Coastal Engineering, v. 56, p. 1,133–1,152, doi:10.1016/j.coastaleng.2009.08.006. Tolman, H.L., Balasubramaniyan, B., Burroughs, L.D., Chalikov, D.V., Chao, Y.Y., Chen H.S., Gerald, V.M., 2002, Development and implementation of wind generated ocean surface wave models at NCEP: Weather and Forecasting, v. 17, p. 311-333. Vitousek, S. and Barnard, P.L., 2015, A non-linear, implicit one-line model to predict long-term shoreline change: in, Wang, P., Rosati, J.D., and Cheng, J., (eds.), The Proceedings of the Coastal Sediments: 2015, World Scientific, 14 p., doi:10.1142/9789814689977_0215.

Projected Hazard: Maximum depth of flooding surface (in cm) in the region landward of the present day shoreline that is inundated for the storm condition and sea-level rise (SLR) scenario indicated. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the model summary and inspect output carefully. Data are complete for the information presented. Details: Model background: The CoSMoS model comprises three tiers. Tier I consists of one Delft3D hydrodynamics FLOW grid for computation of tides, water level variations, flows, and currents and one SWAN grid for computation of wave generation and propagation across the continental shelf. The FLOW and SWAN models are two-way coupled so that tidal currents are accounted for in wave propagation and growth and conversely, so that orbital velocities generated by waves impart changes on tidal currents. The Tier I SWAN and FLOW models consist of identical structured curvilinear grids that extend from far offshore to the shore and range in resolution from 0.5 km in the offshore to 0.2 km in the nearshore. Spatially varying astronomic tidal amplitudes and phases and steric rises in water levels due to large-scale effects (for example, a prolonged rise in sea level) are applied along all open boundaries of the Tier I FLOW grid. Winds (split into eastward and northward components) and sea-level pressure (SLP) fields from CaRD10 (Dr. Dan Cayan, Scripps Institute of Oceanography, San Diego, California, written commun., 2014) that vary in both space and time are applied to all grid cells at each model time-step. Deep-water wave conditions, applied at the open boundaries of the Tier I SWAN model runs, were projected for the 21st century Representative Concentration Pathway (RCP) 4.5 climate scenario (2011-2100) using the WaveWatch III numerical wave model (Tolman and others, 2002) and 3-hourly winds from the GFDL-ESM2M Global Climate Model (GCM). Tier II provides higher resolution near the shore and in areas that require greater resolution of physical processes (such as bays, harbors, and estuaries). A single nested outer grid and multiple two-way coupled domain decomposition (DD) structured grids allow for local grid refinement and higher resolution where needed. Tier II was segmented into 11 sections along the Southern California Bight, to reduce computation time and complete runs within computational limitations. Water-level and Neumann time-series, extracted from Tier I simulations, are applied to the shore-parallel and lateral open boundaries of each Tier II sub-model outer grid respectively. Several of the sub-models proved to be unstable with lateral Neumann boundaries; for those cases one or both of the lateral boundaries were converted to water-level time-series or left unassigned. The open-boundary time-series are extracted from completed Tier I simulations so that there is no communication from Tier II to Tier I. Because this one-way nesting could produce erroneous results near the boundaries of Tier II and because data near any model boundary are always suspect, Tier II sub-model extents were designed to overlap in the along-coast direction. In the landward direction, Tier II DD grids extend to the 10-m topographic contour; exceptions exist where channels (such as the Los Angeles River) or other low-lying regions extend very far inland. Space- and time-varying wind and SLP fields, identical to those used in Tier I simulations, are applied to all Tier II DD grids to allow for wind-setup and local inverse barometer effects (IBE, rise or depression of water levels in response to atmospheric pressure gradients). A total of 42 time-series fluvial discharges are included in the Tier II FLOW domains in an effort to simulate exacerbated flooding caused by backflow at the confluence of high river seaward flows and elevated coastal surge levels migrating inland. Time-varying fluvial discharges are applied either at the closed boundaries or distributed as point sources within the relevant model domains. Wave computations are accomplished with the SWAN model using two grids for each Tier II sub-model: one larger grid covering the same area as the outer FLOW grid and a second finer resolution two-way coupled nearshore nested grid. The nearshore grid extends from approximately 800-1,000 m water depth up to 8-10 m elevations onshore. The landward extension is included to allow for wave computations of the higher SLR scenarios. Time- and space-varying 2D wave spectra extracted from previously completed Tier I simulations are applied approximately every kilometer along the open boundaries of the outer Tier II sub-model SWAN grids. The same space- and time-varying wind fields used in Tier I simulations are also applied to both Tier II SWAN grids to allow for computation of local wave generation. Tier III for the entire Southern California Bight consists of 4,802 cross-shore transects (CST) spaced approximately 100 m apart in the along-shore direction. The profiles extend from the -15 m isobath to at least 10 m above NAVD88. The CSTs are truncated for cases where a lagoon or other waterway exists on the landward end of the profile. Time-varying water levels and wave parameters (significant wave heights, Hs; peak periods, Tp; and peak incident wave directions, Dp), extracted from Tier II grid cells that coincide with the seaward end of the CSTs, are applied at the open boundary of each CST. The XBeach model is run in a hydrostatic (no vertical pressure gradients) mode including event-based morphodynamic change. Wave propagation, two-way wave-current interaction, water-level variations, and wave runup are computed at each transect. XBeach simulations are included in the CoSMoS model to account for infragravity waves that can significantly extend the reach of wave runup (Roelvink and others, 2009) compared to short-wave incident waves. The U.S. west coast is particularly susceptible to infragravity waves at the shore due to breaking of long-period swell waves (Tp > 15). Resulting water levels (WLs) from both Delft3D (high interest bays and marshes) and open-coast XBeach (CSTs) were spatially combined and interpolated to a 10 m grid. These WL elevations are differenced from the originating 2 m digital elevation model (DEM) to determine final flooding extent and depth of flooding. Events: The model system is run for pre-determined scenarios of interest such as the 1-yr or 100-yr storm event in combination with sea-level rise. Storms are first identified from time-series of total water level proxies (TWLpx) at the shore. TWLpx are computed for the majority of the 21st century (2010-2100), assuming a linear super-position of the major processes that contribute to the overall total water level. TWLpx time-series are then evaluated for extreme events, which define the boundary conditions for subsequent modeling with CoSMoS. Multiple 100-yr events are determined (varying Hs, Tp, Dp) and used for multiple model runs to better account for regional and directional flooding affects. Model results are combined and compiled into scenario-specific composites of flood projection. Digital Elevation Model (DEM): Our seamless, topobathymetric digital elevation model (DEM) was based largely upon the Coastal California TopoBathy Merge Project DEM, with some modifications performed by the USGS Earth Resources Observation and Science (EROS) Center to incorporate the most recent, high-resolution topographic and bathymetric datasets available. Topography is derived from bare-earth light detection and ranging (lidar) data collected in 2009-2011 for the CA Coastal Conservancy Lidar Project and bathymetry from 2009-2010 bathymetric lidar as well as acoustic multi- and single-beam data collected primarily between 2001 and 2013. The DEM was constructed to define the shape of nearshore, beach, and cliff surfaces as accurately as possible, utilizing dozens of bathymetric and topographic data sets. These data were used to populate the majority of the Tier I and II grids. To describe and include impacts from long-term shoreline evolution, including cumulative storm activity, seasonal trends, ENSO, and SLR, the DEM was modified for each SLR scenario. Long-term shoreline (Vitousek and Barnard, 2015) and cliff (Limber and others, 2015) erosion projections were efficiently combined along the cross-shore transects to evolve the shore-normal profiles. Elevation changes from the profiles were spatially-merged for a cohesive, 3D depiction of coastal evolution used to modify the DEM. These data are used to generate initial profiles of the 4,802 CSTs used for Phase 2 Tier III XBeach modeling and determining final projected flood depths in each SLR scenario. All data are referenced to NAD83 horizontal datum and NAVD88 vertical datum. Data for Tiers II and III are projected in UTM, zone 11. Outputs include: Projected flood-hazard depth and duration for the storm and sea-level rise indicated. Data correspond to the areas vulnerable to coastal flooding due to storm surge, sea-level anomalies, tide elevation, and wave run-up during the same storm and sea-level rise simulation. References Cited: Howell, S., Smith-Konter, B., Frazer, N., Tong, X., and Sandwell, D., 2016, The vertical fingerprint of earthquake cycle loading in southern California: Nature Geoscience, v. 9, p. 611-614, doi:10.1038/ngeo2741. Limber, P., Barnard, P.L. and Hapke., C., 2015, Towards projecting the retreat of California’s coastal cliffs during the 21st Century: in, Wang, P., Rosati, J.D., and Cheng, J., (eds.), The Proceedings of the Coastal Sediments: 2015, World Scientific, 14 p., doi:10.1142/9789814689977_0245 Roelvink, J.A., Reniers, A., van Dongeren, A.R., van Thiel de Vries, J., McCall, R., and Lescinski, J., 2009, Modeling storm impacts on beaches, dunes and barrier islands: Coastal Engineering, v. 56, p. 1,133–1,152, doi:10.1016/j.coastaleng.2009.08.006. Tolman, H.L., Balasubramaniyan, B., Burroughs, L.D., Chalikov, D.V., Chao, Y.Y., Chen H.S., Gerald, V.M., 2002, Development and implementation of wind generated ocean surface wave models at NCEP: Weather and Forecasting, v. 17, p. 311-333. Vitousek, S. and Barnard, P.L., 2015, A non-linear, implicit one-line model to predict long-term shoreline change: in, Wang, P., Rosati, J.D., and Cheng, J., (eds.), The Proceedings of the Coastal Sediments: 2015, World Scientific, 14 p., doi:10.1142/9789814689977_0215.

Projected Hazard: Maximum depth of flooding surface (in cm) in the region landward of the present day shoreline that is inundated for the storm condition and sea-level rise (SLR) scenario indicated. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the model summary and inspect output carefully. Data are complete for the information presented. Details: Model background: The CoSMoS model comprises three tiers. Tier I consists of one Delft3D hydrodynamics FLOW grid for computation of tides, water level variations, flows, and currents and one SWAN grid for computation of wave generation and propagation across the continental shelf. The FLOW and SWAN models are two-way coupled so that tidal currents are accounted for in wave propagation and growth and conversely, so that orbital velocities generated by waves impart changes on tidal currents. The Tier I SWAN and FLOW models consist of identical structured curvilinear grids that extend from far offshore to the shore and range in resolution from 0.5 km in the offshore to 0.2 km in the nearshore. Spatially varying astronomic tidal amplitudes and phases and steric rises in water levels due to large-scale effects (for example, a prolonged rise in sea level) are applied along all open boundaries of the Tier I FLOW grid. Winds (split into eastward and northward components) and sea-level pressure (SLP) fields from CaRD10 (Dr. Dan Cayan, Scripps Institute of Oceanography, San Diego, California, written commun., 2014) that vary in both space and time are applied to all grid cells at each model time-step. Deep-water wave conditions, applied at the open boundaries of the Tier I SWAN model runs, were projected for the 21st century Representative Concentration Pathway (RCP) 4.5 climate scenario (2011-2100) using the WaveWatch III numerical wave model (Tolman and others, 2002) and 3-hourly winds from the GFDL-ESM2M Global Climate Model (GCM). Tier II provides higher resolution near the shore and in areas that require greater resolution of physical processes (such as bays, harbors, and estuaries). A single nested outer grid and multiple two-way coupled domain decomposition (DD) structured grids allow for local grid refinement and higher resolution where needed. Tier II was segmented into 11 sections along the Southern California Bight, to reduce computation time and complete runs within computational limitations. Water-level and Neumann time-series, extracted from Tier I simulations, are applied to the shore-parallel and lateral open boundaries of each Tier II sub-model outer grid respectively. Several of the sub-models proved to be unstable with lateral Neumann boundaries; for those cases one or both of the lateral boundaries were converted to water-level time-series or left unassigned. The open-boundary time-series are extracted from completed Tier I simulations so that there is no communication from Tier II to Tier I. Because this one-way nesting could produce erroneous results near the boundaries of Tier II and because data near any model boundary are always suspect, Tier II sub-model extents were designed to overlap in the along-coast direction. In the landward direction, Tier II DD grids extend to the 10-m topographic contour; exceptions exist where channels (such as the Los Angeles River) or other low-lying regions extend very far inland. Space- and time-varying wind and SLP fields, identical to those used in Tier I simulations, are applied to all Tier II DD grids to allow for wind-setup and local inverse barometer effects (IBE, rise or depression of water levels in response to atmospheric pressure gradients). A total of 42 time-series fluvial discharges are included in the Tier II FLOW domains in an effort to simulate exacerbated flooding caused by backflow at the confluence of high river seaward flows and elevated coastal surge levels migrating inland. Time-varying fluvial discharges are applied either at the closed boundaries or distributed as point sources within the relevant model domains. Wave computations are accomplished with the SWAN model using two grids for each Tier II sub-model: one larger grid covering the same area as the outer FLOW grid and a second finer resolution two-way coupled nearshore nested grid. The nearshore grid extends from approximately 800-1,000 m water depth up to 8-10 m elevations onshore. The landward extension is included to allow for wave computations of the higher SLR scenarios. Time- and space-varying 2D wave spectra extracted from previously completed Tier I simulations are applied approximately every kilometer along the open boundaries of the outer Tier II sub-model SWAN grids. The same space- and time-varying wind fields used in Tier I simulations are also applied to both Tier II SWAN grids to allow for computation of local wave generation. Tier III for the entire Southern California Bight consists of 4,802 cross-shore transects (CST) spaced approximately 100 m apart in the along-shore direction. The profiles extend from the -15 m isobath to at least 10 m above NAVD88. The CSTs are truncated for cases where a lagoon or other waterway exists on the landward end of the profile. Time-varying water levels and wave parameters (significant wave heights, Hs; peak periods, Tp; and peak incident wave directions, Dp), extracted from Tier II grid cells that coincide with the seaward end of the CSTs, are applied at the open boundary of each CST. The XBeach model is run in a hydrostatic (no vertical pressure gradients) mode including event-based morphodynamic change. Wave propagation, two-way wave-current interaction, water-level variations, and wave runup are computed at each transect. XBeach simulations are included in the CoSMoS model to account for infragravity waves that can significantly extend the reach of wave runup (Roelvink and others, 2009) compared to short-wave incident waves. The U.S. west coast is particularly susceptible to infragravity waves at the shore due to breaking of long-period swell waves (Tp > 15). Resulting water levels (WLs) from both Delft3D (high interest bays and marshes) and open-coast XBeach (CSTs) were spatially combined and interpolated to a 10 m grid. These WL elevations are differenced from the originating 2 m digital elevation model (DEM) to determine final flooding extent and depth of flooding. Events: The model system is run for pre-determined scenarios of interest such as the 1-yr or 100-yr storm event in combination with sea-level rise. Storms are first identified from time-series of total water level proxies (TWLpx) at the shore. TWLpx are computed for the majority of the 21st century (2010-2100), assuming a linear super-position of the major processes that contribute to the overall total water level. TWLpx time-series are then evaluated for extreme events, which define the boundary conditions for subsequent modeling with CoSMoS. Multiple 100-yr events are determined (varying Hs, Tp, Dp) and used for multiple model runs to better account for regional and directional flooding affects. Model results are combined and compiled into scenario-specific composites of flood projection. Digital Elevation Model (DEM): Our seamless, topobathymetric digital elevation model (DEM) was based largely upon the Coastal California TopoBathy Merge Project DEM, with some modifications performed by the USGS Earth Resources Observation and Science (EROS) Center to incorporate the most recent, high-resolution topographic and bathymetric datasets available. Topography is derived from bare-earth light detection and ranging (lidar) data collected in 2009-2011 for the CA Coastal Conservancy Lidar Project and bathymetry from 2009-2010 bathymetric lidar as well as acoustic multi- and single-beam data collected primarily between 2001 and 2013. The DEM was constructed to define the shape of nearshore, beach, and cliff surfaces as accurately as possible, utilizing dozens of bathymetric and topographic data sets. These data were used to populate the majority of the Tier I and II grids. To describe and include impacts from long-term shoreline evolution, including cumulative storm activity, seasonal trends, ENSO, and SLR, the DEM was modified for each SLR scenario. Long-term shoreline (Vitousek and Barnard, 2015) and cliff (Limber and others, 2015) erosion projections were efficiently combined along the cross-shore transects to evolve the shore-normal profiles. Elevation changes from the profiles were spatially-merged for a cohesive, 3D depiction of coastal evolution used to modify the DEM. These data are used to generate initial profiles of the 4,802 CSTs used for Phase 2 Tier III XBeach modeling and determining final projected flood depths in each SLR scenario. All data are referenced to NAD83 horizontal datum and NAVD88 vertical datum. Data for Tiers II and III are projected in UTM, zone 11. Outputs include: Projected flood-hazard depth and duration for the storm and sea-level rise indicated. Data correspond to the areas vulnerable to coastal flooding due to storm surge, sea-level anomalies, tide elevation, and wave run-up during the same storm and sea-level rise simulation. References Cited: Howell, S., Smith-Konter, B., Frazer, N., Tong, X., and Sandwell, D., 2016, The vertical fingerprint of earthquake cycle loading in southern California: Nature Geoscience, v. 9, p. 611-614, doi:10.1038/ngeo2741. Limber, P., Barnard, P.L. and Hapke., C., 2015, Towards projecting the retreat of California’s coastal cliffs during the 21st Century: in, Wang, P., Rosati, J.D., and Cheng, J., (eds.), The Proceedings of the Coastal Sediments: 2015, World Scientific, 14 p., doi:10.1142/9789814689977_0245 Roelvink, J.A., Reniers, A., van Dongeren, A.R., van Thiel de Vries, J., McCall, R., and Lescinski, J., 2009, Modeling storm impacts on beaches, dunes and barrier islands: Coastal Engineering, v. 56, p. 1,133–1,152, doi:10.1016/j.coastaleng.2009.08.006. Tolman, H.L., Balasubramaniyan, B., Burroughs, L.D., Chalikov, D.V., Chao, Y.Y., Chen H.S., Gerald, V.M., 2002, Development and implementation of wind generated ocean surface wave models at NCEP: Weather and Forecasting, v. 17, p. 311-333. Vitousek, S. and Barnard, P.L., 2015, A non-linear, implicit one-line model to predict long-term shoreline change: in, Wang, P., Rosati, J.D., and Cheng, J., (eds.), The Proceedings of the Coastal Sediments: 2015, World Scientific, 14 p., doi:10.1142/9789814689977_0215.

Projected Hazard: Maximum depth of flooding surface (in cm) in the region landward of the present day shoreline that is inundated for the storm condition and sea-level rise (SLR) scenario indicated. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the model summary and inspect output carefully. Data are complete for the information presented. Details: Model background: The CoSMoS model comprises three tiers. Tier I consists of one Delft3D hydrodynamics FLOW grid for computation of tides, water level variations, flows, and currents and one SWAN grid for computation of wave generation and propagation across the continental shelf. The FLOW and SWAN models are two-way coupled so that tidal currents are accounted for in wave propagation and growth and conversely, so that orbital velocities generated by waves impart changes on tidal currents. The Tier I SWAN and FLOW models consist of identical structured curvilinear grids that extend from far offshore to the shore and range in resolution from 0.5 km in the offshore to 0.2 km in the nearshore. Spatially varying astronomic tidal amplitudes and phases and steric rises in water levels due to large-scale effects (for example, a prolonged rise in sea level) are applied along all open boundaries of the Tier I FLOW grid. Winds (split into eastward and northward components) and sea-level pressure (SLP) fields from CaRD10 (Dr. Dan Cayan, Scripps Institute of Oceanography, San Diego, California, written commun., 2014) that vary in both space and time are applied to all grid cells at each model time-step. Deep-water wave conditions, applied at the open boundaries of the Tier I SWAN model runs, were projected for the 21st century Representative Concentration Pathway (RCP) 4.5 climate scenario (2011-2100) using the WaveWatch III numerical wave model (Tolman and others, 2002) and 3-hourly winds from the GFDL-ESM2M Global Climate Model (GCM). Tier II provides higher resolution near the shore and in areas that require greater resolution of physical processes (such as bays, harbors, and estuaries). A single nested outer grid and multiple two-way coupled domain decomposition (DD) structured grids allow for local grid refinement and higher resolution where needed. Tier II was segmented into 11 sections along the Southern California Bight, to reduce computation time and complete runs within computational limitations. Water-level and Neumann time-series, extracted from Tier I simulations, are applied to the shore-parallel and lateral open boundaries of each Tier II sub-model outer grid respectively. Several of the sub-models proved to be unstable with lateral Neumann boundaries; for those cases one or both of the lateral boundaries were converted to water-level time-series or left unassigned. The open-boundary time-series are extracted from completed Tier I simulations so that there is no communication from Tier II to Tier I. Because this one-way nesting could produce erroneous results near the boundaries of Tier II and because data near any model boundary are always suspect, Tier II sub-model extents were designed to overlap in the along-coast direction. In the landward direction, Tier II DD grids extend to the 10-m topographic contour; exceptions exist where channels (such as the Los Angeles River) or other low-lying regions extend very far inland. Space- and time-varying wind and SLP fields, identical to those used in Tier I simulations, are applied to all Tier II DD grids to allow for wind-setup and local inverse barometer effects (IBE, rise or depression of water levels in response to atmospheric pressure gradients). A total of 42 time-series fluvial discharges are included in the Tier II FLOW domains in an effort to simulate exacerbated flooding caused by backflow at the confluence of high river seaward flows and elevated coastal surge levels migrating inland. Time-varying fluvial discharges are applied either at the closed boundaries or distributed as point sources within the relevant model domains. Wave computations are accomplished with the SWAN model using two grids for each Tier II sub-model: one larger grid covering the same area as the outer FLOW grid and a second finer resolution two-way coupled nearshore nested grid. The nearshore grid extends from approximately 800-1,000 m water depth up to 8-10 m elevations onshore. The landward extension is included to allow for wave computations of the higher SLR scenarios. Time- and space-varying 2D wave spectra extracted from previously completed Tier I simulations are applied approximately every kilometer along the open boundaries of the outer Tier II sub-model SWAN grids. The same space- and time-varying wind fields used in Tier I simulations are also applied to both Tier II SWAN grids to allow for computation of local wave generation. Tier III for the entire Southern California Bight consists of 4,802 cross-shore transects (CST) spaced approximately 100 m apart in the along-shore direction. The profiles extend from the -15 m isobath to at least 10 m above NAVD88. The CSTs are truncated for cases where a lagoon or other waterway exists on the landward end of the profile. Time-varying water levels and wave parameters (significant wave heights, Hs; peak periods, Tp; and peak incident wave directions, Dp), extracted from Tier II grid cells that coincide with the seaward end of the CSTs, are applied at the open boundary of each CST. The XBeach model is run in a hydrostatic (no vertical pressure gradients) mode including event-based morphodynamic change. Wave propagation, two-way wave-current interaction, water-level variations, and wave runup are computed at each transect. XBeach simulations are included in the CoSMoS model to account for infragravity waves that can significantly extend the reach of wave runup (Roelvink and others, 2009) compared to short-wave incident waves. The U.S. west coast is particularly susceptible to infragravity waves at the shore due to breaking of long-period swell waves (Tp > 15). Resulting water levels (WLs) from both Delft3D (high interest bays and marshes) and open-coast XBeach (CSTs) were spatially combined and interpolated to a 10 m grid. These WL elevations are differenced from the originating 2 m digital elevation model (DEM) to determine final flooding extent and depth of flooding. Events: The model system is run for pre-determined scenarios of interest such as the 1-yr or 100-yr storm event in combination with sea-level rise. Storms are first identified from time-series of total water level proxies (TWLpx) at the shore. TWLpx are computed for the majority of the 21st century (2010-2100), assuming a linear super-position of the major processes that contribute to the overall total water level. TWLpx time-series are then evaluated for extreme events, which define the boundary conditions for subsequent modeling with CoSMoS. Multiple 100-yr events are determined (varying Hs, Tp, Dp) and used for multiple model runs to better account for regional and directional flooding affects. Model results are combined and compiled into scenario-specific composites of flood projection. Digital Elevation Model (DEM): Our seamless, topobathymetric digital elevation model (DEM) was based largely upon the Coastal California TopoBathy Merge Project DEM, with some modifications performed by the USGS Earth Resources Observation and Science (EROS) Center to incorporate the most recent, high-resolution topographic and bathymetric datasets available. Topography is derived from bare-earth light detection and ranging (lidar) data collected in 2009-2011 for the CA Coastal Conservancy Lidar Project and bathymetry from 2009-2010 bathymetric lidar as well as acoustic multi- and single-beam data collected primarily between 2001 and 2013. The DEM was constructed to define the shape of nearshore, beach, and cliff surfaces as accurately as possible, utilizing dozens of bathymetric and topographic data sets. These data were used to populate the majority of the Tier I and II grids. To describe and include impacts from long-term shoreline evolution, including cumulative storm activity, seasonal trends, ENSO, and SLR, the DEM was modified for each SLR scenario. Long-term shoreline (Vitousek and Barnard, 2015) and cliff (Limber and others, 2015) erosion projections were efficiently combined along the cross-shore transects to evolve the shore-normal profiles. Elevation changes from the profiles were spatially-merged for a cohesive, 3D depiction of coastal evolution used to modify the DEM. These data are used to generate initial profiles of the 4,802 CSTs used for Phase 2 Tier III XBeach modeling and determining final projected flood depths in each SLR scenario. All data are referenced to NAD83 horizontal datum and NAVD88 vertical datum. Data for Tiers II and III are projected in UTM, zone 11. Outputs include: Projected flood-hazard depth and duration for the storm and sea-level rise indicated. Data correspond to the areas vulnerable to coastal flooding due to storm surge, sea-level anomalies, tide elevation, and wave run-up during the same storm and sea-level rise simulation. References Cited: Howell, S., Smith-Konter, B., Frazer, N., Tong, X., and Sandwell, D., 2016, The vertical fingerprint of earthquake cycle loading in southern California: Nature Geoscience, v. 9, p. 611-614, doi:10.1038/ngeo2741. Limber, P., Barnard, P.L. and Hapke., C., 2015, Towards projecting the retreat of California’s coastal cliffs during the 21st Century: in, Wang, P., Rosati, J.D., and Cheng, J., (eds.), The Proceedings of the Coastal Sediments: 2015, World Scientific, 14 p., doi:10.1142/9789814689977_0245 Roelvink, J.A., Reniers, A., van Dongeren, A.R., van Thiel de Vries, J., McCall, R., and Lescinski, J., 2009, Modeling storm impacts on beaches, dunes and barrier islands: Coastal Engineering, v. 56, p. 1,133–1,152, doi:10.1016/j.coastaleng.2009.08.006. Tolman, H.L., Balasubramaniyan, B., Burroughs, L.D., Chalikov, D.V., Chao, Y.Y., Chen H.S., Gerald, V.M., 2002, Development and implementation of wind generated ocean surface wave models at NCEP: Weather and Forecasting, v. 17, p. 311-333. Vitousek, S. and Barnard, P.L., 2015, A non-linear, implicit one-line model to predict long-term shoreline change: in, Wang, P., Rosati, J.D., and Cheng, J., (eds.), The Proceedings of the Coastal Sediments: 2015, World Scientific, 14 p., doi:10.1142/9789814689977_0215.

Projected Hazard: Geographic extent of projected coastal flooding, low-lying vulnerable areas, and maxium/minimum flood potential associated with the sea-level rise and storm condition indicated. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the model summary and inspect output carefully. Data are complete for the information presented. Details: Model background: The CoSMoS model comprises three tiers. Tier I consists of one Delft3D hydrodynamics FLOW grid for computation of tides, water level variations, flows, and currents and one SWAN grid for computation of wave generation and propagation across the continental shelf. The FLOW and SWAN models are two-way coupled so that tidal currents are accounted for in wave propagation and growth and conversely, so that orbital velocities generated by waves impart changes on tidal currents. The Tier I SWAN and FLOW models consist of identical structured curvilinear grids that extend from far offshore to the shore and range in resolution from 0.5 km in the offshore to 0.2 km in the nearshore. Spatially varying astronomic tidal amplitudes and phases and steric rises in water levels due to large-scale effects (for example, a prolonged rise in sea level) are applied along all open boundaries of the Tier I FLOW grid. Winds (split into eastward and northward components) and sea-level pressure (SLP) fields from CaRD10 (Dr. Dan Cayan, Scripps Institute of Oceanography, San Diego, California, written commun., 2014) that vary in both space and time are applied to all grid cells at each model time-step. Deep-water wave conditions, applied at the open boundaries of the Tier I SWAN model runs, were projected for the 21st century Representative Concentration Pathway (RCP) 4.5 climate scenario (2011-2100) using the WaveWatch III numerical wave model (Tolman and others, 2002) and 3-hourly winds from the GFDL-ESM2M Global Climate Model (GCM). Tier II provides higher resolution near the shore and in areas that require greater resolution of physical processes (such as bays, harbors, and estuaries). A single nested outer grid and multiple two-way coupled domain decomposition (DD) structured grids allow for local grid refinement and higher resolution where needed. Tier II was segmented into 11 sections along the Southern California Bight, to reduce computation time and complete runs within computational limitations. Water-level and Neumann time-series, extracted from Tier I simulations, are applied to the shore-parallel and lateral open boundaries of each Tier II sub-model outer grid respectively. Several of the sub-models proved to be unstable with lateral Neumann boundaries; for those cases one or both of the lateral boundaries were converted to water-level time-series or left unassigned. The open-boundary time-series are extracted from completed Tier I simulations so that there is no communication from Tier II to Tier I. Because this one-way nesting could produce erroneous results near the boundaries of Tier II and because data near any model boundary are always suspect, Tier II sub-model extents were designed to overlap in the along-coast direction. In the landward direction, Tier II DD grids extend to the 10-m topographic contour; exceptions exist where channels (such as the Los Angeles River) or other low-lying regions extend very far inland. Space- and time-varying wind and SLP fields, identical to those used in Tier I simulations, are applied to all Tier II DD grids to allow for wind-setup and local inverse barometer effects (IBE, rise or depression of water levels in response to atmospheric pressure gradients). A total of 42 time-series fluvial discharges are included in the Tier II FLOW domains in an effort to simulate exacerbated flooding caused by backflow at the confluence of high river seaward flows and elevated coastal surge levels migrating inland. Time-varying fluvial discharges are applied either at the closed boundaries or distributed as point sources within the relevant model domains. Wave computations are accomplished with the SWAN model using two grids for each Tier II sub-model: one larger grid covering the same area as the outer FLOW grid and a second finer resolution two-way coupled nearshore nested grid. The nearshore grid extends from approximately 800-1,000 m water depth up to 8-10 m elevations onshore. The landward extension is included to allow for wave computations of the higher SLR scenarios. Time- and space-varying 2D wave spectra extracted from previously completed Tier I simulations are applied approximately every kilometer along the open boundaries of the outer Tier II sub-model SWAN grids. The same space- and time-varying wind fields used in Tier I simulations are also applied to both Tier II SWAN grids to allow for computation of local wave generation. Tier III for the entire Southern California Bight consists of 4,802 cross-shore transects (CST) spaced approximately 100 m apart in the along-shore direction. The profiles extend from the -15 m isobath to at least 10 m above NAVD88. The CSTs are truncated for cases where a lagoon or other waterway exists on the landward end of the profile. Time-varying water levels and wave parameters (significant wave heights, Hs; peak periods, Tp; and peak incident wave directions, Dp), extracted from Tier II grid cells that coincide with the seaward end of the CSTs, are applied at the open boundary of each CST. The XBeach model is run in a hydrostatic (no vertical pressure gradients) mode including event-based morphodynamic change. Wave propagation, two-way wave-current interaction, water-level variations, and wave runup are computed at each transect. XBeach simulations are included in the CoSMoS model to account for infragravity waves that can significantly extend the reach of wave runup (Roelvink and others, 2009) compared to short-wave incident waves. The U.S. west coast is particularly susceptible to infragravity waves at the shore due to breaking of long-period swell waves (Tp > 15). Resulting water levels (WLs) from both Delft3D (high interest bays and marshes) and open-coast XBeach (CSTs) were spatially combined and interpolated to a 10 m grid. These WL elevations are differenced from the originating 2 m digital elevation model (DEM) to determine final flooding extent and depth of flooding. Events: The model system is run for pre-determined scenarios of interest such as the 1-yr or 100-yr storm event in combination with sea-level rise. Storms are first identified from time-series of total water level proxies (TWLpx) at the shore. TWLpx are computed for the majority of the 21st century (2010-2100), assuming a linear super-position of the major processes that contribute to the overall total water level. TWLpx time-series are then evaluated for extreme events, which define the boundary conditions for subsequent modeling with CoSMoS. Multiple 100-yr events are determined (varying Hs, Tp, Dp) and used for multiple model runs to better account for regional and directional flooding affects. Model results are combined and compiled into scenario-specific composites of flood projection. Digital Elevation Model (DEM): Our seamless, topobathymetric digital elevation model (DEM) was based largely upon the Coastal California TopoBathy Merge Project DEM, with some modifications performed by the USGS Earth Resources Observation and Science (EROS) Center to incorporate the most recent, high-resolution topographic and bathymetric datasets available. Topography is derived from bare-earth light detection and ranging (lidar) data collected in 2009-2011 for the CA Coastal Conservancy Lidar Project and bathymetry from 2009-2010 bathymetric lidar as well as acoustic multi- and single-beam data collected primarily between 2001 and 2013. The DEM was constructed to define the shape of nearshore, beach, and cliff surfaces as accurately as possible, utilizing dozens of bathymetric and topographic data sets. These data were used to populate the majority of the tier I and II grids. To describe and include impacts from long-term shoreline evolution, including cumulative storm activity, seasonal trends, ENSO, and SLR, the DEM was modified for each SLR scenario. Long-term shoreline (Vitousek and Barnard, 2015) and cliff (Limber et al., 2015) erosion projections were efficiently combined along the cross-shore transects to evolve the shore-normal profiles. Elevation changes from the profiles were spatially-merged for a cohesive, 3D depiction of coastal evolution used to modify the DEM. These data are used to generate initial profiles of the 4,802 CSTs used for Phase 2 tier III XBeach modeling and determining final projected flood depths in each SLR scenario. All data are referenced to NAD83 horizontal datum and NAVD88 vertical datum. Data for Tiers II and III are projected in UTM, zone 11. Outputs include: Areas of projected flood hazards: The area vulnerable to coastal flooding due to storm surge, sea-level anomalies, tide elevation, and wave run-up during the storm simulation, based on the maximum elevation of still-water level (inundation for several minutes) at each CST profile. Enclosed areas illustrate the projected water surface and is shown extending from offshore to the extent of coastal flooding for different SLR scenarios between 0 - 2.0 m (0.25 m increments), and at 5.0 m. Low-lying vulnerable areas depict locations where projections indicate flood potential but are not connected to the primary flood surface. Flood potential indicates the maximum and minimum areas of flooding extent considering accuracy of the DEM, hydrodynamic model accuracy, and vertical land motion (Howell et al., 2016). References Cited: Howell, S., Smith-Konter, B., Frazer, N., Tong, X., and Sandwell, D., 2016, The vertical fingerprint of earthquake cycle loading in southern California: Nature Geoscience, v. 9, p. 611-614, doi:10.1038/ngeo2741. Limber, P., Barnard, P.L. and Hapke., C., 2015, Towards projecting the retreat of California’s coastal cliffs during the 21st Century: in, Wang, P., Rosati, J.D., and Cheng, J., (eds.), The Proceedings of the Coastal Sediments: 2015, World Scientific, 14 p., doi:10.1142/9789814689977_0245 Roelvink, J.A., Reniers, A., van Dongeren, A.R., van Thiel de Vries, J., McCall, R., and Lescinski, J., 2009, Modeling storm impacts on beaches, dunes and barrier islands: Coastal Engineering, v. 56, p. 1,133–1,152, doi:10.1016/j.coastaleng.2009.08.006. Tolman, H.L., Balasubramaniyan, B., Burroughs, L.D., Chalikov, D.V., Chao, Y.Y., Chen H.S., Gerald, V.M., 2002, Development and implementation of wind generated ocean surface wave models at NCEP: Weather and Forecasting, v. 17, p. 311-333. Vitousek, S. and Barnard, P.L., 2015, A non-linear, implicit one-line model to predict long-term shoreline change: in, Wang, P., Rosati, J.D., and Cheng, J., (eds.), The Proceedings of the Coastal Sediments: 2015, World Scientific, 14 p., doi:10.1142/9789814689977_0215.

Projected Hazard: Geographic extent of projected coastal flooding, low-lying vulnerable areas, and maxium/minimum flood potential associated with the sea-level rise and storm condition indicated. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the model summary and inspect output carefully. Data are complete for the information presented. Details: Model background: The CoSMoS model comprises three tiers. Tier I consists of one Delft3D hydrodynamics FLOW grid for computation of tides, water level variations, flows, and currents and one SWAN grid for computation of wave generation and propagation across the continental shelf. The FLOW and SWAN models are two-way coupled so that tidal currents are accounted for in wave propagation and growth and conversely, so that orbital velocities generated by waves impart changes on tidal currents. The Tier I SWAN and FLOW models consist of identical structured curvilinear grids that extend from far offshore to the shore and range in resolution from 0.5 km in the offshore to 0.2 km in the nearshore. Spatially varying astronomic tidal amplitudes and phases and steric rises in water levels due to large-scale effects (for example, a prolonged rise in sea level) are applied along all open boundaries of the Tier I FLOW grid. Winds (split into eastward and northward components) and sea-level pressure (SLP) fields from CaRD10 (Dr. Dan Cayan, Scripps Institute of Oceanography, San Diego, California, written commun., 2014) that vary in both space and time are applied to all grid cells at each model time-step. Deep-water wave conditions, applied at the open boundaries of the Tier I SWAN model runs, were projected for the 21st century Representative Concentration Pathway (RCP) 4.5 climate scenario (2011-2100) using the WaveWatch III numerical wave model (Tolman and others, 2002) and 3-hourly winds from the GFDL-ESM2M Global Climate Model (GCM). Tier II provides higher resolution near the shore and in areas that require greater resolution of physical processes (such as bays, harbors, and estuaries). A single nested outer grid and multiple two-way coupled domain decomposition (DD) structured grids allow for local grid refinement and higher resolution where needed. Tier II was segmented into 11 sections along the Southern California Bight, to reduce computation time and complete runs within computational limitations. Water-level and Neumann time-series, extracted from Tier I simulations, are applied to the shore-parallel and lateral open boundaries of each Tier II sub-model outer grid respectively. Several of the sub-models proved to be unstable with lateral Neumann boundaries; for those cases one or both of the lateral boundaries were converted to water-level time-series or left unassigned. The open-boundary time-series are extracted from completed Tier I simulations so that there is no communication from Tier II to Tier I. Because this one-way nesting could produce erroneous results near the boundaries of Tier II and because data near any model boundary are always suspect, Tier II sub-model extents were designed to overlap in the along-coast direction. In the landward direction, Tier II DD grids extend to the 10-m topographic contour; exceptions exist where channels (such as the Los Angeles River) or other low-lying regions extend very far inland. Space- and time-varying wind and SLP fields, identical to those used in Tier I simulations, are applied to all Tier II DD grids to allow for wind-setup and local inverse barometer effects (IBE, rise or depression of water levels in response to atmospheric pressure gradients). A total of 42 time-series fluvial discharges are included in the Tier II FLOW domains in an effort to simulate exacerbated flooding caused by backflow at the confluence of high river seaward flows and elevated coastal surge levels migrating inland. Time-varying fluvial discharges are applied either at the closed boundaries or distributed as point sources within the relevant model domains. Wave computations are accomplished with the SWAN model using two grids for each Tier II sub-model: one larger grid covering the same area as the outer FLOW grid and a second finer resolution two-way coupled nearshore nested grid. The nearshore grid extends from approximately 800-1,000 m water depth up to 8-10 m elevations onshore. The landward extension is included to allow for wave computations of the higher SLR scenarios. Time- and space-varying 2D wave spectra extracted from previously completed Tier I simulations are applied approximately every kilometer along the open boundaries of the outer Tier II sub-model SWAN grids. The same space- and time-varying wind fields used in Tier I simulations are also applied to both Tier II SWAN grids to allow for computation of local wave generation. Tier III for the entire Southern California Bight consists of 4,802 cross-shore transects (CST) spaced approximately 100 m apart in the along-shore direction. The profiles extend from the -15 m isobath to at least 10 m above NAVD88. The CSTs are truncated for cases where a lagoon or other waterway exists on the landward end of the profile. Time-varying water levels and wave parameters (significant wave heights, Hs; peak periods, Tp; and peak incident wave directions, Dp), extracted from Tier II grid cells that coincide with the seaward end of the CSTs, are applied at the open boundary of each CST. The XBeach model is run in a hydrostatic (no vertical pressure gradients) mode including event-based morphodynamic change. Wave propagation, two-way wave-current interaction, water-level variations, and wave runup are computed at each transect. XBeach simulations are included in the CoSMoS model to account for infragravity waves that can significantly extend the reach of wave runup (Roelvink and others, 2009) compared to short-wave incident waves. The U.S. west coast is particularly susceptible to infragravity waves at the shore due to breaking of long-period swell waves (Tp > 15). Resulting water levels (WLs) from both Delft3D (high interest bays and marshes) and open-coast XBeach (CSTs) were spatially combined and interpolated to a 10 m grid. These WL elevations are differenced from the originating 2 m digital elevation model (DEM) to determine final flooding extent and depth of flooding. Events: The model system is run for pre-determined scenarios of interest such as the 1-yr or 100-yr storm event in combination with sea-level rise. Storms are first identified from time-series of total water level proxies (TWLpx) at the shore. TWLpx are computed for the majority of the 21st century (2010-2100), assuming a linear super-position of the major processes that contribute to the overall total water level. TWLpx time-series are then evaluated for extreme events, which define the boundary conditions for subsequent modeling with CoSMoS. Multiple 100-yr events are determined (varying Hs, Tp, Dp) and used for multiple model runs to better account for regional and directional flooding affects. Model results are combined and compiled into scenario-specific composites of flood projection. Digital Elevation Model (DEM): Our seamless, topobathymetric digital elevation model (DEM) was based largely upon the Coastal California TopoBathy Merge Project DEM, with some modifications performed by the USGS Earth Resources Observation and Science (EROS) Center to incorporate the most recent, high-resolution topographic and bathymetric datasets available. Topography is derived from bare-earth light detection and ranging (lidar) data collected in 2009-2011 for the CA Coastal Conservancy Lidar Project and bathymetry from 2009-2010 bathymetric lidar as well as acoustic multi- and single-beam data collected primarily between 2001 and 2013. The DEM was constructed to define the shape of nearshore, beach, and cliff surfaces as accurately as possible, utilizing dozens of bathymetric and topographic data sets. These data were used to populate the majority of the tier I and II grids. To describe and include impacts from long-term shoreline evolution, including cumulative storm activity, seasonal trends, ENSO, and SLR, the DEM was modified for each SLR scenario. Long-term shoreline (Vitousek and Barnard, 2015) and cliff (Limber et al., 2015) erosion projections were efficiently combined along the cross-shore transects to evolve the shore-normal profiles. Elevation changes from the profiles were spatially-merged for a cohesive, 3D depiction of coastal evolution used to modify the DEM. These data are used to generate initial profiles of the 4,802 CSTs used for Phase 2 tier III XBeach modeling and determining final projected flood depths in each SLR scenario. All data are referenced to NAD83 horizontal datum and NAVD88 vertical datum. Data for Tiers II and III are projected in UTM, zone 11. Outputs include: Areas of projected flood hazards: The area vulnerable to coastal flooding due to storm surge, sea-level anomalies, tide elevation, and wave run-up during the storm simulation, based on the maximum elevation of still-water level (inundation for several minutes) at each CST profile. Enclosed areas illustrate the projected water surface and is shown extending from offshore to the extent of coastal flooding for different SLR scenarios between 0 - 2.0 m (0.25 m increments), and at 5.0 m. Low-lying vulnerable areas depict locations where projections indicate flood potential but are not connected to the primary flood surface. Flood potential indicates the maximum and minimum areas of flooding extent considering accuracy of the DEM, hydrodynamic model accuracy, and vertical land motion (Howell et al., 2016). References Cited: Howell, S., Smith-Konter, B., Frazer, N., Tong, X., and Sandwell, D., 2016, The vertical fingerprint of earthquake cycle loading in southern California: Nature Geoscience, v. 9, p. 611-614, doi:10.1038/ngeo2741. Limber, P., Barnard, P.L. and Hapke., C., 2015, Towards projecting the retreat of California’s coastal cliffs during the 21st Century: in, Wang, P., Rosati, J.D., and Cheng, J., (eds.), The Proceedings of the Coastal Sediments: 2015, World Scientific, 14 p., doi:10.1142/9789814689977_0245 Roelvink, J.A., Reniers, A., van Dongeren, A.R., van Thiel de Vries, J., McCall, R., and Lescinski, J., 2009, Modeling storm impacts on beaches, dunes and barrier islands: Coastal Engineering, v. 56, p. 1,133–1,152, doi:10.1016/j.coastaleng.2009.08.006. Tolman, H.L., Balasubramaniyan, B., Burroughs, L.D., Chalikov, D.V., Chao, Y.Y., Chen H.S., Gerald, V.M., 2002, Development and implementation of wind generated ocean surface wave models at NCEP: Weather and Forecasting, v. 17, p. 311-333. Vitousek, S. and Barnard, P.L., 2015, A non-linear, implicit one-line model to predict long-term shoreline change: in, Wang, P., Rosati, J.D., and Cheng, J., (eds.), The Proceedings of the Coastal Sediments: 2015, World Scientific, 14 p., doi:10.1142/9789814689977_0215.

Projected Hazard: Geographic extent of projected coastal flooding, low-lying vulnerable areas, and maxium/minimum flood potential associated with the sea-level rise and storm condition indicated. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the model summary and inspect output carefully. Data are complete for the information presented. Details: Model background: The CoSMoS model comprises three tiers. Tier I consists of one Delft3D hydrodynamics FLOW grid for computation of tides, water level variations, flows, and currents and one SWAN grid for computation of wave generation and propagation across the continental shelf. The FLOW and SWAN models are two-way coupled so that tidal currents are accounted for in wave propagation and growth and conversely, so that orbital velocities generated by waves impart changes on tidal currents. The Tier I SWAN and FLOW models consist of identical structured curvilinear grids that extend from far offshore to the shore and range in resolution from 0.5 km in the offshore to 0.2 km in the nearshore. Spatially varying astronomic tidal amplitudes and phases and steric rises in water levels due to large-scale effects (for example, a prolonged rise in sea level) are applied along all open boundaries of the Tier I FLOW grid. Winds (split into eastward and northward components) and sea-level pressure (SLP) fields from CaRD10 (Dr. Dan Cayan, Scripps Institute of Oceanography, San Diego, California, written commun., 2014) that vary in both space and time are applied to all grid cells at each model time-step. Deep-water wave conditions, applied at the open boundaries of the Tier I SWAN model runs, were projected for the 21st century Representative Concentration Pathway (RCP) 4.5 climate scenario (2011-2100) using the WaveWatch III numerical wave model (Tolman and others, 2002) and 3-hourly winds from the GFDL-ESM2M Global Climate Model (GCM). Tier II provides higher resolution near the shore and in areas that require greater resolution of physical processes (such as bays, harbors, and estuaries). A single nested outer grid and multiple two-way coupled domain decomposition (DD) structured grids allow for local grid refinement and higher resolution where needed. Tier II was segmented into 11 sections along the Southern California Bight, to reduce computation time and complete runs within computational limitations. Water-level and Neumann time-series, extracted from Tier I simulations, are applied to the shore-parallel and lateral open boundaries of each Tier II sub-model outer grid respectively. Several of the sub-models proved to be unstable with lateral Neumann boundaries; for those cases one or both of the lateral boundaries were converted to water-level time-series or left unassigned. The open-boundary time-series are extracted from completed Tier I simulations so that there is no communication from Tier II to Tier I. Because this one-way nesting could produce erroneous results near the boundaries of Tier II and because data near any model boundary are always suspect, Tier II sub-model extents were designed to overlap in the along-coast direction. In the landward direction, Tier II DD grids extend to the 10-m topographic contour; exceptions exist where channels (such as the Los Angeles River) or other low-lying regions extend very far inland. Space- and time-varying wind and SLP fields, identical to those used in Tier I simulations, are applied to all Tier II DD grids to allow for wind-setup and local inverse barometer effects (IBE, rise or depression of water levels in response to atmospheric pressure gradients). A total of 42 time-series fluvial discharges are included in the Tier II FLOW domains in an effort to simulate exacerbated flooding caused by backflow at the confluence of high river seaward flows and elevated coastal surge levels migrating inland. Time-varying fluvial discharges are applied either at the closed boundaries or distributed as point sources within the relevant model domains. Wave computations are accomplished with the SWAN model using two grids for each Tier II sub-model: one larger grid covering the same area as the outer FLOW grid and a second finer resolution two-way coupled nearshore nested grid. The nearshore grid extends from approximately 800-1,000 m water depth up to 8-10 m elevations onshore. The landward extension is included to allow for wave computations of the higher SLR scenarios. Time- and space-varying 2D wave spectra extracted from previously completed Tier I simulations are applied approximately every kilometer along the open boundaries of the outer Tier II sub-model SWAN grids. The same space- and time-varying wind fields used in Tier I simulations are also applied to both Tier II SWAN grids to allow for computation of local wave generation. Tier III for the entire Southern California Bight consists of 4,802 cross-shore transects (CST) spaced approximately 100 m apart in the along-shore direction. The profiles extend from the -15 m isobath to at least 10 m above NAVD88. The CSTs are truncated for cases where a lagoon or other waterway exists on the landward end of the profile. Time-varying water levels and wave parameters (significant wave heights, Hs; peak periods, Tp; and peak incident wave directions, Dp), extracted from Tier II grid cells that coincide with the seaward end of the CSTs, are applied at the open boundary of each CST. The XBeach model is run in a hydrostatic (no vertical pressure gradients) mode including event-based morphodynamic change. Wave propagation, two-way wave-current interaction, water-level variations, and wave runup are computed at each transect. XBeach simulations are included in the CoSMoS model to account for infragravity waves that can significantly extend the reach of wave runup (Roelvink and others, 2009) compared to short-wave incident waves. The U.S. west coast is particularly susceptible to infragravity waves at the shore due to breaking of long-period swell waves (Tp > 15). Resulting water levels (WLs) from both Delft3D (high interest bays and marshes) and open-coast XBeach (CSTs) were spatially combined and interpolated to a 10 m grid. These WL elevations are differenced from the originating 2 m digital elevation model (DEM) to determine final flooding extent and depth of flooding. Events: The model system is run for pre-determined scenarios of interest such as the 1-yr or 100-yr storm event in combination with sea-level rise. Storms are first identified from time-series of total water level proxies (TWLpx) at the shore. TWLpx are computed for the majority of the 21st century (2010-2100), assuming a linear super-position of the major processes that contribute to the overall total water level. TWLpx time-series are then evaluated for extreme events, which define the boundary conditions for subsequent modeling with CoSMoS. Multiple 100-yr events are determined (varying Hs, Tp, Dp) and used for multiple model runs to better account for regional and directional flooding affects. Model results are combined and compiled into scenario-specific composites of flood projection. Digital Elevation Model (DEM): Our seamless, topobathymetric digital elevation model (DEM) was based largely upon the Coastal California TopoBathy Merge Project DEM, with some modifications performed by the USGS Earth Resources Observation and Science (EROS) Center to incorporate the most recent, high-resolution topographic and bathymetric datasets available. Topography is derived from bare-earth light detection and ranging (lidar) data collected in 2009-2011 for the CA Coastal Conservancy Lidar Project and bathymetry from 2009-2010 bathymetric lidar as well as acoustic multi- and single-beam data collected primarily between 2001 and 2013. The DEM was constructed to define the shape of nearshore, beach, and cliff surfaces as accurately as possible, utilizing dozens of bathymetric and topographic data sets. These data were used to populate the majority of the tier I and II grids. To describe and include impacts from long-term shoreline evolution, including cumulative storm activity, seasonal trends, ENSO, and SLR, the DEM was modified for each SLR scenario. Long-term shoreline (Vitousek and Barnard, 2015) and cliff (Limber et al., 2015) erosion projections were efficiently combined along the cross-shore transects to evolve the shore-normal profiles. Elevation changes from the profiles were spatially-merged for a cohesive, 3D depiction of coastal evolution used to modify the DEM. These data are used to generate initial profiles of the 4,802 CSTs used for Phase 2 tier III XBeach modeling and determining final projected flood depths in each SLR scenario. All data are referenced to NAD83 horizontal datum and NAVD88 vertical datum. Data for Tiers II and III are projected in UTM, zone 11. Outputs include: Areas of projected flood hazards: The area vulnerable to coastal flooding due to storm surge, sea-level anomalies, tide elevation, and wave run-up during the storm simulation, based on the maximum elevation of still-water level (inundation for several minutes) at each CST profile. Enclosed areas illustrate the projected water surface and is shown extending from offshore to the extent of coastal flooding for different SLR scenarios between 0 - 2.0 m (0.25 m increments), and at 5.0 m. Low-lying vulnerable areas depict locations where projections indicate flood potential but are not connected to the primary flood surface. Flood potential indicates the maximum and minimum areas of flooding extent considering accuracy of the DEM, hydrodynamic model accuracy, and vertical land motion (Howell et al., 2016). References Cited: Howell, S., Smith-Konter, B., Frazer, N., Tong, X., and Sandwell, D., 2016, The vertical fingerprint of earthquake cycle loading in southern California: Nature Geoscience, v. 9, p. 611-614, doi:10.1038/ngeo2741. Limber, P., Barnard, P.L. and Hapke., C., 2015, Towards projecting the retreat of California’s coastal cliffs during the 21st Century: in, Wang, P., Rosati, J.D., and Cheng, J., (eds.), The Proceedings of the Coastal Sediments: 2015, World Scientific, 14 p., doi:10.1142/9789814689977_0245 Roelvink, J.A., Reniers, A., van Dongeren, A.R., van Thiel de Vries, J., McCall, R., and Lescinski, J., 2009, Modeling storm impacts on beaches, dunes and barrier islands: Coastal Engineering, v. 56, p. 1,133–1,152, doi:10.1016/j.coastaleng.2009.08.006. Tolman, H.L., Balasubramaniyan, B., Burroughs, L.D., Chalikov, D.V., Chao, Y.Y., Chen H.S., Gerald, V.M., 2002, Development and implementation of wind generated ocean surface wave models at NCEP: Weather and Forecasting, v. 17, p. 311-333. Vitousek, S. and Barnard, P.L., 2015, A non-linear, implicit one-line model to predict long-term shoreline change: in, Wang, P., Rosati, J.D., and Cheng, J., (eds.), The Proceedings of the Coastal Sediments: 2015, World Scientific, 14 p., doi:10.1142/9789814689977_0215.

Projected Hazard: Geographic extent of projected coastal flooding, low-lying vulnerable areas, and maxium/minimum flood potential associated with the sea-level rise and storm condition indicated. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the model summary and inspect output carefully. Data are complete for the information presented. Details: Model background: The CoSMoS model comprises three tiers. Tier I consists of one Delft3D hydrodynamics FLOW grid for computation of tides, water level variations, flows, and currents and one SWAN grid for computation of wave generation and propagation across the continental shelf. The FLOW and SWAN models are two-way coupled so that tidal currents are accounted for in wave propagation and growth and conversely, so that orbital velocities generated by waves impart changes on tidal currents. The Tier I SWAN and FLOW models consist of identical structured curvilinear grids that extend from far offshore to the shore and range in resolution from 0.5 km in the offshore to 0.2 km in the nearshore. Spatially varying astronomic tidal amplitudes and phases and steric rises in water levels due to large-scale effects (for example, a prolonged rise in sea level) are applied along all open boundaries of the Tier I FLOW grid. Winds (split into eastward and northward components) and sea-level pressure (SLP) fields from CaRD10 (Dr. Dan Cayan, Scripps Institute of Oceanography, San Diego, California, written commun., 2014) that vary in both space and time are applied to all grid cells at each model time-step. Deep-water wave conditions, applied at the open boundaries of the Tier I SWAN model runs, were projected for the 21st century Representative Concentration Pathway (RCP) 4.5 climate scenario (2011-2100) using the WaveWatch III numerical wave model (Tolman and others, 2002) and 3-hourly winds from the GFDL-ESM2M Global Climate Model (GCM). Tier II provides higher resolution near the shore and in areas that require greater resolution of physical processes (such as bays, harbors, and estuaries). A single nested outer grid and multiple two-way coupled domain decomposition (DD) structured grids allow for local grid refinement and higher resolution where needed. Tier II was segmented into 11 sections along the Southern California Bight, to reduce computation time and complete runs within computational limitations. Water-level and Neumann time-series, extracted from Tier I simulations, are applied to the shore-parallel and lateral open boundaries of each Tier II sub-model outer grid respectively. Several of the sub-models proved to be unstable with lateral Neumann boundaries; for those cases one or both of the lateral boundaries were converted to water-level time-series or left unassigned. The open-boundary time-series are extracted from completed Tier I simulations so that there is no communication from Tier II to Tier I. Because this one-way nesting could produce erroneous results near the boundaries of Tier II and because data near any model boundary are always suspect, Tier II sub-model extents were designed to overlap in the along-coast direction. In the landward direction, Tier II DD grids extend to the 10-m topographic contour; exceptions exist where channels (such as the Los Angeles River) or other low-lying regions extend very far inland. Space- and time-varying wind and SLP fields, identical to those used in Tier I simulations, are applied to all Tier II DD grids to allow for wind-setup and local inverse barometer effects (IBE, rise or depression of water levels in response to atmospheric pressure gradients). A total of 42 time-series fluvial discharges are included in the Tier II FLOW domains in an effort to simulate exacerbated flooding caused by backflow at the confluence of high river seaward flows and elevated coastal surge levels migrating inland. Time-varying fluvial discharges are applied either at the closed boundaries or distributed as point sources within the relevant model domains. Wave computations are accomplished with the SWAN model using two grids for each Tier II sub-model: one larger grid covering the same area as the outer FLOW grid and a second finer resolution two-way coupled nearshore nested grid. The nearshore grid extends from approximately 800-1,000 m water depth up to 8-10 m elevations onshore. The landward extension is included to allow for wave computations of the higher SLR scenarios. Time- and space-varying 2D wave spectra extracted from previously completed Tier I simulations are applied approximately every kilometer along the open boundaries of the outer Tier II sub-model SWAN grids. The same space- and time-varying wind fields used in Tier I simulations are also applied to both Tier II SWAN grids to allow for computation of local wave generation. Tier III for the entire Southern California Bight consists of 4,802 cross-shore transects (CST) spaced approximately 100 m apart in the along-shore direction. The profiles extend from the -15 m isobath to at least 10 m above NAVD88. The CSTs are truncated for cases where a lagoon or other waterway exists on the landward end of the profile. Time-varying water levels and wave parameters (significant wave heights, Hs; peak periods, Tp; and peak incident wave directions, Dp), extracted from Tier II grid cells that coincide with the seaward end of the CSTs, are applied at the open boundary of each CST. The XBeach model is run in a hydrostatic (no vertical pressure gradients) mode including event-based morphodynamic change. Wave propagation, two-way wave-current interaction, water-level variations, and wave runup are computed at each transect. XBeach simulations are included in the CoSMoS model to account for infragravity waves that can significantly extend the reach of wave runup (Roelvink and others, 2009) compared to short-wave incident waves. The U.S. west coast is particularly susceptible to infragravity waves at the shore due to breaking of long-period swell waves (Tp > 15). Resulting water levels (WLs) from both Delft3D (high interest bays and marshes) and open-coast XBeach (CSTs) were spatially combined and interpolated to a 10 m grid. These WL elevations are differenced from the originating 2 m digital elevation model (DEM) to determine final flooding extent and depth of flooding. Events: The model system is run for pre-determined scenarios of interest such as the 1-yr or 100-yr storm event in combination with sea-level rise. Storms are first identified from time-series of total water level proxies (TWLpx) at the shore. TWLpx are computed for the majority of the 21st century (2010-2100), assuming a linear super-position of the major processes that contribute to the overall total water level. TWLpx time-series are then evaluated for extreme events, which define the boundary conditions for subsequent modeling with CoSMoS. Multiple 100-yr events are determined (varying Hs, Tp, Dp) and used for multiple model runs to better account for regional and directional flooding affects. Model results are combined and compiled into scenario-specific composites of flood projection. Digital Elevation Model (DEM): Our seamless, topobathymetric digital elevation model (DEM) was based largely upon the Coastal California TopoBathy Merge Project DEM, with some modifications performed by the USGS Earth Resources Observation and Science (EROS) Center to incorporate the most recent, high-resolution topographic and bathymetric datasets available. Topography is derived from bare-earth light detection and ranging (lidar) data collected in 2009-2011 for the CA Coastal Conservancy Lidar Project and bathymetry from 2009-2010 bathymetric lidar as well as acoustic multi- and single-beam data collected primarily between 2001 and 2013. The DEM was constructed to define the shape of nearshore, beach, and cliff surfaces as accurately as possible, utilizing dozens of bathymetric and topographic data sets. These data were used to populate the majority of the tier I and II grids. To describe and include impacts from long-term shoreline evolution, including cumulative storm activity, seasonal trends, ENSO, and SLR, the DEM was modified for each SLR scenario. Long-term shoreline (Vitousek and Barnard, 2015) and cliff (Limber et al., 2015) erosion projections were efficiently combined along the cross-shore transects to evolve the shore-normal profiles. Elevation changes from the profiles were spatially-merged for a cohesive, 3D depiction of coastal evolution used to modify the DEM. These data are used to generate initial profiles of the 4,802 CSTs used for Phase 2 tier III XBeach modeling and determining final projected flood depths in each SLR scenario. All data are referenced to NAD83 horizontal datum and NAVD88 vertical datum. Data for Tiers II and III are projected in UTM, zone 11. Outputs include: Areas of projected flood hazards: The area vulnerable to coastal flooding due to storm surge, sea-level anomalies, tide elevation, and wave run-up during the storm simulation, based on the maximum elevation of still-water level (inundation for several minutes) at each CST profile. Enclosed areas illustrate the projected water surface and is shown extending from offshore to the extent of coastal flooding for different SLR scenarios between 0 - 2.0 m (0.25 m increments), and at 5.0 m. Low-lying vulnerable areas depict locations where projections indicate flood potential but are not connected to the primary flood surface. Flood potential indicates the maximum and minimum areas of flooding extent considering accuracy of the DEM, hydrodynamic model accuracy, and vertical land motion (Howell et al., 2016). References Cited: Howell, S., Smith-Konter, B., Frazer, N., Tong, X., and Sandwell, D., 2016, The vertical fingerprint of earthquake cycle loading in southern California: Nature Geoscience, v. 9, p. 611-614, doi:10.1038/ngeo2741. Limber, P., Barnard, P.L. and Hapke., C., 2015, Towards projecting the retreat of California’s coastal cliffs during the 21st Century: in, Wang, P., Rosati, J.D., and Cheng, J., (eds.), The Proceedings of the Coastal Sediments: 2015, World Scientific, 14 p., doi:10.1142/9789814689977_0245 Roelvink, J.A., Reniers, A., van Dongeren, A.R., van Thiel de Vries, J., McCall, R., and Lescinski, J., 2009, Modeling storm impacts on beaches, dunes and barrier islands: Coastal Engineering, v. 56, p. 1,133–1,152, doi:10.1016/j.coastaleng.2009.08.006. Tolman, H.L., Balasubramaniyan, B., Burroughs, L.D., Chalikov, D.V., Chao, Y.Y., Chen H.S., Gerald, V.M., 2002, Development and implementation of wind generated ocean surface wave models at NCEP: Weather and Forecasting, v. 17, p. 311-333. Vitousek, S. and Barnard, P.L., 2015, A non-linear, implicit one-line model to predict long-term shoreline change: in, Wang, P., Rosati, J.D., and Cheng, J., (eds.), The Proceedings of the Coastal Sediments: 2015, World Scientific, 14 p., doi:10.1142/9789814689977_0215.

Projected Hazard: Model-derived ocean current velocities (in meters per second) for the given storm condition and sea-level rise (SLR) scenario. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the model summary and inspect output carefully. Data are complete for the information presented. Details: Model background: The CoSMoS model comprises three tiers. Tier I consists of one Delft3D hydrodynamics FLOW grid for computation of tides, water level variations, flows, and currents and one SWAN grid for computation of wave generation and propagation across the continental shelf. The FLOW and SWAN models are two-way coupled so that tidal currents are accounted for in wave propagation and growth and conversely, so that orbital velocities generated by waves impart changes on tidal currents. The Tier I SWAN and FLOW models consist of identical structured curvilinear grids that extend from far offshore to the shore and range in resolution from 0.5 km in the offshore to 0.2 km in the nearshore. Spatially varying astronomic tidal amplitudes and phases and steric rises in water levels due to large-scale effects (for example, a prolonged rise in sea level) are applied along all open boundaries of the Tier I FLOW grid. Winds (split into eastward and northward components) and sea-level pressure (SLP) fields from CaRD10 (Dr. Dan Cayan, Scripps Institute of Oceanography, San Diego, California, written commun., 2014) that vary in both space and time are applied to all grid cells at each model time-step. Deep-water wave conditions, applied at the open boundaries of the Tier I SWAN model runs, were projected for the 21st century Representative Concentration Pathway (RCP) 4.5 climate scenario (2011-2100) using the WaveWatch III numerical wave model (Tolman and others, 2002) and 3-hourly winds from the GFDL-ESM2M Global Climate Model (GCM). Tier II provides higher resolution near the shore and in areas that require greater resolution of physical processes (such as bays, harbors, and estuaries). A single nested outer grid and multiple two-way coupled domain decomposition (DD) structured grids allow for local grid refinement and higher resolution where needed. Tier II was segmented into 11 sections along the Southern California Bight, to reduce computation time and complete runs within computational limitations. Water-level and Neumann time-series, extracted from Tier I simulations, are applied to the shore-parallel and lateral open boundaries of each Tier II sub-model outer grid respectively. Several of the sub-models proved to be unstable with lateral Neumann boundaries; for those cases one or both of the lateral boundaries were converted to water-level time-series or left unassigned. The open-boundary time-series are extracted from completed Tier I simulations so that there is no communication from Tier II to Tier I. Because this one-way nesting could produce erroneous results near the boundaries of Tier II and because data near any model boundary are always suspect, Tier II sub-model extents were designed to overlap in the along-coast direction. In the landward direction, Tier II DD grids extend to the 10-m topographic contour; exceptions exist where channels (such as the Los Angeles River) or other low-lying regions extend very far inland. Space- and time-varying wind and SLP fields, identical to those used in Tier I simulations, are applied to all Tier II DD grids to allow for wind-setup and local inverse barometer effects (IBE, rise or depression of water levels in response to atmospheric pressure gradients). A total of 42 time-series fluvial discharges are included in the Tier II FLOW domains in an effort to simulate exacerbated flooding caused by backflow at the confluence of high river seaward flows and elevated coastal surge levels migrating inland. Time-varying fluvial discharges are applied either at the closed boundaries or distributed as point sources within the relevant model domains. Wave computations are accomplished with the SWAN model using two grids for each Tier II sub-model: one larger grid covering the same area as the outer FLOW grid and a second finer resolution two-way coupled nearshore nested grid. The nearshore grid extends from approximately 800-1,000 m water depth up to 8-10 m elevations onshore. The landward extension is included to allow for wave computations of the higher SLR scenarios. Time- and space-varying 2D wave spectra extracted from previously completed Tier I simulations are applied approximately every kilometer along the open boundaries of the outer Tier II sub-model SWAN grids. The same space- and time-varying wind fields used in Tier I simulations are also applied to both Tier II SWAN grids to allow for computation of local wave generation. Tier III for the entire Southern California Bight consists of 4,802 cross-shore transects (CST) spaced approximately 100 m apart in the along-shore direction. The profiles extend from the -15 m isobath to at least 10 m above NAVD88. The CSTs are truncated for cases where a lagoon or other waterway exists on the landward end of the profile. Time-varying water levels and wave parameters (significant wave heights, Hs; peak periods, Tp; and peak incident wave directions, Dp), extracted from Tier II grid cells that coincide with the seaward end of the CSTs, are applied at the open boundary of each CST. The XBeach model is run in a hydrostatic (no vertical pressure gradients) mode including event-based morphodynamic change. Wave propagation, two-way wave-current interaction, water-level variations, and wave runup are computed at each transect. XBeach simulations are included in the CoSMoS model to account for infragravity waves that can significantly extend the reach of wave runup (Roelvink and others, 2009) compared to short-wave incident waves. The U.S. west coast is particularly susceptible to infragravity waves at the shore due to breaking of long-period swell waves (Tp > 15). Resulting water levels (WLs) from both Delft3D (high interest bays and marshes) and open-coast XBeach (CSTs) were spatially combined and interpolated to a 10 m grid. These WL elevations are differenced from the originating 2 m digital elevation model (DEM) to determine final flooding extent and depth of flooding. Events: The model system is run for pre-determined scenarios of interest such as the 1-yr or 100-yr storm event in combination with sea-level rise. Storms are first identified from time-series of total water level proxies (TWLpx) at the shore. TWLpx are computed for the majority of the 21st century (2010-2100), assuming a linear super-position of the major processes that contribute to the overall total water level. TWLpx time-series are then evaluated for extreme events, which define the boundary conditions for subsequent modeling with CoSMoS. Multiple 100-yr events are determined (varying Hs, Tp, Dp) and used for multiple model runs to better account for regional and directional flooding affects. Model results are combined and compiled into scenario-specific composites of flood projection. Digital Elevation Model (DEM): Our seamless, topobathymetric digital elevation model (DEM) was based largely upon the Coastal California TopoBathy Merge Project DEM, with some modifications performed by the USGS Earth Resources Observation and Science (EROS) Center to incorporate the most recent, high-resolution topographic and bathymetric datasets available. Topography is derived from bare-earth light detection and ranging (lidar) data collected in 2009-2011 for the CA Coastal Conservancy Lidar Project and bathymetry from 2009-2010 bathymetric lidar as well as acoustic multi- and single-beam data collected primarily between 2001 and 2013. The DEM was constructed to define the shape of nearshore, beach, and cliff surfaces as accurately as possible, utilizing dozens of bathymetric and topographic data sets. These data were used to populate the majority of the Tier I and II grids. To describe and include impacts from long-term shoreline evolution, including cumulative storm activity, seasonal trends, ENSO, and SLR, the DEM was modified for each SLR scenario. Long-term shoreline (Vitousek and Barnard, 2015) and cliff (Limber and others, 2015) erosion projections were efficiently combined along the cross-shore transects to evolve the shore-normal profiles. Elevation changes from the profiles were spatially-merged for a cohesive, 3D depiction of coastal evolution used to modify the DEM. These data are used to generate initial profiles of the 4,802 CSTs used for Phase 2 Tier III XBeach modeling and determining final projected flood depths in each SLR scenario. All data are referenced to NAD83 horizontal datum and NAVD88 vertical datum. Data for Tiers II and III are projected in UTM, zone 11. Outputs include: Projected ocean current velocities for the 100-year storm and 0.0 m sea-level rise scenario. Data correspond to the near-shore region including areas vulnerable to coastal flooding due to storm surge, sea-level anomalies, tide elevation, and wave run-up during the same storm and sea-level rise simulation. References Cited: Howell, S., Smith-Konter, B., Frazer, N., Tong, X., and Sandwell, D., 2016, The vertical fingerprint of earthquake cycle loading in southern California: Nature Geoscience, v. 9, p. 611-614, doi:10.1038/ngeo2741. Limber, P., Barnard, P.L. and Hapke., C., 2015, Towards projecting the retreat of California’s coastal cliffs during the 21st Century: in, Wang, P., Rosati, J.D., and Cheng, J., (eds.), The Proceedings of the Coastal Sediments: 2015, World Scientific, 14 p., doi:10.1142/9789814689977_0245 Roelvink, J.A., Reniers, A., van Dongeren, A.R., van Thiel de Vries, J., McCall, R., and Lescinski, J., 2009, Modeling storm impacts on beaches, dunes and barrier islands: Coastal Engineering, v. 56, p. 1,133–1,152, doi:10.1016/j.coastaleng.2009.08.006. Tolman, H.L., Balasubramaniyan, B., Burroughs, L.D., Chalikov, D.V., Chao, Y.Y., Chen H.S., Gerald, V.M., 2002, Development and implementation of wind generated ocean surface wave models at NCEP: Weather and Forecasting, v. 17, p. 311-333. Vitousek, S. and Barnard, P.L., 2015, A non-linear, implicit one-line model to predict long-term shoreline change: in, Wang, P., Rosati, J.D., and Cheng, J., (eds.), The Proceedings of the Coastal Sediments: 2015, World Scientific, 14 p., doi:10.1142/9789814689977_0215.

Projected Hazard: Model-derived ocean current velocities (in meters per second) for the given storm condition and sea-level rise (SLR) scenario. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the model summary and inspect output carefully. Data are complete for the information presented. Details: Model background: The CoSMoS model comprises three tiers. Tier I consists of one Delft3D hydrodynamics FLOW grid for computation of tides, water level variations, flows, and currents and one SWAN grid for computation of wave generation and propagation across the continental shelf. The FLOW and SWAN models are two-way coupled so that tidal currents are accounted for in wave propagation and growth and conversely, so that orbital velocities generated by waves impart changes on tidal currents. The Tier I SWAN and FLOW models consist of identical structured curvilinear grids that extend from far offshore to the shore and range in resolution from 0.5 km in the offshore to 0.2 km in the nearshore. Spatially varying astronomic tidal amplitudes and phases and steric rises in water levels due to large-scale effects (for example, a prolonged rise in sea level) are applied along all open boundaries of the Tier I FLOW grid. Winds (split into eastward and northward components) and sea-level pressure (SLP) fields from CaRD10 (Dr. Dan Cayan, Scripps Institute of Oceanography, San Diego, California, written commun., 2014) that vary in both space and time are applied to all grid cells at each model time-step. Deep-water wave conditions, applied at the open boundaries of the Tier I SWAN model runs, were projected for the 21st century Representative Concentration Pathway (RCP) 4.5 climate scenario (2011-2100) using the WaveWatch III numerical wave model (Tolman and others, 2002) and 3-hourly winds from the GFDL-ESM2M Global Climate Model (GCM). Tier II provides higher resolution near the shore and in areas that require greater resolution of physical processes (such as bays, harbors, and estuaries). A single nested outer grid and multiple two-way coupled domain decomposition (DD) structured grids allow for local grid refinement and higher resolution where needed. Tier II was segmented into 11 sections along the Southern California Bight, to reduce computation time and complete runs within computational limitations. Water-level and Neumann time-series, extracted from Tier I simulations, are applied to the shore-parallel and lateral open boundaries of each Tier II sub-model outer grid respectively. Several of the sub-models proved to be unstable with lateral Neumann boundaries; for those cases one or both of the lateral boundaries were converted to water-level time-series or left unassigned. The open-boundary time-series are extracted from completed Tier I simulations so that there is no communication from Tier II to Tier I. Because this one-way nesting could produce erroneous results near the boundaries of Tier II and because data near any model boundary are always suspect, Tier II sub-model extents were designed to overlap in the along-coast direction. In the landward direction, Tier II DD grids extend to the 10-m topographic contour; exceptions exist where channels (such as the Los Angeles River) or other low-lying regions extend very far inland. Space- and time-varying wind and SLP fields, identical to those used in Tier I simulations, are applied to all Tier II DD grids to allow for wind-setup and local inverse barometer effects (IBE, rise or depression of water levels in response to atmospheric pressure gradients). A total of 42 time-series fluvial discharges are included in the Tier II FLOW domains in an effort to simulate exacerbated flooding caused by backflow at the confluence of high river seaward flows and elevated coastal surge levels migrating inland. Time-varying fluvial discharges are applied either at the closed boundaries or distributed as point sources within the relevant model domains. Wave computations are accomplished with the SWAN model using two grids for each Tier II sub-model: one larger grid covering the same area as the outer FLOW grid and a second finer resolution two-way coupled nearshore nested grid. The nearshore grid extends from approximately 800-1,000 m water depth up to 8-10 m elevations onshore. The landward extension is included to allow for wave computations of the higher SLR scenarios. Time- and space-varying 2D wave spectra extracted from previously completed Tier I simulations are applied approximately every kilometer along the open boundaries of the outer Tier II sub-model SWAN grids. The same space- and time-varying wind fields used in Tier I simulations are also applied to both Tier II SWAN grids to allow for computation of local wave generation. Tier III for the entire Southern California Bight consists of 4,802 cross-shore transects (CST) spaced approximately 100 m apart in the along-shore direction. The profiles extend from the -15 m isobath to at least 10 m above NAVD88. The CSTs are truncated for cases where a lagoon or other waterway exists on the landward end of the profile. Time-varying water levels and wave parameters (significant wave heights, Hs; peak periods, Tp; and peak incident wave directions, Dp), extracted from Tier II grid cells that coincide with the seaward end of the CSTs, are applied at the open boundary of each CST. The XBeach model is run in a hydrostatic (no vertical pressure gradients) mode including event-based morphodynamic change. Wave propagation, two-way wave-current interaction, water-level variations, and wave runup are computed at each transect. XBeach simulations are included in the CoSMoS model to account for infragravity waves that can significantly extend the reach of wave runup (Roelvink and others, 2009) compared to short-wave incident waves. The U.S. west coast is particularly susceptible to infragravity waves at the shore due to breaking of long-period swell waves (Tp > 15). Resulting water levels (WLs) from both Delft3D (high interest bays and marshes) and open-coast XBeach (CSTs) were spatially combined and interpolated to a 10 m grid. These WL elevations are differenced from the originating 2 m digital elevation model (DEM) to determine final flooding extent and depth of flooding. Events: The model system is run for pre-determined scenarios of interest such as the 1-yr or 100-yr storm event in combination with sea-level rise. Storms are first identified from time-series of total water level proxies (TWLpx) at the shore. TWLpx are computed for the majority of the 21st century (2010-2100), assuming a linear super-position of the major processes that contribute to the overall total water level. TWLpx time-series are then evaluated for extreme events, which define the boundary conditions for subsequent modeling with CoSMoS. Multiple 100-yr events are determined (varying Hs, Tp, Dp) and used for multiple model runs to better account for regional and directional flooding affects. Model results are combined and compiled into scenario-specific composites of flood projection. Digital Elevation Model (DEM): Our seamless, topobathymetric digital elevation model (DEM) was based largely upon the Coastal California TopoBathy Merge Project DEM, with some modifications performed by the USGS Earth Resources Observation and Science (EROS) Center to incorporate the most recent, high-resolution topographic and bathymetric datasets available. Topography is derived from bare-earth light detection and ranging (lidar) data collected in 2009-2011 for the CA Coastal Conservancy Lidar Project and bathymetry from 2009-2010 bathymetric lidar as well as acoustic multi- and single-beam data collected primarily between 2001 and 2013. The DEM was constructed to define the shape of nearshore, beach, and cliff surfaces as accurately as possible, utilizing dozens of bathymetric and topographic data sets. These data were used to populate the majority of the Tier I and II grids. To describe and include impacts from long-term shoreline evolution, including cumulative storm activity, seasonal trends, ENSO, and SLR, the DEM was modified for each SLR scenario. Long-term shoreline (Vitousek and Barnard, 2015) and cliff (Limber and others, 2015) erosion projections were efficiently combined along the cross-shore transects to evolve the shore-normal profiles. Elevation changes from the profiles were spatially-merged for a cohesive, 3D depiction of coastal evolution used to modify the DEM. These data are used to generate initial profiles of the 4,802 CSTs used for Phase 2 Tier III XBeach modeling and determining final projected flood depths in each SLR scenario. All data are referenced to NAD83 horizontal datum and NAVD88 vertical datum. Data for Tiers II and III are projected in UTM, zone 11. Outputs include: Projected ocean current velocities for the 100-year storm and 0.0 m sea-level rise scenario. Data correspond to the near-shore region including areas vulnerable to coastal flooding due to storm surge, sea-level anomalies, tide elevation, and wave run-up during the same storm and sea-level rise simulation. References Cited: Howell, S., Smith-Konter, B., Frazer, N., Tong, X., and Sandwell, D., 2016, The vertical fingerprint of earthquake cycle loading in southern California: Nature Geoscience, v. 9, p. 611-614, doi:10.1038/ngeo2741. Limber, P., Barnard, P.L. and Hapke., C., 2015, Towards projecting the retreat of California’s coastal cliffs during the 21st Century: in, Wang, P., Rosati, J.D., and Cheng, J., (eds.), The Proceedings of the Coastal Sediments: 2015, World Scientific, 14 p., doi:10.1142/9789814689977_0245 Roelvink, J.A., Reniers, A., van Dongeren, A.R., van Thiel de Vries, J., McCall, R., and Lescinski, J., 2009, Modeling storm impacts on beaches, dunes and barrier islands: Coastal Engineering, v. 56, p. 1,133–1,152, doi:10.1016/j.coastaleng.2009.08.006. Tolman, H.L., Balasubramaniyan, B., Burroughs, L.D., Chalikov, D.V., Chao, Y.Y., Chen H.S., Gerald, V.M., 2002, Development and implementation of wind generated ocean surface wave models at NCEP: Weather and Forecasting, v. 17, p. 311-333. Vitousek, S. and Barnard, P.L., 2015, A non-linear, implicit one-line model to predict long-term shoreline change: in, Wang, P., Rosati, J.D., and Cheng, J., (eds.), The Proceedings of the Coastal Sediments: 2015, World Scientific, 14 p., doi:10.1142/9789814689977_0215.

Projected Hazard: Model-derived ocean current velocities (in meters per second) for the given storm condition and sea-level rise (SLR) scenario. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the model summary and inspect output carefully. Data are complete for the information presented. Details: Model background: The CoSMoS model comprises three tiers. Tier I consists of one Delft3D hydrodynamics FLOW grid for computation of tides, water level variations, flows, and currents and one SWAN grid for computation of wave generation and propagation across the continental shelf. The FLOW and SWAN models are two-way coupled so that tidal currents are accounted for in wave propagation and growth and conversely, so that orbital velocities generated by waves impart changes on tidal currents. The Tier I SWAN and FLOW models consist of identical structured curvilinear grids that extend from far offshore to the shore and range in resolution from 0.5 km in the offshore to 0.2 km in the nearshore. Spatially varying astronomic tidal amplitudes and phases and steric rises in water levels due to large-scale effects (for example, a prolonged rise in sea level) are applied along all open boundaries of the Tier I FLOW grid. Winds (split into eastward and northward components) and sea-level pressure (SLP) fields from CaRD10 (Dr. Dan Cayan, Scripps Institute of Oceanography, San Diego, California, written commun., 2014) that vary in both space and time are applied to all grid cells at each model time-step. Deep-water wave conditions, applied at the open boundaries of the Tier I SWAN model runs, were projected for the 21st century Representative Concentration Pathway (RCP) 4.5 climate scenario (2011-2100) using the WaveWatch III numerical wave model (Tolman and others, 2002) and 3-hourly winds from the GFDL-ESM2M Global Climate Model (GCM). Tier II provides higher resolution near the shore and in areas that require greater resolution of physical processes (such as bays, harbors, and estuaries). A single nested outer grid and multiple two-way coupled domain decomposition (DD) structured grids allow for local grid refinement and higher resolution where needed. Tier II was segmented into 11 sections along the Southern California Bight, to reduce computation time and complete runs within computational limitations. Water-level and Neumann time-series, extracted from Tier I simulations, are applied to the shore-parallel and lateral open boundaries of each Tier II sub-model outer grid respectively. Several of the sub-models proved to be unstable with lateral Neumann boundaries; for those cases one or both of the lateral boundaries were converted to water-level time-series or left unassigned. The open-boundary time-series are extracted from completed Tier I simulations so that there is no communication from Tier II to Tier I. Because this one-way nesting could produce erroneous results near the boundaries of Tier II and because data near any model boundary are always suspect, Tier II sub-model extents were designed to overlap in the along-coast direction. In the landward direction, Tier II DD grids extend to the 10-m topographic contour; exceptions exist where channels (such as the Los Angeles River) or other low-lying regions extend very far inland. Space- and time-varying wind and SLP fields, identical to those used in Tier I simulations, are applied to all Tier II DD grids to allow for wind-setup and local inverse barometer effects (IBE, rise or depression of water levels in response to atmospheric pressure gradients). A total of 42 time-series fluvial discharges are included in the Tier II FLOW domains in an effort to simulate exacerbated flooding caused by backflow at the confluence of high river seaward flows and elevated coastal surge levels migrating inland. Time-varying fluvial discharges are applied either at the closed boundaries or distributed as point sources within the relevant model domains. Wave computations are accomplished with the SWAN model using two grids for each Tier II sub-model: one larger grid covering the same area as the outer FLOW grid and a second finer resolution two-way coupled nearshore nested grid. The nearshore grid extends from approximately 800-1,000 m water depth up to 8-10 m elevations onshore. The landward extension is included to allow for wave computations of the higher SLR scenarios. Time- and space-varying 2D wave spectra extracted from previously completed Tier I simulations are applied approximately every kilometer along the open boundaries of the outer Tier II sub-model SWAN grids. The same space- and time-varying wind fields used in Tier I simulations are also applied to both Tier II SWAN grids to allow for computation of local wave generation. Tier III for the entire Southern California Bight consists of 4,802 cross-shore transects (CST) spaced approximately 100 m apart in the along-shore direction. The profiles extend from the -15 m isobath to at least 10 m above NAVD88. The CSTs are truncated for cases where a lagoon or other waterway exists on the landward end of the profile. Time-varying water levels and wave parameters (significant wave heights, Hs; peak periods, Tp; and peak incident wave directions, Dp), extracted from Tier II grid cells that coincide with the seaward end of the CSTs, are applied at the open boundary of each CST. The XBeach model is run in a hydrostatic (no vertical pressure gradients) mode including event-based morphodynamic change. Wave propagation, two-way wave-current interaction, water-level variations, and wave runup are computed at each transect. XBeach simulations are included in the CoSMoS model to account for infragravity waves that can significantly extend the reach of wave runup (Roelvink and others, 2009) compared to short-wave incident waves. The U.S. west coast is particularly susceptible to infragravity waves at the shore due to breaking of long-period swell waves (Tp > 15). Resulting water levels (WLs) from both Delft3D (high interest bays and marshes) and open-coast XBeach (CSTs) were spatially combined and interpolated to a 10 m grid. These WL elevations are differenced from the originating 2 m digital elevation model (DEM) to determine final flooding extent and depth of flooding. Events: The model system is run for pre-determined scenarios of interest such as the 1-yr or 100-yr storm event in combination with sea-level rise. Storms are first identified from time-series of total water level proxies (TWLpx) at the shore. TWLpx are computed for the majority of the 21st century (2010-2100), assuming a linear super-position of the major processes that contribute to the overall total water level. TWLpx time-series are then evaluated for extreme events, which define the boundary conditions for subsequent modeling with CoSMoS. Multiple 100-yr events are determined (varying Hs, Tp, Dp) and used for multiple model runs to better account for regional and directional flooding affects. Model results are combined and compiled into scenario-specific composites of flood projection. Digital Elevation Model (DEM): Our seamless, topobathymetric digital elevation model (DEM) was based largely upon the Coastal California TopoBathy Merge Project DEM, with some modifications performed by the USGS Earth Resources Observation and Science (EROS) Center to incorporate the most recent, high-resolution topographic and bathymetric datasets available. Topography is derived from bare-earth light detection and ranging (lidar) data collected in 2009-2011 for the CA Coastal Conservancy Lidar Project and bathymetry from 2009-2010 bathymetric lidar as well as acoustic multi- and single-beam data collected primarily between 2001 and 2013. The DEM was constructed to define the shape of nearshore, beach, and cliff surfaces as accurately as possible, utilizing dozens of bathymetric and topographic data sets. These data were used to populate the majority of the Tier I and II grids. To describe and include impacts from long-term shoreline evolution, including cumulative storm activity, seasonal trends, ENSO, and SLR, the DEM was modified for each SLR scenario. Long-term shoreline (Vitousek and Barnard, 2015) and cliff (Limber and others, 2015) erosion projections were efficiently combined along the cross-shore transects to evolve the shore-normal profiles. Elevation changes from the profiles were spatially-merged for a cohesive, 3D depiction of coastal evolution used to modify the DEM. These data are used to generate initial profiles of the 4,802 CSTs used for Phase 2 Tier III XBeach modeling and determining final projected flood depths in each SLR scenario. All data are referenced to NAD83 horizontal datum and NAVD88 vertical datum. Data for Tiers II and III are projected in UTM, zone 11. Outputs include: Projected ocean current velocities for the 100-year storm and 0.0 m sea-level rise scenario. Data correspond to the near-shore region including areas vulnerable to coastal flooding due to storm surge, sea-level anomalies, tide elevation, and wave run-up during the same storm and sea-level rise simulation. References Cited: Howell, S., Smith-Konter, B., Frazer, N., Tong, X., and Sandwell, D., 2016, The vertical fingerprint of earthquake cycle loading in southern California: Nature Geoscience, v. 9, p. 611-614, doi:10.1038/ngeo2741. Limber, P., Barnard, P.L. and Hapke., C., 2015, Towards projecting the retreat of California’s coastal cliffs during the 21st Century: in, Wang, P., Rosati, J.D., and Cheng, J., (eds.), The Proceedings of the Coastal Sediments: 2015, World Scientific, 14 p., doi:10.1142/9789814689977_0245 Roelvink, J.A., Reniers, A., van Dongeren, A.R., van Thiel de Vries, J., McCall, R., and Lescinski, J., 2009, Modeling storm impacts on beaches, dunes and barrier islands: Coastal Engineering, v. 56, p. 1,133–1,152, doi:10.1016/j.coastaleng.2009.08.006. Tolman, H.L., Balasubramaniyan, B., Burroughs, L.D., Chalikov, D.V., Chao, Y.Y., Chen H.S., Gerald, V.M., 2002, Development and implementation of wind generated ocean surface wave models at NCEP: Weather and Forecasting, v. 17, p. 311-333. Vitousek, S. and Barnard, P.L., 2015, A non-linear, implicit one-line model to predict long-term shoreline change: in, Wang, P., Rosati, J.D., and Cheng, J., (eds.), The Proceedings of the Coastal Sediments: 2015, World Scientific, 14 p., doi:10.1142/9789814689977_0215.

Projected Hazard: Model-derived ocean current velocities (in meters per second) for the given storm condition and sea-level rise (SLR) scenario. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the model summary and inspect output carefully. Data are complete for the information presented. Details: Model background: The CoSMoS model comprises three tiers. Tier I consists of one Delft3D hydrodynamics FLOW grid for computation of tides, water level variations, flows, and currents and one SWAN grid for computation of wave generation and propagation across the continental shelf. The FLOW and SWAN models are two-way coupled so that tidal currents are accounted for in wave propagation and growth and conversely, so that orbital velocities generated by waves impart changes on tidal currents. The Tier I SWAN and FLOW models consist of identical structured curvilinear grids that extend from far offshore to the shore and range in resolution from 0.5 km in the offshore to 0.2 km in the nearshore. Spatially varying astronomic tidal amplitudes and phases and steric rises in water levels due to large-scale effects (for example, a prolonged rise in sea level) are applied along all open boundaries of the Tier I FLOW grid. Winds (split into eastward and northward components) and sea-level pressure (SLP) fields from CaRD10 (Dr. Dan Cayan, Scripps Institute of Oceanography, San Diego, California, written commun., 2014) that vary in both space and time are applied to all grid cells at each model time-step. Deep-water wave conditions, applied at the open boundaries of the Tier I SWAN model runs, were projected for the 21st century Representative Concentration Pathway (RCP) 4.5 climate scenario (2011-2100) using the WaveWatch III numerical wave model (Tolman and others, 2002) and 3-hourly winds from the GFDL-ESM2M Global Climate Model (GCM). Tier II provides higher resolution near the shore and in areas that require greater resolution of physical processes (such as bays, harbors, and estuaries). A single nested outer grid and multiple two-way coupled domain decomposition (DD) structured grids allow for local grid refinement and higher resolution where needed. Tier II was segmented into 11 sections along the Southern California Bight, to reduce computation time and complete runs within computational limitations. Water-level and Neumann time-series, extracted from Tier I simulations, are applied to the shore-parallel and lateral open boundaries of each Tier II sub-model outer grid respectively. Several of the sub-models proved to be unstable with lateral Neumann boundaries; for those cases one or both of the lateral boundaries were converted to water-level time-series or left unassigned. The open-boundary time-series are extracted from completed Tier I simulations so that there is no communication from Tier II to Tier I. Because this one-way nesting could produce erroneous results near the boundaries of Tier II and because data near any model boundary are always suspect, Tier II sub-model extents were designed to overlap in the along-coast direction. In the landward direction, Tier II DD grids extend to the 10-m topographic contour; exceptions exist where channels (such as the Los Angeles River) or other low-lying regions extend very far inland. Space- and time-varying wind and SLP fields, identical to those used in Tier I simulations, are applied to all Tier II DD grids to allow for wind-setup and local inverse barometer effects (IBE, rise or depression of water levels in response to atmospheric pressure gradients). A total of 42 time-series fluvial discharges are included in the Tier II FLOW domains in an effort to simulate exacerbated flooding caused by backflow at the confluence of high river seaward flows and elevated coastal surge levels migrating inland. Time-varying fluvial discharges are applied either at the closed boundaries or distributed as point sources within the relevant model domains. Wave computations are accomplished with the SWAN model using two grids for each Tier II sub-model: one larger grid covering the same area as the outer FLOW grid and a second finer resolution two-way coupled nearshore nested grid. The nearshore grid extends from approximately 800-1,000 m water depth up to 8-10 m elevations onshore. The landward extension is included to allow for wave computations of the higher SLR scenarios. Time- and space-varying 2D wave spectra extracted from previously completed Tier I simulations are applied approximately every kilometer along the open boundaries of the outer Tier II sub-model SWAN grids. The same space- and time-varying wind fields used in Tier I simulations are also applied to both Tier II SWAN grids to allow for computation of local wave generation. Tier III for the entire Southern California Bight consists of 4,802 cross-shore transects (CST) spaced approximately 100 m apart in the along-shore direction. The profiles extend from the -15 m isobath to at least 10 m above NAVD88. The CSTs are truncated for cases where a lagoon or other waterway exists on the landward end of the profile. Time-varying water levels and wave parameters (significant wave heights, Hs; peak periods, Tp; and peak incident wave directions, Dp), extracted from Tier II grid cells that coincide with the seaward end of the CSTs, are applied at the open boundary of each CST. The XBeach model is run in a hydrostatic (no vertical pressure gradients) mode including event-based morphodynamic change. Wave propagation, two-way wave-current interaction, water-level variations, and wave runup are computed at each transect. XBeach simulations are included in the CoSMoS model to account for infragravity waves that can significantly extend the reach of wave runup (Roelvink and others, 2009) compared to short-wave incident waves. The U.S. west coast is particularly susceptible to infragravity waves at the shore due to breaking of long-period swell waves (Tp > 15). Resulting water levels (WLs) from both Delft3D (high interest bays and marshes) and open-coast XBeach (CSTs) were spatially combined and interpolated to a 10 m grid. These WL elevations are differenced from the originating 2 m digital elevation model (DEM) to determine final flooding extent and depth of flooding. Events: The model system is run for pre-determined scenarios of interest such as the 1-yr or 100-yr storm event in combination with sea-level rise. Storms are first identified from time-series of total water level proxies (TWLpx) at the shore. TWLpx are computed for the majority of the 21st century (2010-2100), assuming a linear super-position of the major processes that contribute to the overall total water level. TWLpx time-series are then evaluated for extreme events, which define the boundary conditions for subsequent modeling with CoSMoS. Multiple 100-yr events are determined (varying Hs, Tp, Dp) and used for multiple model runs to better account for regional and directional flooding affects. Model results are combined and compiled into scenario-specific composites of flood projection. Digital Elevation Model (DEM): Our seamless, topobathymetric digital elevation model (DEM) was based largely upon the Coastal California TopoBathy Merge Project DEM, with some modifications performed by the USGS Earth Resources Observation and Science (EROS) Center to incorporate the most recent, high-resolution topographic and bathymetric datasets available. Topography is derived from bare-earth light detection and ranging (lidar) data collected in 2009-2011 for the CA Coastal Conservancy Lidar Project and bathymetry from 2009-2010 bathymetric lidar as well as acoustic multi- and single-beam data collected primarily between 2001 and 2013. The DEM was constructed to define the shape of nearshore, beach, and cliff surfaces as accurately as possible, utilizing dozens of bathymetric and topographic data sets. These data were used to populate the majority of the Tier I and II grids. To describe and include impacts from long-term shoreline evolution, including cumulative storm activity, seasonal trends, ENSO, and SLR, the DEM was modified for each SLR scenario. Long-term shoreline (Vitousek and Barnard, 2015) and cliff (Limber and others, 2015) erosion projections were efficiently combined along the cross-shore transects to evolve the shore-normal profiles. Elevation changes from the profiles were spatially-merged for a cohesive, 3D depiction of coastal evolution used to modify the DEM. These data are used to generate initial profiles of the 4,802 CSTs used for Phase 2 Tier III XBeach modeling and determining final projected flood depths in each SLR scenario. All data are referenced to NAD83 horizontal datum and NAVD88 vertical datum. Data for Tiers II and III are projected in UTM, zone 11. Outputs include: Projected ocean current velocities for the 100-year storm and 0.0 m sea-level rise scenario. Data correspond to the near-shore region including areas vulnerable to coastal flooding due to storm surge, sea-level anomalies, tide elevation, and wave run-up during the same storm and sea-level rise simulation. References Cited: Howell, S., Smith-Konter, B., Frazer, N., Tong, X., and Sandwell, D., 2016, The vertical fingerprint of earthquake cycle loading in southern California: Nature Geoscience, v. 9, p. 611-614, doi:10.1038/ngeo2741. Limber, P., Barnard, P.L. and Hapke., C., 2015, Towards projecting the retreat of California’s coastal cliffs during the 21st Century: in, Wang, P., Rosati, J.D., and Cheng, J., (eds.), The Proceedings of the Coastal Sediments: 2015, World Scientific, 14 p., doi:10.1142/9789814689977_0245 Roelvink, J.A., Reniers, A., van Dongeren, A.R., van Thiel de Vries, J., McCall, R., and Lescinski, J., 2009, Modeling storm impacts on beaches, dunes and barrier islands: Coastal Engineering, v. 56, p. 1,133–1,152, doi:10.1016/j.coastaleng.2009.08.006. Tolman, H.L., Balasubramaniyan, B., Burroughs, L.D., Chalikov, D.V., Chao, Y.Y., Chen H.S., Gerald, V.M., 2002, Development and implementation of wind generated ocean surface wave models at NCEP: Weather and Forecasting, v. 17, p. 311-333. Vitousek, S. and Barnard, P.L., 2015, A non-linear, implicit one-line model to predict long-term shoreline change: in, Wang, P., Rosati, J.D., and Cheng, J., (eds.), The Proceedings of the Coastal Sediments: 2015, World Scientific, 14 p., doi:10.1142/9789814689977_0215.

Projected Hazard: Model-derived water levels (in meters) for the given storm condition and sea-level rise (SLR) scenario. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the model summary and inspect output carefully. Data are complete for the information presented. Details: Model background: The CoSMoS model comprises three tiers. Tier I consists of one Delft3D hydrodynamics FLOW grid for computation of tides, water level variations, flows, and currents and one SWAN grid for computation of wave generation and propagation across the continental shelf. The FLOW and SWAN models are two-way coupled so that tidal currents are accounted for in wave propagation and growth and conversely, so that orbital velocities generated by waves impart changes on tidal currents. The Tier I SWAN and FLOW models consist of identical structured curvilinear grids that extend from far offshore to the shore and range in resolution from 0.5 km in the offshore to 0.2 km in the nearshore. Spatially varying astronomic tidal amplitudes and phases and steric rises in water levels due to large-scale effects (for example, a prolonged rise in sea level) are applied along all open boundaries of the Tier I FLOW grid. Winds (split into eastward and northward components) and sea-level pressure (SLP) fields from CaRD10 (Dr. Dan Cayan, Scripps Institute of Oceanography, San Diego, California, written commun., 2014) that vary in both space and time are applied to all grid cells at each model time-step. Deep-water wave conditions, applied at the open boundaries of the Tier I SWAN model runs, were projected for the 21st century Representative Concentration Pathway (RCP) 4.5 climate scenario (2011-2100) using the WaveWatch III numerical wave model (Tolman and others, 2002) and 3-hourly winds from the GFDL-ESM2M Global Climate Model (GCM). Tier II provides higher resolution near the shore and in areas that require greater resolution of physical processes (such as bays, harbors, and estuaries). A single nested outer grid and multiple two-way coupled domain decomposition (DD) structured grids allow for local grid refinement and higher resolution where needed. Tier II was segmented into 11 sections along the Southern California Bight, to reduce computation time and complete runs within computational limitations. Water-level and Neumann time-series, extracted from Tier I simulations, are applied to the shore-parallel and lateral open boundaries of each Tier II sub-model outer grid respectively. Several of the sub-models proved to be unstable with lateral Neumann boundaries; for those cases one or both of the lateral boundaries were converted to water-level time-series or left unassigned. The open-boundary time-series are extracted from completed Tier I simulations so that there is no communication from Tier II to Tier I. Because this one-way nesting could produce erroneous results near the boundaries of Tier II and because data near any model boundary are always suspect, Tier II sub-model extents were designed to overlap in the along-coast direction. In the landward direction, Tier II DD grids extend to the 10-m topographic contour; exceptions exist where channels (such as the Los Angeles River) or other low-lying regions extend very far inland. Space- and time-varying wind and SLP fields, identical to those used in Tier I simulations, are applied to all Tier II DD grids to allow for wind-setup and local inverse barometer effects (IBE, rise or depression of water levels in response to atmospheric pressure gradients). A total of 42 time-series fluvial discharges are included in the Tier II FLOW domains in an effort to simulate exacerbated flooding caused by backflow at the confluence of high river seaward flows and elevated coastal surge levels migrating inland. Time-varying fluvial discharges are applied either at the closed boundaries or distributed as point sources within the relevant model domains. Wave computations are accomplished with the SWAN model using two grids for each Tier II sub-model: one larger grid covering the same area as the outer FLOW grid and a second finer resolution two-way coupled nearshore nested grid. The nearshore grid extends from approximately 800-1,000 m water depth up to 8-10 m elevations onshore. The landward extension is included to allow for wave computations of the higher SLR scenarios. Time- and space-varying 2D wave spectra extracted from previously completed Tier I simulations are applied approximately every kilometer along the open boundaries of the outer Tier II sub-model SWAN grids. The same space- and time-varying wind fields used in Tier I simulations are also applied to both Tier II SWAN grids to allow for computation of local wave generation. Tier III for the entire Southern California Bight consists of 4,802 cross-shore transects (CST) spaced approximately 100 m apart in the along-shore direction. The profiles extend from the -15 m isobath to at least 10 m above NAVD88. The CSTs are truncated for cases where a lagoon or other waterway exists on the landward end of the profile. Time-varying water levels and wave parameters (significant wave heights, Hs; peak periods, Tp; and peak incident wave directions, Dp), extracted from Tier II grid cells that coincide with the seaward end of the CSTs, are applied at the open boundary of each CST. The XBeach model is run in a hydrostatic (no vertical pressure gradients) mode including event-based morphodynamic change. Wave propagation, two-way wave-current interaction, water-level variations, and wave runup are computed at each transect. XBeach simulations are included in the CoSMoS model to account for infragravity waves that can significantly extend the reach of wave runup (Roelvink and others, 2009) compared to short-wave incident waves. The U.S. west coast is particularly susceptible to infragravity waves at the shore due to breaking of long-period swell waves (Tp > 15). Resulting water levels (WLs) from both Delft3D (high interest bays and marshes) and open-coast XBeach (CSTs) were spatially combined and interpolated to a 10 m grid. These WL elevations are differenced from the originating 2 m digital elevation model (DEM) to determine final flooding extent and depth of flooding. Events: The model system is run for pre-determined scenarios of interest such as the 1-yr or 100-yr storm event in combination with sea-level rise. Storms are first identified from time-series of total water level proxies (TWLpx) at the shore. TWLpx are computed for the majority of the 21st century (2010-2100), assuming a linear super-position of the major processes that contribute to the overall total water level. TWLpx time-series are then evaluated for extreme events, which define the boundary conditions for subsequent modeling with CoSMoS. Multiple 100-yr events are determined (varying Hs, Tp, Dp) and used for multiple model runs to better account for regional and directional flooding affects. Model results are combined and compiled into scenario-specific composites of flood projection. Digital Elevation Model (DEM): Our seamless, topobathymetric digital elevation model (DEM) was based largely upon the Coastal California TopoBathy Merge Project DEM, with some modifications performed by the USGS Earth Resources Observation and Science (EROS) Center to incorporate the most recent, high-resolution topographic and bathymetric datasets available. Topography is derived from bare-earth light detection and ranging (lidar) data collected in 2009-2011 for the CA Coastal Conservancy Lidar Project and bathymetry from 2009-2010 bathymetric lidar as well as acoustic multi- and single-beam data collected primarily between 2001 and 2013. The DEM was constructed to define the shape of nearshore, beach, and cliff surfaces as accurately as possible, utilizing dozens of bathymetric and topographic data sets. These data were used to populate the majority of the Tier I and II grids. To describe and include impacts from long-term shoreline evolution, including cumulative storm activity, seasonal trends, ENSO, and SLR, the DEM was modified for each SLR scenario. Long-term shoreline (Vitousek and Barnard, 2015) and cliff (Limber and others, 2015) erosion projections were efficiently combined along the cross-shore transects to evolve the shore-normal profiles. Elevation changes from the profiles were spatially-merged for a cohesive, 3D depiction of coastal evolution used to modify the DEM. These data are used to generate initial profiles of the 4,802 CSTs used for Phase 2 Tier III XBeach modeling and determining final projected flood depths in each SLR scenario. All data are referenced to NAD83 horizontal datum and NAVD88 vertical datum. Data for Tiers II and III are projected in UTM, zone 11. Outputs include: Projected water levels for the storm and sea-level rise scenario indicated. Data correspond to the near-shore region including areas vulnerable to coastal flooding due to storm surge, sea-level anomalies, tide elevation, and wave run-up during the same storm and sea-level rise simulation. References Cited: Howell, S., Smith-Konter, B., Frazer, N., Tong, X., and Sandwell, D., 2016, The vertical fingerprint of earthquake cycle loading in southern California: Nature Geoscience, v. 9, p. 611-614, doi:10.1038/ngeo2741. Limber, P., Barnard, P.L. and Hapke., C., 2015, Towards projecting the retreat of California’s coastal cliffs during the 21st Century: in, Wang, P., Rosati, J.D., and Cheng, J., (eds.), The Proceedings of the Coastal Sediments: 2015, World Scientific, 14 p., doi:10.1142/9789814689977_0245 Roelvink, J.A., Reniers, A., van Dongeren, A.R., van Thiel de Vries, J., McCall, R., and Lescinski, J., 2009, Modeling storm impacts on beaches, dunes and barrier islands: Coastal Engineering, v. 56, p. 1,133–1,152, doi:10.1016/j.coastaleng.2009.08.006. Tolman, H.L., Balasubramaniyan, B., Burroughs, L.D., Chalikov, D.V., Chao, Y.Y., Chen H.S., Gerald, V.M., 2002, Development and implementation of wind generated ocean surface wave models at NCEP: Weather and Forecasting, v. 17, p. 311-333. Vitousek, S. and Barnard, P.L., 2015, A non-linear, implicit one-line model to predict long-term shoreline change: in, Wang, P., Rosati, J.D., and Cheng, J., (eds.), The Proceedings of the Coastal Sediments: 2015, World Scientific, 14 p., doi:10.1142/9789814689977_0215.

Projected Hazard: Model-derived water levels (in meters) for the given storm condition and sea-level rise (SLR) scenario. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the model summary and inspect output carefully. Data are complete for the information presented. Details: Model background: The CoSMoS model comprises three tiers. Tier I consists of one Delft3D hydrodynamics FLOW grid for computation of tides, water level variations, flows, and currents and one SWAN grid for computation of wave generation and propagation across the continental shelf. The FLOW and SWAN models are two-way coupled so that tidal currents are accounted for in wave propagation and growth and conversely, so that orbital velocities generated by waves impart changes on tidal currents. The Tier I SWAN and FLOW models consist of identical structured curvilinear grids that extend from far offshore to the shore and range in resolution from 0.5 km in the offshore to 0.2 km in the nearshore. Spatially varying astronomic tidal amplitudes and phases and steric rises in water levels due to large-scale effects (for example, a prolonged rise in sea level) are applied along all open boundaries of the Tier I FLOW grid. Winds (split into eastward and northward components) and sea-level pressure (SLP) fields from CaRD10 (Dr. Dan Cayan, Scripps Institute of Oceanography, San Diego, California, written commun., 2014) that vary in both space and time are applied to all grid cells at each model time-step. Deep-water wave conditions, applied at the open boundaries of the Tier I SWAN model runs, were projected for the 21st century Representative Concentration Pathway (RCP) 4.5 climate scenario (2011-2100) using the WaveWatch III numerical wave model (Tolman and others, 2002) and 3-hourly winds from the GFDL-ESM2M Global Climate Model (GCM). Tier II provides higher resolution near the shore and in areas that require greater resolution of physical processes (such as bays, harbors, and estuaries). A single nested outer grid and multiple two-way coupled domain decomposition (DD) structured grids allow for local grid refinement and higher resolution where needed. Tier II was segmented into 11 sections along the Southern California Bight, to reduce computation time and complete runs within computational limitations. Water-level and Neumann time-series, extracted from Tier I simulations, are applied to the shore-parallel and lateral open boundaries of each Tier II sub-model outer grid respectively. Several of the sub-models proved to be unstable with lateral Neumann boundaries; for those cases one or both of the lateral boundaries were converted to water-level time-series or left unassigned. The open-boundary time-series are extracted from completed Tier I simulations so that there is no communication from Tier II to Tier I. Because this one-way nesting could produce erroneous results near the boundaries of Tier II and because data near any model boundary are always suspect, Tier II sub-model extents were designed to overlap in the along-coast direction. In the landward direction, Tier II DD grids extend to the 10-m topographic contour; exceptions exist where channels (such as the Los Angeles River) or other low-lying regions extend very far inland. Space- and time-varying wind and SLP fields, identical to those used in Tier I simulations, are applied to all Tier II DD grids to allow for wind-setup and local inverse barometer effects (IBE, rise or depression of water levels in response to atmospheric pressure gradients). A total of 42 time-series fluvial discharges are included in the Tier II FLOW domains in an effort to simulate exacerbated flooding caused by backflow at the confluence of high river seaward flows and elevated coastal surge levels migrating inland. Time-varying fluvial discharges are applied either at the closed boundaries or distributed as point sources within the relevant model domains. Wave computations are accomplished with the SWAN model using two grids for each Tier II sub-model: one larger grid covering the same area as the outer FLOW grid and a second finer resolution two-way coupled nearshore nested grid. The nearshore grid extends from approximately 800-1,000 m water depth up to 8-10 m elevations onshore. The landward extension is included to allow for wave computations of the higher SLR scenarios. Time- and space-varying 2D wave spectra extracted from previously completed Tier I simulations are applied approximately every kilometer along the open boundaries of the outer Tier II sub-model SWAN grids. The same space- and time-varying wind fields used in Tier I simulations are also applied to both Tier II SWAN grids to allow for computation of local wave generation. Tier III for the entire Southern California Bight consists of 4,802 cross-shore transects (CST) spaced approximately 100 m apart in the along-shore direction. The profiles extend from the -15 m isobath to at least 10 m above NAVD88. The CSTs are truncated for cases where a lagoon or other waterway exists on the landward end of the profile. Time-varying water levels and wave parameters (significant wave heights, Hs; peak periods, Tp; and peak incident wave directions, Dp), extracted from Tier II grid cells that coincide with the seaward end of the CSTs, are applied at the open boundary of each CST. The XBeach model is run in a hydrostatic (no vertical pressure gradients) mode including event-based morphodynamic change. Wave propagation, two-way wave-current interaction, water-level variations, and wave runup are computed at each transect. XBeach simulations are included in the CoSMoS model to account for infragravity waves that can significantly extend the reach of wave runup (Roelvink and others, 2009) compared to short-wave incident waves. The U.S. west coast is particularly susceptible to infragravity waves at the shore due to breaking of long-period swell waves (Tp > 15). Resulting water levels (WLs) from both Delft3D (high interest bays and marshes) and open-coast XBeach (CSTs) were spatially combined and interpolated to a 10 m grid. These WL elevations are differenced from the originating 2 m digital elevation model (DEM) to determine final flooding extent and depth of flooding. Events: The model system is run for pre-determined scenarios of interest such as the 1-yr or 100-yr storm event in combination with sea-level rise. Storms are first identified from time-series of total water level proxies (TWLpx) at the shore. TWLpx are computed for the majority of the 21st century (2010-2100), assuming a linear super-position of the major processes that contribute to the overall total water level. TWLpx time-series are then evaluated for extreme events, which define the boundary conditions for subsequent modeling with CoSMoS. Multiple 100-yr events are determined (varying Hs, Tp, Dp) and used for multiple model runs to better account for regional and directional flooding affects. Model results are combined and compiled into scenario-specific composites of flood projection. Digital Elevation Model (DEM): Our seamless, topobathymetric digital elevation model (DEM) was based largely upon the Coastal California TopoBathy Merge Project DEM, with some modifications performed by the USGS Earth Resources Observation and Science (EROS) Center to incorporate the most recent, high-resolution topographic and bathymetric datasets available. Topography is derived from bare-earth light detection and ranging (lidar) data collected in 2009-2011 for the CA Coastal Conservancy Lidar Project and bathymetry from 2009-2010 bathymetric lidar as well as acoustic multi- and single-beam data collected primarily between 2001 and 2013. The DEM was constructed to define the shape of nearshore, beach, and cliff surfaces as accurately as possible, utilizing dozens of bathymetric and topographic data sets. These data were used to populate the majority of the Tier I and II grids. To describe and include impacts from long-term shoreline evolution, including cumulative storm activity, seasonal trends, ENSO, and SLR, the DEM was modified for each SLR scenario. Long-term shoreline (Vitousek and Barnard, 2015) and cliff (Limber and others, 2015) erosion projections were efficiently combined along the cross-shore transects to evolve the shore-normal profiles. Elevation changes from the profiles were spatially-merged for a cohesive, 3D depiction of coastal evolution used to modify the DEM. These data are used to generate initial profiles of the 4,802 CSTs used for Phase 2 Tier III XBeach modeling and determining final projected flood depths in each SLR scenario. All data are referenced to NAD83 horizontal datum and NAVD88 vertical datum. Data for Tiers II and III are projected in UTM, zone 11. Outputs include: Projected water levels for the storm and sea-level rise scenario indicated. Data correspond to the near-shore region including areas vulnerable to coastal flooding due to storm surge, sea-level anomalies, tide elevation, and wave run-up during the same storm and sea-level rise simulation. References Cited: Howell, S., Smith-Konter, B., Frazer, N., Tong, X., and Sandwell, D., 2016, The vertical fingerprint of earthquake cycle loading in southern California: Nature Geoscience, v. 9, p. 611-614, doi:10.1038/ngeo2741. Limber, P., Barnard, P.L. and Hapke., C., 2015, Towards projecting the retreat of California’s coastal cliffs during the 21st Century: in, Wang, P., Rosati, J.D., and Cheng, J., (eds.), The Proceedings of the Coastal Sediments: 2015, World Scientific, 14 p., doi:10.1142/9789814689977_0245 Roelvink, J.A., Reniers, A., van Dongeren, A.R., van Thiel de Vries, J., McCall, R., and Lescinski, J., 2009, Modeling storm impacts on beaches, dunes and barrier islands: Coastal Engineering, v. 56, p. 1,133–1,152, doi:10.1016/j.coastaleng.2009.08.006. Tolman, H.L., Balasubramaniyan, B., Burroughs, L.D., Chalikov, D.V., Chao, Y.Y., Chen H.S., Gerald, V.M., 2002, Development and implementation of wind generated ocean surface wave models at NCEP: Weather and Forecasting, v. 17, p. 311-333. Vitousek, S. and Barnard, P.L., 2015, A non-linear, implicit one-line model to predict long-term shoreline change: in, Wang, P., Rosati, J.D., and Cheng, J., (eds.), The Proceedings of the Coastal Sediments: 2015, World Scientific, 14 p., doi:10.1142/9789814689977_0215.

Projected Hazard: Model-derived water levels (in meters) for the given storm condition and sea-level rise (SLR) scenario. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the model summary and inspect output carefully. Data are complete for the information presented. Details: Model background: The CoSMoS model comprises three tiers. Tier I consists of one Delft3D hydrodynamics FLOW grid for computation of tides, water level variations, flows, and currents and one SWAN grid for computation of wave generation and propagation across the continental shelf. The FLOW and SWAN models are two-way coupled so that tidal currents are accounted for in wave propagation and growth and conversely, so that orbital velocities generated by waves impart changes on tidal currents. The Tier I SWAN and FLOW models consist of identical structured curvilinear grids that extend from far offshore to the shore and range in resolution from 0.5 km in the offshore to 0.2 km in the nearshore. Spatially varying astronomic tidal amplitudes and phases and steric rises in water levels due to large-scale effects (for example, a prolonged rise in sea level) are applied along all open boundaries of the Tier I FLOW grid. Winds (split into eastward and northward components) and sea-level pressure (SLP) fields from CaRD10 (Dr. Dan Cayan, Scripps Institute of Oceanography, San Diego, California, written commun., 2014) that vary in both space and time are applied to all grid cells at each model time-step. Deep-water wave conditions, applied at the open boundaries of the Tier I SWAN model runs, were projected for the 21st century Representative Concentration Pathway (RCP) 4.5 climate scenario (2011-2100) using the WaveWatch III numerical wave model (Tolman and others, 2002) and 3-hourly winds from the GFDL-ESM2M Global Climate Model (GCM). Tier II provides higher resolution near the shore and in areas that require greater resolution of physical processes (such as bays, harbors, and estuaries). A single nested outer grid and multiple two-way coupled domain decomposition (DD) structured grids allow for local grid refinement and higher resolution where needed. Tier II was segmented into 11 sections along the Southern California Bight, to reduce computation time and complete runs within computational limitations. Water-level and Neumann time-series, extracted from Tier I simulations, are applied to the shore-parallel and lateral open boundaries of each Tier II sub-model outer grid respectively. Several of the sub-models proved to be unstable with lateral Neumann boundaries; for those cases one or both of the lateral boundaries were converted to water-level time-series or left unassigned. The open-boundary time-series are extracted from completed Tier I simulations so that there is no communication from Tier II to Tier I. Because this one-way nesting could produce erroneous results near the boundaries of Tier II and because data near any model boundary are always suspect, Tier II sub-model extents were designed to overlap in the along-coast direction. In the landward direction, Tier II DD grids extend to the 10-m topographic contour; exceptions exist where channels (such as the Los Angeles River) or other low-lying regions extend very far inland. Space- and time-varying wind and SLP fields, identical to those used in Tier I simulations, are applied to all Tier II DD grids to allow for wind-setup and local inverse barometer effects (IBE, rise or depression of water levels in response to atmospheric pressure gradients). A total of 42 time-series fluvial discharges are included in the Tier II FLOW domains in an effort to simulate exacerbated flooding caused by backflow at the confluence of high river seaward flows and elevated coastal surge levels migrating inland. Time-varying fluvial discharges are applied either at the closed boundaries or distributed as point sources within the relevant model domains. Wave computations are accomplished with the SWAN model using two grids for each Tier II sub-model: one larger grid covering the same area as the outer FLOW grid and a second finer resolution two-way coupled nearshore nested grid. The nearshore grid extends from approximately 800-1,000 m water depth up to 8-10 m elevations onshore. The landward extension is included to allow for wave computations of the higher SLR scenarios. Time- and space-varying 2D wave spectra extracted from previously completed Tier I simulations are applied approximately every kilometer along the open boundaries of the outer Tier II sub-model SWAN grids. The same space- and time-varying wind fields used in Tier I simulations are also applied to both Tier II SWAN grids to allow for computation of local wave generation. Tier III for the entire Southern California Bight consists of 4,802 cross-shore transects (CST) spaced approximately 100 m apart in the along-shore direction. The profiles extend from the -15 m isobath to at least 10 m above NAVD88. The CSTs are truncated for cases where a lagoon or other waterway exists on the landward end of the profile. Time-varying water levels and wave parameters (significant wave heights, Hs; peak periods, Tp; and peak incident wave directions, Dp), extracted from Tier II grid cells that coincide with the seaward end of the CSTs, are applied at the open boundary of each CST. The XBeach model is run in a hydrostatic (no vertical pressure gradients) mode including event-based morphodynamic change. Wave propagation, two-way wave-current interaction, water-level variations, and wave runup are computed at each transect. XBeach simulations are included in the CoSMoS model to account for infragravity waves that can significantly extend the reach of wave runup (Roelvink and others, 2009) compared to short-wave incident waves. The U.S. west coast is particularly susceptible to infragravity waves at the shore due to breaking of long-period swell waves (Tp > 15). Resulting water levels (WLs) from both Delft3D (high interest bays and marshes) and open-coast XBeach (CSTs) were spatially combined and interpolated to a 10 m grid. These WL elevations are differenced from the originating 2 m digital elevation model (DEM) to determine final flooding extent and depth of flooding. Events: The model system is run for pre-determined scenarios of interest such as the 1-yr or 100-yr storm event in combination with sea-level rise. Storms are first identified from time-series of total water level proxies (TWLpx) at the shore. TWLpx are computed for the majority of the 21st century (2010-2100), assuming a linear super-position of the major processes that contribute to the overall total water level. TWLpx time-series are then evaluated for extreme events, which define the boundary conditions for subsequent modeling with CoSMoS. Multiple 100-yr events are determined (varying Hs, Tp, Dp) and used for multiple model runs to better account for regional and directional flooding affects. Model results are combined and compiled into scenario-specific composites of flood projection. Digital Elevation Model (DEM): Our seamless, topobathymetric digital elevation model (DEM) was based largely upon the Coastal California TopoBathy Merge Project DEM, with some modifications performed by the USGS Earth Resources Observation and Science (EROS) Center to incorporate the most recent, high-resolution topographic and bathymetric datasets available. Topography is derived from bare-earth light detection and ranging (lidar) data collected in 2009-2011 for the CA Coastal Conservancy Lidar Project and bathymetry from 2009-2010 bathymetric lidar as well as acoustic multi- and single-beam data collected primarily between 2001 and 2013. The DEM was constructed to define the shape of nearshore, beach, and cliff surfaces as accurately as possible, utilizing dozens of bathymetric and topographic data sets. These data were used to populate the majority of the Tier I and II grids. To describe and include impacts from long-term shoreline evolution, including cumulative storm activity, seasonal trends, ENSO, and SLR, the DEM was modified for each SLR scenario. Long-term shoreline (Vitousek and Barnard, 2015) and cliff (Limber and others, 2015) erosion projections were efficiently combined along the cross-shore transects to evolve the shore-normal profiles. Elevation changes from the profiles were spatially-merged for a cohesive, 3D depiction of coastal evolution used to modify the DEM. These data are used to generate initial profiles of the 4,802 CSTs used for Phase 2 Tier III XBeach modeling and determining final projected flood depths in each SLR scenario. All data are referenced to NAD83 horizontal datum and NAVD88 vertical datum. Data for Tiers II and III are projected in UTM, zone 11. Outputs include: Projected water levels for the storm and sea-level rise scenario indicated. Data correspond to the near-shore region including areas vulnerable to coastal flooding due to storm surge, sea-level anomalies, tide elevation, and wave run-up during the same storm and sea-level rise simulation. References Cited: Howell, S., Smith-Konter, B., Frazer, N., Tong, X., and Sandwell, D., 2016, The vertical fingerprint of earthquake cycle loading in southern California: Nature Geoscience, v. 9, p. 611-614, doi:10.1038/ngeo2741. Limber, P., Barnard, P.L. and Hapke., C., 2015, Towards projecting the retreat of California’s coastal cliffs during the 21st Century: in, Wang, P., Rosati, J.D., and Cheng, J., (eds.), The Proceedings of the Coastal Sediments: 2015, World Scientific, 14 p., doi:10.1142/9789814689977_0245 Roelvink, J.A., Reniers, A., van Dongeren, A.R., van Thiel de Vries, J., McCall, R., and Lescinski, J., 2009, Modeling storm impacts on beaches, dunes and barrier islands: Coastal Engineering, v. 56, p. 1,133–1,152, doi:10.1016/j.coastaleng.2009.08.006. Tolman, H.L., Balasubramaniyan, B., Burroughs, L.D., Chalikov, D.V., Chao, Y.Y., Chen H.S., Gerald, V.M., 2002, Development and implementation of wind generated ocean surface wave models at NCEP: Weather and Forecasting, v. 17, p. 311-333. Vitousek, S. and Barnard, P.L., 2015, A non-linear, implicit one-line model to predict long-term shoreline change: in, Wang, P., Rosati, J.D., and Cheng, J., (eds.), The Proceedings of the Coastal Sediments: 2015, World Scientific, 14 p., doi:10.1142/9789814689977_0215.

Projected Hazard: Model-derived water levels (in meters) for the given storm condition and sea-level rise (SLR) scenario. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the model summary and inspect output carefully. Data are complete for the information presented. Details: Model background: The CoSMoS model comprises three tiers. Tier I consists of one Delft3D hydrodynamics FLOW grid for computation of tides, water level variations, flows, and currents and one SWAN grid for computation of wave generation and propagation across the continental shelf. The FLOW and SWAN models are two-way coupled so that tidal currents are accounted for in wave propagation and growth and conversely, so that orbital velocities generated by waves impart changes on tidal currents. The Tier I SWAN and FLOW models consist of identical structured curvilinear grids that extend from far offshore to the shore and range in resolution from 0.5 km in the offshore to 0.2 km in the nearshore. Spatially varying astronomic tidal amplitudes and phases and steric rises in water levels due to large-scale effects (for example, a prolonged rise in sea level) are applied along all open boundaries of the Tier I FLOW grid. Winds (split into eastward and northward components) and sea-level pressure (SLP) fields from CaRD10 (Dr. Dan Cayan, Scripps Institute of Oceanography, San Diego, California, written commun., 2014) that vary in both space and time are applied to all grid cells at each model time-step. Deep-water wave conditions, applied at the open boundaries of the Tier I SWAN model runs, were projected for the 21st century Representative Concentration Pathway (RCP) 4.5 climate scenario (2011-2100) using the WaveWatch III numerical wave model (Tolman and others, 2002) and 3-hourly winds from the GFDL-ESM2M Global Climate Model (GCM). Tier II provides higher resolution near the shore and in areas that require greater resolution of physical processes (such as bays, harbors, and estuaries). A single nested outer grid and multiple two-way coupled domain decomposition (DD) structured grids allow for local grid refinement and higher resolution where needed. Tier II was segmented into 11 sections along the Southern California Bight, to reduce computation time and complete runs within computational limitations. Water-level and Neumann time-series, extracted from Tier I simulations, are applied to the shore-parallel and lateral open boundaries of each Tier II sub-model outer grid respectively. Several of the sub-models proved to be unstable with lateral Neumann boundaries; for those cases one or both of the lateral boundaries were converted to water-level time-series or left unassigned. The open-boundary time-series are extracted from completed Tier I simulations so that there is no communication from Tier II to Tier I. Because this one-way nesting could produce erroneous results near the boundaries of Tier II and because data near any model boundary are always suspect, Tier II sub-model extents were designed to overlap in the along-coast direction. In the landward direction, Tier II DD grids extend to the 10-m topographic contour; exceptions exist where channels (such as the Los Angeles River) or other low-lying regions extend very far inland. Space- and time-varying wind and SLP fields, identical to those used in Tier I simulations, are applied to all Tier II DD grids to allow for wind-setup and local inverse barometer effects (IBE, rise or depression of water levels in response to atmospheric pressure gradients). A total of 42 time-series fluvial discharges are included in the Tier II FLOW domains in an effort to simulate exacerbated flooding caused by backflow at the confluence of high river seaward flows and elevated coastal surge levels migrating inland. Time-varying fluvial discharges are applied either at the closed boundaries or distributed as point sources within the relevant model domains. Wave computations are accomplished with the SWAN model using two grids for each Tier II sub-model: one larger grid covering the same area as the outer FLOW grid and a second finer resolution two-way coupled nearshore nested grid. The nearshore grid extends from approximately 800-1,000 m water depth up to 8-10 m elevations onshore. The landward extension is included to allow for wave computations of the higher SLR scenarios. Time- and space-varying 2D wave spectra extracted from previously completed Tier I simulations are applied approximately every kilometer along the open boundaries of the outer Tier II sub-model SWAN grids. The same space- and time-varying wind fields used in Tier I simulations are also applied to both Tier II SWAN grids to allow for computation of local wave generation. Tier III for the entire Southern California Bight consists of 4,802 cross-shore transects (CST) spaced approximately 100 m apart in the along-shore direction. The profiles extend from the -15 m isobath to at least 10 m above NAVD88. The CSTs are truncated for cases where a lagoon or other waterway exists on the landward end of the profile. Time-varying water levels and wave parameters (significant wave heights, Hs; peak periods, Tp; and peak incident wave directions, Dp), extracted from Tier II grid cells that coincide with the seaward end of the CSTs, are applied at the open boundary of each CST. The XBeach model is run in a hydrostatic (no vertical pressure gradients) mode including event-based morphodynamic change. Wave propagation, two-way wave-current interaction, water-level variations, and wave runup are computed at each transect. XBeach simulations are included in the CoSMoS model to account for infragravity waves that can significantly extend the reach of wave runup (Roelvink and others, 2009) compared to short-wave incident waves. The U.S. west coast is particularly susceptible to infragravity waves at the shore due to breaking of long-period swell waves (Tp > 15). Resulting water levels (WLs) from both Delft3D (high interest bays and marshes) and open-coast XBeach (CSTs) were spatially combined and interpolated to a 10 m grid. These WL elevations are differenced from the originating 2 m digital elevation model (DEM) to determine final flooding extent and depth of flooding. Events: The model system is run for pre-determined scenarios of interest such as the 1-yr or 100-yr storm event in combination with sea-level rise. Storms are first identified from time-series of total water level proxies (TWLpx) at the shore. TWLpx are computed for the majority of the 21st century (2010-2100), assuming a linear super-position of the major processes that contribute to the overall total water level. TWLpx time-series are then evaluated for extreme events, which define the boundary conditions for subsequent modeling with CoSMoS. Multiple 100-yr events are determined (varying Hs, Tp, Dp) and used for multiple model runs to better account for regional and directional flooding affects. Model results are combined and compiled into scenario-specific composites of flood projection. Digital Elevation Model (DEM): Our seamless, topobathymetric digital elevation model (DEM) was based largely upon the Coastal California TopoBathy Merge Project DEM, with some modifications performed by the USGS Earth Resources Observation and Science (EROS) Center to incorporate the most recent, high-resolution topographic and bathymetric datasets available. Topography is derived from bare-earth light detection and ranging (lidar) data collected in 2009-2011 for the CA Coastal Conservancy Lidar Project and bathymetry from 2009-2010 bathymetric lidar as well as acoustic multi- and single-beam data collected primarily between 2001 and 2013. The DEM was constructed to define the shape of nearshore, beach, and cliff surfaces as accurately as possible, utilizing dozens of bathymetric and topographic data sets. These data were used to populate the majority of the Tier I and II grids. To describe and include impacts from long-term shoreline evolution, including cumulative storm activity, seasonal trends, ENSO, and SLR, the DEM was modified for each SLR scenario. Long-term shoreline (Vitousek and Barnard, 2015) and cliff (Limber and others, 2015) erosion projections were efficiently combined along the cross-shore transects to evolve the shore-normal profiles. Elevation changes from the profiles were spatially-merged for a cohesive, 3D depiction of coastal evolution used to modify the DEM. These data are used to generate initial profiles of the 4,802 CSTs used for Phase 2 Tier III XBeach modeling and determining final projected flood depths in each SLR scenario. All data are referenced to NAD83 horizontal datum and NAVD88 vertical datum. Data for Tiers II and III are projected in UTM, zone 11. Outputs include: Projected water levels for the storm and sea-level rise scenario indicated. Data correspond to the near-shore region including areas vulnerable to coastal flooding due to storm surge, sea-level anomalies, tide elevation, and wave run-up during the same storm and sea-level rise simulation. References Cited: Howell, S., Smith-Konter, B., Frazer, N., Tong, X., and Sandwell, D., 2016, The vertical fingerprint of earthquake cycle loading in southern California: Nature Geoscience, v. 9, p. 611-614, doi:10.1038/ngeo2741. Limber, P., Barnard, P.L. and Hapke., C., 2015, Towards projecting the retreat of California’s coastal cliffs during the 21st Century: in, Wang, P., Rosati, J.D., and Cheng, J., (eds.), The Proceedings of the Coastal Sediments: 2015, World Scientific, 14 p., doi:10.1142/9789814689977_0245 Roelvink, J.A., Reniers, A., van Dongeren, A.R., van Thiel de Vries, J., McCall, R., and Lescinski, J., 2009, Modeling storm impacts on beaches, dunes and barrier islands: Coastal Engineering, v. 56, p. 1,133–1,152, doi:10.1016/j.coastaleng.2009.08.006. Tolman, H.L., Balasubramaniyan, B., Burroughs, L.D., Chalikov, D.V., Chao, Y.Y., Chen H.S., Gerald, V.M., 2002, Development and implementation of wind generated ocean surface wave models at NCEP: Weather and Forecasting, v. 17, p. 311-333. Vitousek, S. and Barnard, P.L., 2015, A non-linear, implicit one-line model to predict long-term shoreline change: in, Wang, P., Rosati, J.D., and Cheng, J., (eds.), The Proceedings of the Coastal Sediments: 2015, World Scientific, 14 p., doi:10.1142/9789814689977_0215.

Projected Hazard: Model-derived significant wave height (in meters) for the given storm condition and sea-level rise (SLR) scenario. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the model summary and inspect output carefully. Data are complete for the information presented. Details: Model background: The CoSMoS model comprises three tiers. Tier I consists of one Delft3D hydrodynamics FLOW grid for computation of tides, water level variations, flows, and currents and one SWAN grid for computation of wave generation and propagation across the continental shelf. The FLOW and SWAN models are two-way coupled so that tidal currents are accounted for in wave propagation and growth and conversely, so that orbital velocities generated by waves impart changes on tidal currents. The Tier I SWAN and FLOW models consist of identical structured curvilinear grids that extend from far offshore to the shore and range in resolution from 0.5 km in the offshore to 0.2 km in the nearshore. Spatially varying astronomic tidal amplitudes and phases and steric rises in water levels due to large-scale effects (for example, a prolonged rise in sea level) are applied along all open boundaries of the Tier I FLOW grid. Winds (split into eastward and northward components) and sea-level pressure (SLP) fields from CaRD10 (Dr. Dan Cayan, Scripps Institute of Oceanography, San Diego, California, written commun., 2014) that vary in both space and time are applied to all grid cells at each model time-step. Deep-water wave conditions, applied at the open boundaries of the Tier I SWAN model runs, were projected for the 21st century Representative Concentration Pathway (RCP) 4.5 climate scenario (2011-2100) using the WaveWatch III numerical wave model (Tolman and others, 2002) and 3-hourly winds from the GFDL-ESM2M Global Climate Model (GCM). Tier II provides higher resolution near the shore and in areas that require greater resolution of physical processes (such as bays, harbors, and estuaries). A single nested outer grid and multiple two-way coupled domain decomposition (DD) structured grids allow for local grid refinement and higher resolution where needed. Tier II was segmented into 11 sections along the Southern California Bight, to reduce computation time and complete runs within computational limitations. Water-level and Neumann time-series, extracted from Tier I simulations, are applied to the shore-parallel and lateral open boundaries of each Tier II sub-model outer grid respectively. Several of the sub-models proved to be unstable with lateral Neumann boundaries; for those cases one or both of the lateral boundaries were converted to water-level time-series or left unassigned. The open-boundary time-series are extracted from completed Tier I simulations so that there is no communication from Tier II to Tier I. Because this one-way nesting could produce erroneous results near the boundaries of Tier II and because data near any model boundary are always suspect, Tier II sub-model extents were designed to overlap in the along-coast direction. In the landward direction, Tier II DD grids extend to the 10-m topographic contour; exceptions exist where channels (such as the Los Angeles River) or other low-lying regions extend very far inland. Space- and time-varying wind and SLP fields, identical to those used in Tier I simulations, are applied to all Tier II DD grids to allow for wind-setup and local inverse barometer effects (IBE, rise or depression of water levels in response to atmospheric pressure gradients). A total of 42 time-series fluvial discharges are included in the Tier II FLOW domains in an effort to simulate exacerbated flooding caused by backflow at the confluence of high river seaward flows and elevated coastal surge levels migrating inland. Time-varying fluvial discharges are applied either at the closed boundaries or distributed as point sources within the relevant model domains. Wave computations are accomplished with the SWAN model using two grids for each Tier II sub-model: one larger grid covering the same area as the outer FLOW grid and a second finer resolution two-way coupled nearshore nested grid. The nearshore grid extends from approximately 800-1,000 m water depth up to 8-10 m elevations onshore. The landward extension is included to allow for wave computations of the higher SLR scenarios. Time- and space-varying 2D wave spectra extracted from previously completed Tier I simulations are applied approximately every kilometer along the open boundaries of the outer Tier II sub-model SWAN grids. The same space- and time-varying wind fields used in Tier I simulations are also applied to both Tier II SWAN grids to allow for computation of local wave generation. Tier III for the entire Southern California Bight consists of 4,802 cross-shore transects (CST) spaced approximately 100 m apart in the along-shore direction. The profiles extend from the -15 m isobath to at least 10 m above NAVD88. The CSTs are truncated for cases where a lagoon or other waterway exists on the landward end of the profile. Time-varying water levels and wave parameters (significant wave heights, Hs; peak periods, Tp; and peak incident wave directions, Dp), extracted from Tier II grid cells that coincide with the seaward end of the CSTs, are applied at the open boundary of each CST. The XBeach model is run in a hydrostatic (no vertical pressure gradients) mode including event-based morphodynamic change. Wave propagation, two-way wave-current interaction, water-level variations, and wave runup are computed at each transect. XBeach simulations are included in the CoSMoS model to account for infragravity waves that can significantly extend the reach of wave runup (Roelvink and others, 2009) compared to short-wave incident waves. The U.S. west coast is particularly susceptible to infragravity waves at the shore due to breaking of long-period swell waves (Tp > 15). Resulting water levels (WLs) from both Delft3D (high interest bays and marshes) and open-coast XBeach (CSTs) were spatially combined and interpolated to a 10 m grid. These WL elevations are differenced from the originating 2 m digital elevation model (DEM) to determine final flooding extent and depth of flooding. Events: The model system is run for pre-determined scenarios of interest such as the 1-yr or 100-yr storm event in combination with sea-level rise. Storms are first identified from time-series of total water level proxies (TWLpx) at the shore. TWLpx are computed for the majority of the 21st century (2010-2100), assuming a linear super-position of the major processes that contribute to the overall total water level. TWLpx time-series are then evaluated for extreme events, which define the boundary conditions for subsequent modeling with CoSMoS. Multiple 100-yr events are determined (varying Hs, Tp, Dp) and used for multiple model runs to better account for regional and directional flooding affects. Model results are combined and compiled into scenario-specific composites of flood projection. Digital Elevation Model (DEM): Our seamless, topobathymetric digital elevation model (DEM) was based largely upon the Coastal California TopoBathy Merge Project DEM, with some modifications performed by the USGS Earth Resources Observation and Science (EROS) Center to incorporate the most recent, high-resolution topographic and bathymetric datasets available. Topography is derived from bare-earth light detection and ranging (lidar) data collected in 2009-2011 for the CA Coastal Conservancy Lidar Project and bathymetry from 2009-2010 bathymetric lidar as well as acoustic multi- and single-beam data collected primarily between 2001 and 2013. The DEM was constructed to define the shape of nearshore, beach, and cliff surfaces as accurately as possible, utilizing dozens of bathymetric and topographic data sets. These data were used to populate the majority of the Tier I and II grids. To describe and include impacts from long-term shoreline evolution, including cumulative storm activity, seasonal trends, ENSO, and SLR, the DEM was modified for each SLR scenario. Long-term shoreline (Vitousek and Barnard, 2015) and cliff (Limber and others, 2015) erosion projections were efficiently combined along the cross-shore transects to evolve the shore-normal profiles. Elevation changes from the profiles were spatially-merged for a cohesive, 3D depiction of coastal evolution used to modify the DEM. These data are used to generate initial profiles of the 4,802 CSTs used for Phase 2 Tier III XBeach modeling and determining final projected flood depths in each SLR scenario. All data are referenced to NAD83 horizontal datum and NAVD88 vertical datum. Data for Tiers II and III are projected in UTM, zone 11. Outputs include: Projected wave height for the storm and sea-level rise scenario indicated. Data correspond to the near-shore region including areas vulnerable to coastal flooding due to storm surge, sea-level anomalies, tide elevation, and wave run-up during the same storm and sea-level rise simulation. References Cited: Howell, S., Smith-Konter, B., Frazer, N., Tong, X., and Sandwell, D., 2016, The vertical fingerprint of earthquake cycle loading in southern California: Nature Geoscience, v. 9, p. 611-614, doi:10.1038/ngeo2741. Limber, P., Barnard, P.L. and Hapke., C., 2015, Towards projecting the retreat of California’s coastal cliffs during the 21st Century: in, Wang, P., Rosati, J.D., and Cheng, J., (eds.), The Proceedings of the Coastal Sediments: 2015, World Scientific, 14 p., doi:10.1142/9789814689977_0245 Roelvink, J.A., Reniers, A., van Dongeren, A.R., van Thiel de Vries, J., McCall, R., and Lescinski, J., 2009, Modeling storm impacts on beaches, dunes and barrier islands: Coastal Engineering, v. 56, p. 1,133–1,152, doi:10.1016/j.coastaleng.2009.08.006. Tolman, H.L., Balasubramaniyan, B., Burroughs, L.D., Chalikov, D.V., Chao, Y.Y., Chen H.S., Gerald, V.M., 2002, Development and implementation of wind generated ocean surface wave models at NCEP: Weather and Forecasting, v. 17, p. 311-333. Vitousek, S. and Barnard, P.L., 2015, A non-linear, implicit one-line model to predict long-term shoreline change: in, Wang, P., Rosati, J.D., and Cheng, J., (eds.), The Proceedings of the Coastal Sediments: 2015, World Scientific, 14 p., doi:10.1142/9789814689977_0215.

Projected Hazard: Model-derived significant wave height (in meters) for the given storm condition and sea-level rise (SLR) scenario. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the model summary and inspect output carefully. Data are complete for the information presented. Details: Model background: The CoSMoS model comprises three tiers. Tier I consists of one Delft3D hydrodynamics FLOW grid for computation of tides, water level variations, flows, and currents and one SWAN grid for computation of wave generation and propagation across the continental shelf. The FLOW and SWAN models are two-way coupled so that tidal currents are accounted for in wave propagation and growth and conversely, so that orbital velocities generated by waves impart changes on tidal currents. The Tier I SWAN and FLOW models consist of identical structured curvilinear grids that extend from far offshore to the shore and range in resolution from 0.5 km in the offshore to 0.2 km in the nearshore. Spatially varying astronomic tidal amplitudes and phases and steric rises in water levels due to large-scale effects (for example, a prolonged rise in sea level) are applied along all open boundaries of the Tier I FLOW grid. Winds (split into eastward and northward components) and sea-level pressure (SLP) fields from CaRD10 (Dr. Dan Cayan, Scripps Institute of Oceanography, San Diego, California, written commun., 2014) that vary in both space and time are applied to all grid cells at each model time-step. Deep-water wave conditions, applied at the open boundaries of the Tier I SWAN model runs, were projected for the 21st century Representative Concentration Pathway (RCP) 4.5 climate scenario (2011-2100) using the WaveWatch III numerical wave model (Tolman and others, 2002) and 3-hourly winds from the GFDL-ESM2M Global Climate Model (GCM). Tier II provides higher resolution near the shore and in areas that require greater resolution of physical processes (such as bays, harbors, and estuaries). A single nested outer grid and multiple two-way coupled domain decomposition (DD) structured grids allow for local grid refinement and higher resolution where needed. Tier II was segmented into 11 sections along the Southern California Bight, to reduce computation time and complete runs within computational limitations. Water-level and Neumann time-series, extracted from Tier I simulations, are applied to the shore-parallel and lateral open boundaries of each Tier II sub-model outer grid respectively. Several of the sub-models proved to be unstable with lateral Neumann boundaries; for those cases one or both of the lateral boundaries were converted to water-level time-series or left unassigned. The open-boundary time-series are extracted from completed Tier I simulations so that there is no communication from Tier II to Tier I. Because this one-way nesting could produce erroneous results near the boundaries of Tier II and because data near any model boundary are always suspect, Tier II sub-model extents were designed to overlap in the along-coast direction. In the landward direction, Tier II DD grids extend to the 10-m topographic contour; exceptions exist where channels (such as the Los Angeles River) or other low-lying regions extend very far inland. Space- and time-varying wind and SLP fields, identical to those used in Tier I simulations, are applied to all Tier II DD grids to allow for wind-setup and local inverse barometer effects (IBE, rise or depression of water levels in response to atmospheric pressure gradients). A total of 42 time-series fluvial discharges are included in the Tier II FLOW domains in an effort to simulate exacerbated flooding caused by backflow at the confluence of high river seaward flows and elevated coastal surge levels migrating inland. Time-varying fluvial discharges are applied either at the closed boundaries or distributed as point sources within the relevant model domains. Wave computations are accomplished with the SWAN model using two grids for each Tier II sub-model: one larger grid covering the same area as the outer FLOW grid and a second finer resolution two-way coupled nearshore nested grid. The nearshore grid extends from approximately 800-1,000 m water depth up to 8-10 m elevations onshore. The landward extension is included to allow for wave computations of the higher SLR scenarios. Time- and space-varying 2D wave spectra extracted from previously completed Tier I simulations are applied approximately every kilometer along the open boundaries of the outer Tier II sub-model SWAN grids. The same space- and time-varying wind fields used in Tier I simulations are also applied to both Tier II SWAN grids to allow for computation of local wave generation. Tier III for the entire Southern California Bight consists of 4,802 cross-shore transects (CST) spaced approximately 100 m apart in the along-shore direction. The profiles extend from the -15 m isobath to at least 10 m above NAVD88. The CSTs are truncated for cases where a lagoon or other waterway exists on the landward end of the profile. Time-varying water levels and wave parameters (significant wave heights, Hs; peak periods, Tp; and peak incident wave directions, Dp), extracted from Tier II grid cells that coincide with the seaward end of the CSTs, are applied at the open boundary of each CST. The XBeach model is run in a hydrostatic (no vertical pressure gradients) mode including event-based morphodynamic change. Wave propagation, two-way wave-current interaction, water-level variations, and wave runup are computed at each transect. XBeach simulations are included in the CoSMoS model to account for infragravity waves that can significantly extend the reach of wave runup (Roelvink and others, 2009) compared to short-wave incident waves. The U.S. west coast is particularly susceptible to infragravity waves at the shore due to breaking of long-period swell waves (Tp > 15). Resulting water levels (WLs) from both Delft3D (high interest bays and marshes) and open-coast XBeach (CSTs) were spatially combined and interpolated to a 10 m grid. These WL elevations are differenced from the originating 2 m digital elevation model (DEM) to determine final flooding extent and depth of flooding. Events: The model system is run for pre-determined scenarios of interest such as the 1-yr or 100-yr storm event in combination with sea-level rise. Storms are first identified from time-series of total water level proxies (TWLpx) at the shore. TWLpx are computed for the majority of the 21st century (2010-2100), assuming a linear super-position of the major processes that contribute to the overall total water level. TWLpx time-series are then evaluated for extreme events, which define the boundary conditions for subsequent modeling with CoSMoS. Multiple 100-yr events are determined (varying Hs, Tp, Dp) and used for multiple model runs to better account for regional and directional flooding affects. Model results are combined and compiled into scenario-specific composites of flood projection. Digital Elevation Model (DEM): Our seamless, topobathymetric digital elevation model (DEM) was based largely upon the Coastal California TopoBathy Merge Project DEM, with some modifications performed by the USGS Earth Resources Observation and Science (EROS) Center to incorporate the most recent, high-resolution topographic and bathymetric datasets available. Topography is derived from bare-earth light detection and ranging (lidar) data collected in 2009-2011 for the CA Coastal Conservancy Lidar Project and bathymetry from 2009-2010 bathymetric lidar as well as acoustic multi- and single-beam data collected primarily between 2001 and 2013. The DEM was constructed to define the shape of nearshore, beach, and cliff surfaces as accurately as possible, utilizing dozens of bathymetric and topographic data sets. These data were used to populate the majority of the Tier I and II grids. To describe and include impacts from long-term shoreline evolution, including cumulative storm activity, seasonal trends, ENSO, and SLR, the DEM was modified for each SLR scenario. Long-term shoreline (Vitousek and Barnard, 2015) and cliff (Limber and others, 2015) erosion projections were efficiently combined along the cross-shore transects to evolve the shore-normal profiles. Elevation changes from the profiles were spatially-merged for a cohesive, 3D depiction of coastal evolution used to modify the DEM. These data are used to generate initial profiles of the 4,802 CSTs used for Phase 2 Tier III XBeach modeling and determining final projected flood depths in each SLR scenario. All data are referenced to NAD83 horizontal datum and NAVD88 vertical datum. Data for Tiers II and III are projected in UTM, zone 11. Outputs include: Projected wave height for the storm and sea-level rise scenario indicated. Data correspond to the near-shore region including areas vulnerable to coastal flooding due to storm surge, sea-level anomalies, tide elevation, and wave run-up during the same storm and sea-level rise simulation. References Cited: Howell, S., Smith-Konter, B., Frazer, N., Tong, X., and Sandwell, D., 2016, The vertical fingerprint of earthquake cycle loading in southern California: Nature Geoscience, v. 9, p. 611-614, doi:10.1038/ngeo2741. Limber, P., Barnard, P.L. and Hapke., C., 2015, Towards projecting the retreat of California’s coastal cliffs during the 21st Century: in, Wang, P., Rosati, J.D., and Cheng, J., (eds.), The Proceedings of the Coastal Sediments: 2015, World Scientific, 14 p., doi:10.1142/9789814689977_0245 Roelvink, J.A., Reniers, A., van Dongeren, A.R., van Thiel de Vries, J., McCall, R., and Lescinski, J., 2009, Modeling storm impacts on beaches, dunes and barrier islands: Coastal Engineering, v. 56, p. 1,133–1,152, doi:10.1016/j.coastaleng.2009.08.006. Tolman, H.L., Balasubramaniyan, B., Burroughs, L.D., Chalikov, D.V., Chao, Y.Y., Chen H.S., Gerald, V.M., 2002, Development and implementation of wind generated ocean surface wave models at NCEP: Weather and Forecasting, v. 17, p. 311-333. Vitousek, S. and Barnard, P.L., 2015, A non-linear, implicit one-line model to predict long-term shoreline change: in, Wang, P., Rosati, J.D., and Cheng, J., (eds.), The Proceedings of the Coastal Sediments: 2015, World Scientific, 14 p., doi:10.1142/9789814689977_0215.

Projected Hazard: Model-derived significant wave height (in meters) for the given storm condition and sea-level rise (SLR) scenario. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the model summary and inspect output carefully. Data are complete for the information presented. Details: Model background: The CoSMoS model comprises three tiers. Tier I consists of one Delft3D hydrodynamics FLOW grid for computation of tides, water level variations, flows, and currents and one SWAN grid for computation of wave generation and propagation across the continental shelf. The FLOW and SWAN models are two-way coupled so that tidal currents are accounted for in wave propagation and growth and conversely, so that orbital velocities generated by waves impart changes on tidal currents. The Tier I SWAN and FLOW models consist of identical structured curvilinear grids that extend from far offshore to the shore and range in resolution from 0.5 km in the offshore to 0.2 km in the nearshore. Spatially varying astronomic tidal amplitudes and phases and steric rises in water levels due to large-scale effects (for example, a prolonged rise in sea level) are applied along all open boundaries of the Tier I FLOW grid. Winds (split into eastward and northward components) and sea-level pressure (SLP) fields from CaRD10 (Dr. Dan Cayan, Scripps Institute of Oceanography, San Diego, California, written commun., 2014) that vary in both space and time are applied to all grid cells at each model time-step. Deep-water wave conditions, applied at the open boundaries of the Tier I SWAN model runs, were projected for the 21st century Representative Concentration Pathway (RCP) 4.5 climate scenario (2011-2100) using the WaveWatch III numerical wave model (Tolman and others, 2002) and 3-hourly winds from the GFDL-ESM2M Global Climate Model (GCM). Tier II provides higher resolution near the shore and in areas that require greater resolution of physical processes (such as bays, harbors, and estuaries). A single nested outer grid and multiple two-way coupled domain decomposition (DD) structured grids allow for local grid refinement and higher resolution where needed. Tier II was segmented into 11 sections along the Southern California Bight, to reduce computation time and complete runs within computational limitations. Water-level and Neumann time-series, extracted from Tier I simulations, are applied to the shore-parallel and lateral open boundaries of each Tier II sub-model outer grid respectively. Several of the sub-models proved to be unstable with lateral Neumann boundaries; for those cases one or both of the lateral boundaries were converted to water-level time-series or left unassigned. The open-boundary time-series are extracted from completed Tier I simulations so that there is no communication from Tier II to Tier I. Because this one-way nesting could produce erroneous results near the boundaries of Tier II and because data near any model boundary are always suspect, Tier II sub-model extents were designed to overlap in the along-coast direction. In the landward direction, Tier II DD grids extend to the 10-m topographic contour; exceptions exist where channels (such as the Los Angeles River) or other low-lying regions extend very far inland. Space- and time-varying wind and SLP fields, identical to those used in Tier I simulations, are applied to all Tier II DD grids to allow for wind-setup and local inverse barometer effects (IBE, rise or depression of water levels in response to atmospheric pressure gradients). A total of 42 time-series fluvial discharges are included in the Tier II FLOW domains in an effort to simulate exacerbated flooding caused by backflow at the confluence of high river seaward flows and elevated coastal surge levels migrating inland. Time-varying fluvial discharges are applied either at the closed boundaries or distributed as point sources within the relevant model domains. Wave computations are accomplished with the SWAN model using two grids for each Tier II sub-model: one larger grid covering the same area as the outer FLOW grid and a second finer resolution two-way coupled nearshore nested grid. The nearshore grid extends from approximately 800-1,000 m water depth up to 8-10 m elevations onshore. The landward extension is included to allow for wave computations of the higher SLR scenarios. Time- and space-varying 2D wave spectra extracted from previously completed Tier I simulations are applied approximately every kilometer along the open boundaries of the outer Tier II sub-model SWAN grids. The same space- and time-varying wind fields used in Tier I simulations are also applied to both Tier II SWAN grids to allow for computation of local wave generation. Tier III for the entire Southern California Bight consists of 4,802 cross-shore transects (CST) spaced approximately 100 m apart in the along-shore direction. The profiles extend from the -15 m isobath to at least 10 m above NAVD88. The CSTs are truncated for cases where a lagoon or other waterway exists on the landward end of the profile. Time-varying water levels and wave parameters (significant wave heights, Hs; peak periods, Tp; and peak incident wave directions, Dp), extracted from Tier II grid cells that coincide with the seaward end of the CSTs, are applied at the open boundary of each CST. The XBeach model is run in a hydrostatic (no vertical pressure gradients) mode including event-based morphodynamic change. Wave propagation, two-way wave-current interaction, water-level variations, and wave runup are computed at each transect. XBeach simulations are included in the CoSMoS model to account for infragravity waves that can significantly extend the reach of wave runup (Roelvink and others, 2009) compared to short-wave incident waves. The U.S. west coast is particularly susceptible to infragravity waves at the shore due to breaking of long-period swell waves (Tp > 15). Resulting water levels (WLs) from both Delft3D (high interest bays and marshes) and open-coast XBeach (CSTs) were spatially combined and interpolated to a 10 m grid. These WL elevations are differenced from the originating 2 m digital elevation model (DEM) to determine final flooding extent and depth of flooding. Events: The model system is run for pre-determined scenarios of interest such as the 1-yr or 100-yr storm event in combination with sea-level rise. Storms are first identified from time-series of total water level proxies (TWLpx) at the shore. TWLpx are computed for the majority of the 21st century (2010-2100), assuming a linear super-position of the major processes that contribute to the overall total water level. TWLpx time-series are then evaluated for extreme events, which define the boundary conditions for subsequent modeling with CoSMoS. Multiple 100-yr events are determined (varying Hs, Tp, Dp) and used for multiple model runs to better account for regional and directional flooding affects. Model results are combined and compiled into scenario-specific composites of flood projection. Digital Elevation Model (DEM): Our seamless, topobathymetric digital elevation model (DEM) was based largely upon the Coastal California TopoBathy Merge Project DEM, with some modifications performed by the USGS Earth Resources Observation and Science (EROS) Center to incorporate the most recent, high-resolution topographic and bathymetric datasets available. Topography is derived from bare-earth light detection and ranging (lidar) data collected in 2009-2011 for the CA Coastal Conservancy Lidar Project and bathymetry from 2009-2010 bathymetric lidar as well as acoustic multi- and single-beam data collected primarily between 2001 and 2013. The DEM was constructed to define the shape of nearshore, beach, and cliff surfaces as accurately as possible, utilizing dozens of bathymetric and topographic data sets. These data were used to populate the majority of the Tier I and II grids. To describe and include impacts from long-term shoreline evolution, including cumulative storm activity, seasonal trends, ENSO, and SLR, the DEM was modified for each SLR scenario. Long-term shoreline (Vitousek and Barnard, 2015) and cliff (Limber and others, 2015) erosion projections were efficiently combined along the cross-shore transects to evolve the shore-normal profiles. Elevation changes from the profiles were spatially-merged for a cohesive, 3D depiction of coastal evolution used to modify the DEM. These data are used to generate initial profiles of the 4,802 CSTs used for Phase 2 Tier III XBeach modeling and determining final projected flood depths in each SLR scenario. All data are referenced to NAD83 horizontal datum and NAVD88 vertical datum. Data for Tiers II and III are projected in UTM, zone 11. Outputs include: Projected wave height for the storm and sea-level rise scenario indicated. Data correspond to the near-shore region including areas vulnerable to coastal flooding due to storm surge, sea-level anomalies, tide elevation, and wave run-up during the same storm and sea-level rise simulation. References Cited: Howell, S., Smith-Konter, B., Frazer, N., Tong, X., and Sandwell, D., 2016, The vertical fingerprint of earthquake cycle loading in southern California: Nature Geoscience, v. 9, p. 611-614, doi:10.1038/ngeo2741. Limber, P., Barnard, P.L. and Hapke., C., 2015, Towards projecting the retreat of California’s coastal cliffs during the 21st Century: in, Wang, P., Rosati, J.D., and Cheng, J., (eds.), The Proceedings of the Coastal Sediments: 2015, World Scientific, 14 p., doi:10.1142/9789814689977_0245 Roelvink, J.A., Reniers, A., van Dongeren, A.R., van Thiel de Vries, J., McCall, R., and Lescinski, J., 2009, Modeling storm impacts on beaches, dunes and barrier islands: Coastal Engineering, v. 56, p. 1,133–1,152, doi:10.1016/j.coastaleng.2009.08.006. Tolman, H.L., Balasubramaniyan, B., Burroughs, L.D., Chalikov, D.V., Chao, Y.Y., Chen H.S., Gerald, V.M., 2002, Development and implementation of wind generated ocean surface wave models at NCEP: Weather and Forecasting, v. 17, p. 311-333. Vitousek, S. and Barnard, P.L., 2015, A non-linear, implicit one-line model to predict long-term shoreline change: in, Wang, P., Rosati, J.D., and Cheng, J., (eds.), The Proceedings of the Coastal Sediments: 2015, World Scientific, 14 p., doi:10.1142/9789814689977_0215.

Projected Hazard: Model-derived significant wave height (in meters) for the given storm condition and sea-level rise (SLR) scenario. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the model summary and inspect output carefully. Data are complete for the information presented. Details: Model background: The CoSMoS model comprises three tiers. Tier I consists of one Delft3D hydrodynamics FLOW grid for computation of tides, water level variations, flows, and currents and one SWAN grid for computation of wave generation and propagation across the continental shelf. The FLOW and SWAN models are two-way coupled so that tidal currents are accounted for in wave propagation and growth and conversely, so that orbital velocities generated by waves impart changes on tidal currents. The Tier I SWAN and FLOW models consist of identical structured curvilinear grids that extend from far offshore to the shore and range in resolution from 0.5 km in the offshore to 0.2 km in the nearshore. Spatially varying astronomic tidal amplitudes and phases and steric rises in water levels due to large-scale effects (for example, a prolonged rise in sea level) are applied along all open boundaries of the Tier I FLOW grid. Winds (split into eastward and northward components) and sea-level pressure (SLP) fields from CaRD10 (Dr. Dan Cayan, Scripps Institute of Oceanography, San Diego, California, written commun., 2014) that vary in both space and time are applied to all grid cells at each model time-step. Deep-water wave conditions, applied at the open boundaries of the Tier I SWAN model runs, were projected for the 21st century Representative Concentration Pathway (RCP) 4.5 climate scenario (2011-2100) using the WaveWatch III numerical wave model (Tolman and others, 2002) and 3-hourly winds from the GFDL-ESM2M Global Climate Model (GCM). Tier II provides higher resolution near the shore and in areas that require greater resolution of physical processes (such as bays, harbors, and estuaries). A single nested outer grid and multiple two-way coupled domain decomposition (DD) structured grids allow for local grid refinement and higher resolution where needed. Tier II was segmented into 11 sections along the Southern California Bight, to reduce computation time and complete runs within computational limitations. Water-level and Neumann time-series, extracted from Tier I simulations, are applied to the shore-parallel and lateral open boundaries of each Tier II sub-model outer grid respectively. Several of the sub-models proved to be unstable with lateral Neumann boundaries; for those cases one or both of the lateral boundaries were converted to water-level time-series or left unassigned. The open-boundary time-series are extracted from completed Tier I simulations so that there is no communication from Tier II to Tier I. Because this one-way nesting could produce erroneous results near the boundaries of Tier II and because data near any model boundary are always suspect, Tier II sub-model extents were designed to overlap in the along-coast direction. In the landward direction, Tier II DD grids extend to the 10-m topographic contour; exceptions exist where channels (such as the Los Angeles River) or other low-lying regions extend very far inland. Space- and time-varying wind and SLP fields, identical to those used in Tier I simulations, are applied to all Tier II DD grids to allow for wind-setup and local inverse barometer effects (IBE, rise or depression of water levels in response to atmospheric pressure gradients). A total of 42 time-series fluvial discharges are included in the Tier II FLOW domains in an effort to simulate exacerbated flooding caused by backflow at the confluence of high river seaward flows and elevated coastal surge levels migrating inland. Time-varying fluvial discharges are applied either at the closed boundaries or distributed as point sources within the relevant model domains. Wave computations are accomplished with the SWAN model using two grids for each Tier II sub-model: one larger grid covering the same area as the outer FLOW grid and a second finer resolution two-way coupled nearshore nested grid. The nearshore grid extends from approximately 800-1,000 m water depth up to 8-10 m elevations onshore. The landward extension is included to allow for wave computations of the higher SLR scenarios. Time- and space-varying 2D wave spectra extracted from previously completed Tier I simulations are applied approximately every kilometer along the open boundaries of the outer Tier II sub-model SWAN grids. The same space- and time-varying wind fields used in Tier I simulations are also applied to both Tier II SWAN grids to allow for computation of local wave generation. Tier III for the entire Southern California Bight consists of 4,802 cross-shore transects (CST) spaced approximately 100 m apart in the along-shore direction. The profiles extend from the -15 m isobath to at least 10 m above NAVD88. The CSTs are truncated for cases where a lagoon or other waterway exists on the landward end of the profile. Time-varying water levels and wave parameters (significant wave heights, Hs; peak periods, Tp; and peak incident wave directions, Dp), extracted from Tier II grid cells that coincide with the seaward end of the CSTs, are applied at the open boundary of each CST. The XBeach model is run in a hydrostatic (no vertical pressure gradients) mode including event-based morphodynamic change. Wave propagation, two-way wave-current interaction, water-level variations, and wave runup are computed at each transect. XBeach simulations are included in the CoSMoS model to account for infragravity waves that can significantly extend the reach of wave runup (Roelvink and others, 2009) compared to short-wave incident waves. The U.S. west coast is particularly susceptible to infragravity waves at the shore due to breaking of long-period swell waves (Tp > 15). Resulting water levels (WLs) from both Delft3D (high interest bays and marshes) and open-coast XBeach (CSTs) were spatially combined and interpolated to a 10 m grid. These WL elevations are differenced from the originating 2 m digital elevation model (DEM) to determine final flooding extent and depth of flooding. Events: The model system is run for pre-determined scenarios of interest such as the 1-yr or 100-yr storm event in combination with sea-level rise. Storms are first identified from time-series of total water level proxies (TWLpx) at the shore. TWLpx are computed for the majority of the 21st century (2010-2100), assuming a linear super-position of the major processes that contribute to the overall total water level. TWLpx time-series are then evaluated for extreme events, which define the boundary conditions for subsequent modeling with CoSMoS. Multiple 100-yr events are determined (varying Hs, Tp, Dp) and used for multiple model runs to better account for regional and directional flooding affects. Model results are combined and compiled into scenario-specific composites of flood projection. Digital Elevation Model (DEM): Our seamless, topobathymetric digital elevation model (DEM) was based largely upon the Coastal California TopoBathy Merge Project DEM, with some modifications performed by the USGS Earth Resources Observation and Science (EROS) Center to incorporate the most recent, high-resolution topographic and bathymetric datasets available. Topography is derived from bare-earth light detection and ranging (lidar) data collected in 2009-2011 for the CA Coastal Conservancy Lidar Project and bathymetry from 2009-2010 bathymetric lidar as well as acoustic multi- and single-beam data collected primarily between 2001 and 2013. The DEM was constructed to define the shape of nearshore, beach, and cliff surfaces as accurately as possible, utilizing dozens of bathymetric and topographic data sets. These data were used to populate the majority of the Tier I and II grids. To describe and include impacts from long-term shoreline evolution, including cumulative storm activity, seasonal trends, ENSO, and SLR, the DEM was modified for each SLR scenario. Long-term shoreline (Vitousek and Barnard, 2015) and cliff (Limber and others, 2015) erosion projections were efficiently combined along the cross-shore transects to evolve the shore-normal profiles. Elevation changes from the profiles were spatially-merged for a cohesive, 3D depiction of coastal evolution used to modify the DEM. These data are used to generate initial profiles of the 4,802 CSTs used for Phase 2 Tier III XBeach modeling and determining final projected flood depths in each SLR scenario. All data are referenced to NAD83 horizontal datum and NAVD88 vertical datum. Data for Tiers II and III are projected in UTM, zone 11. Outputs include: Projected wave height for the storm and sea-level rise scenario indicated. Data correspond to the near-shore region including areas vulnerable to coastal flooding due to storm surge, sea-level anomalies, tide elevation, and wave run-up during the same storm and sea-level rise simulation. References Cited: Howell, S., Smith-Konter, B., Frazer, N., Tong, X., and Sandwell, D., 2016, The vertical fingerprint of earthquake cycle loading in southern California: Nature Geoscience, v. 9, p. 611-614, doi:10.1038/ngeo2741. Limber, P., Barnard, P.L. and Hapke., C., 2015, Towards projecting the retreat of California’s coastal cliffs during the 21st Century: in, Wang, P., Rosati, J.D., and Cheng, J., (eds.), The Proceedings of the Coastal Sediments: 2015, World Scientific, 14 p., doi:10.1142/9789814689977_0245 Roelvink, J.A., Reniers, A., van Dongeren, A.R., van Thiel de Vries, J., McCall, R., and Lescinski, J., 2009, Modeling storm impacts on beaches, dunes and barrier islands: Coastal Engineering, v. 56, p. 1,133–1,152, doi:10.1016/j.coastaleng.2009.08.006. Tolman, H.L., Balasubramaniyan, B., Burroughs, L.D., Chalikov, D.V., Chao, Y.Y., Chen H.S., Gerald, V.M., 2002, Development and implementation of wind generated ocean surface wave models at NCEP: Weather and Forecasting, v. 17, p. 311-333. Vitousek, S. and Barnard, P.L., 2015, A non-linear, implicit one-line model to predict long-term shoreline change: in, Wang, P., Rosati, J.D., and Cheng, J., (eds.), The Proceedings of the Coastal Sediments: 2015, World Scientific, 14 p., doi:10.1142/9789814689977_0215.

Maximum depth of flooding surface (in cm) in the region landward of the present day shoreline that is inundated for the storm condition and sea-level rise (SLR) scenario indicated. Note: Duration datasets may have occasional gaps in open-coast sections. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Model details and data sources are outlined in CoSMoS_3.0_Phase_2_Southern_California_Bight:_Summary_of_data_and_methods (available at https://www.sciencebase.gov/catalog/file/get/57f1d4f3e4b0bc0bebfee139?name=CoSMoS_SoCalv3_Phase2_summary_of_methods.pdf). Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the Summary of methods and inspect output carefully. Data are complete for the information presented.

Maximum depth of flooding surface (in cm) in the region landward of the present day shoreline that is inundated for the storm condition and sea-level rise (SLR) scenario indicated. Note: Duration datasets may have occasional gaps in open-coast sections. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Model details and data sources are outlined in CoSMoS_3.0_Phase_2_Southern_California_Bight:_Summary_of_data_and_methods (available at https://www.sciencebase.gov/catalog/file/get/57f1d4f3e4b0bc0bebfee139?name=CoSMoS_SoCalv3_Phase2_summary_of_methods.pdf). Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the Summary of methods and inspect output carefully. Data are complete for the information presented.

Maximum depth of flooding surface (in cm) in the region landward of the present day shoreline that is inundated for the storm condition and sea-level rise (SLR) scenario indicated. Note: Duration datasets may have occasional gaps in open-coast sections. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Model details and data sources are outlined in CoSMoS_3.0_Phase_2_Southern_California_Bight:_Summary_of_data_and_methods (available at https://www.sciencebase.gov/catalog/file/get/57f1d4f3e4b0bc0bebfee139?name=CoSMoS_SoCalv3_Phase2_summary_of_methods.pdf). Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the Summary of methods and inspect output carefully. Data are complete for the information presented.

Maximum depth of flooding surface (in cm) in the region landward of the present day shoreline that is inundated for the storm condition and sea-level rise (SLR) scenario indicated. Note: Duration datasets may have occasional gaps in open-coast sections. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Model details and data sources are outlined in CoSMoS_3.0_Phase_2_Southern_California_Bight:_Summary_of_data_and_methods (available at https://www.sciencebase.gov/catalog/file/get/57f1d4f3e4b0bc0bebfee139?name=CoSMoS_SoCalv3_Phase2_summary_of_methods.pdf). Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the Summary of methods and inspect output carefully. Data are complete for the information presented.

Geographic extent of projected coastal flooding, low-lying vulnerable areas, and maxium/minimum flood potential (flood uncertainty) associated with the sea-level rise and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Model details and data sources are outlined in CoSMoS_3.0_Phase_2_Southern_California_Bight:_Summary_of_data_and_methods (available at https://www.sciencebase.gov/catalog/file/get/57f1d4f3e4b0bc0bebfee139?name=CoSMoS_SoCalv3_Phase2_summary_of_methods.pdf). Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the Summary of methods and inspect output carefully. Data are complete for the information presented.

Geographic extent of projected coastal flooding, low-lying vulnerable areas, and maxium/minimum flood potential (flood uncertainty) associated with the sea-level rise and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Model details and data sources are outlined in CoSMoS_3.0_Phase_2_Southern_California_Bight:_Summary_of_data_and_methods (available at https://www.sciencebase.gov/catalog/file/get/57f1d4f3e4b0bc0bebfee139?name=CoSMoS_SoCalv3_Phase2_summary_of_methods.pdf). Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the Summary of methods and inspect output carefully. Data are complete for the information presented.

Geographic extent of projected coastal flooding, low-lying vulnerable areas, and maxium/minimum flood potential (flood uncertainty) associated with the sea-level rise and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Model details and data sources are outlined in CoSMoS_3.0_Phase_2_Southern_California_Bight:_Summary_of_data_and_methods (available at https://www.sciencebase.gov/catalog/file/get/57f1d4f3e4b0bc0bebfee139?name=CoSMoS_SoCalv3_Phase2_summary_of_methods.pdf). Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the Summary of methods and inspect output carefully. Data are complete for the information presented.

Geographic extent of projected coastal flooding, low-lying vulnerable areas, and maxium/minimum flood potential (flood uncertainty) associated with the sea-level rise and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Model details and data sources are outlined in CoSMoS_3.0_Phase_2_Southern_California_Bight:_Summary_of_data_and_methods (available at https://www.sciencebase.gov/catalog/file/get/57f1d4f3e4b0bc0bebfee139?name=CoSMoS_SoCalv3_Phase2_summary_of_methods.pdf). Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the Summary of methods and inspect output carefully. Data are complete for the information presented.

Model-derived ocean current velocities (in meters per second) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Model details and data sources are outlined in CoSMoS_3.0_Phase_2_Southern_California_Bight:_Summary_of_data_and_methods (available at https://www.sciencebase.gov/catalog/file/get/57f1d4f3e4b0bc0bebfee139?name=CoSMoS_SoCalv3_Phase2_summary_of_methods.pdf). Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the Summary of methods and inspect output carefully. Data are complete for the information presented.

Model-derived ocean current velocities (in meters per second) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Model details and data sources are outlined in CoSMoS_3.0_Phase_2_Southern_California_Bight:_Summary_of_data_and_methods (available at https://www.sciencebase.gov/catalog/file/get/57f1d4f3e4b0bc0bebfee139?name=CoSMoS_SoCalv3_Phase2_summary_of_methods.pdf). Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the Summary of methods and inspect output carefully. Data are complete for the information presented.

Model-derived ocean current velocities (in meters per second) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Model details and data sources are outlined in CoSMoS_3.0_Phase_2_Southern_California_Bight:_Summary_of_data_and_methods (available at https://www.sciencebase.gov/catalog/file/get/57f1d4f3e4b0bc0bebfee139?name=CoSMoS_SoCalv3_Phase2_summary_of_methods.pdf). Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the Summary of methods and inspect output carefully. Data are complete for the information presented.

Model-derived ocean current velocities (in meters per second) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Model details and data sources are outlined in CoSMoS_3.0_Phase_2_Southern_California_Bight:_Summary_of_data_and_methods (available at https://www.sciencebase.gov/catalog/file/get/57f1d4f3e4b0bc0bebfee139?name=CoSMoS_SoCalv3_Phase2_summary_of_methods.pdf). Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the Summary of methods and inspect output carefully. Data are complete for the information presented.

Model-derived total water levels (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Model details and data sources are outlined in CoSMoS_3.0_Phase_2_Southern_California_Bight:_Summary_of_data_and_methods (available at https://www.sciencebase.gov/catalog/file/get/57f1d4f3e4b0bc0bebfee139?name=CoSMoS_SoCalv3_Phase2_summary_of_methods.pdf). Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the Summary of methods and inspect output carefully. Data are complete for the information presented.

Model-derived total water levels (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Model details and data sources are outlined in CoSMoS_3.0_Phase_2_Southern_California_Bight:_Summary_of_data_and_methods (available at https://www.sciencebase.gov/catalog/file/get/57f1d4f3e4b0bc0bebfee139?name=CoSMoS_SoCalv3_Phase2_summary_of_methods.pdf). Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the Summary of methods and inspect output carefully. Data are complete for the information presented.

Model-derived total water levels (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Model details and data sources are outlined in CoSMoS_3.0_Phase_2_Southern_California_Bight:_Summary_of_data_and_methods (available at https://www.sciencebase.gov/catalog/file/get/57f1d4f3e4b0bc0bebfee139?name=CoSMoS_SoCalv3_Phase2_summary_of_methods.pdf). Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the Summary of methods and inspect output carefully. Data are complete for the information presented.

Model-derived total water levels (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Model details and data sources are outlined in CoSMoS_3.0_Phase_2_Southern_California_Bight:_Summary_of_data_and_methods (available at https://www.sciencebase.gov/catalog/file/get/57f1d4f3e4b0bc0bebfee139?name=CoSMoS_SoCalv3_Phase2_summary_of_methods.pdf). Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the Summary of methods and inspect output carefully. Data are complete for the information presented.

Model-derived significant wave height (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Model details and data sources are outlined in CoSMoS_3.0_Phase_2_Southern_California_Bight:_Summary_of_data_and_methods (available at https://www.sciencebase.gov/catalog/file/get/57f1d4f3e4b0bc0bebfee139?name=CoSMoS_SoCalv3_Phase2_summary_of_methods.pdf). Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the Summary of methods and inspect output carefully. Data are complete for the information presented.

Model-derived significant wave height (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Model details and data sources are outlined in CoSMoS_3.0_Phase_2_Southern_California_Bight:_Summary_of_data_and_methods (available at https://www.sciencebase.gov/catalog/file/get/57f1d4f3e4b0bc0bebfee139?name=CoSMoS_SoCalv3_Phase2_summary_of_methods.pdf). Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the Summary of methods and inspect output carefully. Data are complete for the information presented.

Model-derived significant wave height (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Model details and data sources are outlined in CoSMoS_3.0_Phase_2_Southern_California_Bight:_Summary_of_data_and_methods (available at https://www.sciencebase.gov/catalog/file/get/57f1d4f3e4b0bc0bebfee139?name=CoSMoS_SoCalv3_Phase2_summary_of_methods.pdf). Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the Summary of methods and inspect output carefully. Data are complete for the information presented.

Model-derived significant wave height (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Model details and data sources are outlined in CoSMoS_3.0_Phase_2_Southern_California_Bight:_Summary_of_data_and_methods (available at https://www.sciencebase.gov/catalog/file/get/57f1d4f3e4b0bc0bebfee139?name=CoSMoS_SoCalv3_Phase2_summary_of_methods.pdf). Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the Summary of methods and inspect output carefully. Data are complete for the information presented.

Maximum depth of flooding surface (in cm) in the region landward of the present day shoreline that is inundated for the storm condition and sea-level rise (SLR) scenario indicated. Note: Duration datasets may have occasional gaps in open-coast sections. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Model details and data sources are outlined in CoSMoS_3.0_Phase_2_Southern_California_Bight:_Summary_of_data_and_methods (available at https://www.sciencebase.gov/catalog/file/get/57f1d4f3e4b0bc0bebfee139?name=CoSMoS_SoCalv3_Phase2_summary_of_methods.pdf). Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the Summary of methods and inspect output carefully. Data are complete for the information presented.

Maximum depth of flooding surface (in cm) in the region landward of the present day shoreline that is inundated for the storm condition and sea-level rise (SLR) scenario indicated. Note: Duration datasets may have occasional gaps in open-coast sections. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Model details and data sources are outlined in CoSMoS_3.0_Phase_2_Southern_California_Bight:_Summary_of_data_and_methods (available at https://www.sciencebase.gov/catalog/file/get/57f1d4f3e4b0bc0bebfee139?name=CoSMoS_SoCalv3_Phase2_summary_of_methods.pdf). Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the Summary of methods and inspect output carefully. Data are complete for the information presented.

Maximum depth of flooding surface (in cm) in the region landward of the present day shoreline that is inundated for the storm condition and sea-level rise (SLR) scenario indicated. Note: Duration datasets may have occasional gaps in open-coast sections. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Model details and data sources are outlined in CoSMoS_3.0_Phase_2_Southern_California_Bight:_Summary_of_data_and_methods (available at https://www.sciencebase.gov/catalog/file/get/57f1d4f3e4b0bc0bebfee139?name=CoSMoS_SoCalv3_Phase2_summary_of_methods.pdf). Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the Summary of methods and inspect output carefully. Data are complete for the information presented.

Maximum depth of flooding surface (in cm) in the region landward of the present day shoreline that is inundated for the storm condition and sea-level rise (SLR) scenario indicated. Note: Duration datasets may have occasional gaps in open-coast sections. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Model details and data sources are outlined in CoSMoS_3.0_Phase_2_Southern_California_Bight:_Summary_of_data_and_methods (available at https://www.sciencebase.gov/catalog/file/get/57f1d4f3e4b0bc0bebfee139?name=CoSMoS_SoCalv3_Phase2_summary_of_methods.pdf). Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the Summary of methods and inspect output carefully. Data are complete for the information presented.

Geographic extent of projected coastal flooding, low-lying vulnerable areas, and maxium/minimum flood potential (flood uncertainty) associated with the sea-level rise and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Model details and data sources are outlined in CoSMoS_3.0_Phase_2_Southern_California_Bight:_Summary_of_data_and_methods (available at https://www.sciencebase.gov/catalog/file/get/57f1d4f3e4b0bc0bebfee139?name=CoSMoS_SoCalv3_Phase2_summary_of_methods.pdf). Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the Summary of methods and inspect output carefully. Data are complete for the information presented.

Geographic extent of projected coastal flooding, low-lying vulnerable areas, and maxium/minimum flood potential (flood uncertainty) associated with the sea-level rise and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Model details and data sources are outlined in CoSMoS_3.0_Phase_2_Southern_California_Bight:_Summary_of_data_and_methods (available at https://www.sciencebase.gov/catalog/file/get/57f1d4f3e4b0bc0bebfee139?name=CoSMoS_SoCalv3_Phase2_summary_of_methods.pdf). Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the Summary of methods and inspect output carefully. Data are complete for the information presented.

Geographic extent of projected coastal flooding, low-lying vulnerable areas, and maxium/minimum flood potential (flood uncertainty) associated with the sea-level rise and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Model details and data sources are outlined in CoSMoS_3.0_Phase_2_Southern_California_Bight:_Summary_of_data_and_methods (available at https://www.sciencebase.gov/catalog/file/get/57f1d4f3e4b0bc0bebfee139?name=CoSMoS_SoCalv3_Phase2_summary_of_methods.pdf). Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the Summary of methods and inspect output carefully. Data are complete for the information presented.

Geographic extent of projected coastal flooding, low-lying vulnerable areas, and maxium/minimum flood potential (flood uncertainty) associated with the sea-level rise and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Model details and data sources are outlined in CoSMoS_3.0_Phase_2_Southern_California_Bight:_Summary_of_data_and_methods (available at https://www.sciencebase.gov/catalog/file/get/57f1d4f3e4b0bc0bebfee139?name=CoSMoS_SoCalv3_Phase2_summary_of_methods.pdf). Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the Summary of methods and inspect output carefully. Data are complete for the information presented.

Model-derived ocean current velocities (in meters per second) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Model details and data sources are outlined in CoSMoS_3.0_Phase_2_Southern_California_Bight:_Summary_of_data_and_methods (available at https://www.sciencebase.gov/catalog/file/get/57f1d4f3e4b0bc0bebfee139?name=CoSMoS_SoCalv3_Phase2_summary_of_methods.pdf). Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the Summary of methods and inspect output carefully. Data are complete for the information presented.

Model-derived ocean current velocities (in meters per second) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Model details and data sources are outlined in CoSMoS_3.0_Phase_2_Southern_California_Bight:_Summary_of_data_and_methods (available at https://www.sciencebase.gov/catalog/file/get/57f1d4f3e4b0bc0bebfee139?name=CoSMoS_SoCalv3_Phase2_summary_of_methods.pdf). Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the Summary of methods and inspect output carefully. Data are complete for the information presented.

Model-derived ocean current velocities (in meters per second) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Model details and data sources are outlined in CoSMoS_3.0_Phase_2_Southern_California_Bight:_Summary_of_data_and_methods (available at https://www.sciencebase.gov/catalog/file/get/57f1d4f3e4b0bc0bebfee139?name=CoSMoS_SoCalv3_Phase2_summary_of_methods.pdf). Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the Summary of methods and inspect output carefully. Data are complete for the information presented.

Model-derived ocean current velocities (in meters per second) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Model details and data sources are outlined in CoSMoS_3.0_Phase_2_Southern_California_Bight:_Summary_of_data_and_methods (available at https://www.sciencebase.gov/catalog/file/get/57f1d4f3e4b0bc0bebfee139?name=CoSMoS_SoCalv3_Phase2_summary_of_methods.pdf). Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the Summary of methods and inspect output carefully. Data are complete for the information presented.

Model-derived total water levels (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Model details and data sources are outlined in CoSMoS_3.0_Phase_2_Southern_California_Bight:_Summary_of_data_and_methods (available at https://www.sciencebase.gov/catalog/file/get/57f1d4f3e4b0bc0bebfee139?name=CoSMoS_SoCalv3_Phase2_summary_of_methods.pdf). Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the Summary of methods and inspect output carefully. Data are complete for the information presented.

Model-derived total water levels (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Model details and data sources are outlined in CoSMoS_3.0_Phase_2_Southern_California_Bight:_Summary_of_data_and_methods (available at https://www.sciencebase.gov/catalog/file/get/57f1d4f3e4b0bc0bebfee139?name=CoSMoS_SoCalv3_Phase2_summary_of_methods.pdf). Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the Summary of methods and inspect output carefully. Data are complete for the information presented.

Model-derived total water levels (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Model details and data sources are outlined in CoSMoS_3.0_Phase_2_Southern_California_Bight:_Summary_of_data_and_methods (available at https://www.sciencebase.gov/catalog/file/get/57f1d4f3e4b0bc0bebfee139?name=CoSMoS_SoCalv3_Phase2_summary_of_methods.pdf). Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the Summary of methods and inspect output carefully. Data are complete for the information presented.

Model-derived total water levels (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Model details and data sources are outlined in CoSMoS_3.0_Phase_2_Southern_California_Bight:_Summary_of_data_and_methods (available at https://www.sciencebase.gov/catalog/file/get/57f1d4f3e4b0bc0bebfee139?name=CoSMoS_SoCalv3_Phase2_summary_of_methods.pdf). Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the Summary of methods and inspect output carefully. Data are complete for the information presented.

Model-derived significant wave height (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Model details and data sources are outlined in CoSMoS_3.0_Phase_2_Southern_California_Bight:_Summary_of_data_and_methods (available at https://www.sciencebase.gov/catalog/file/get/57f1d4f3e4b0bc0bebfee139?name=CoSMoS_SoCalv3_Phase2_summary_of_methods.pdf). Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the Summary of methods and inspect output carefully. Data are complete for the information presented.

Model-derived significant wave height (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Model details and data sources are outlined in CoSMoS_3.0_Phase_2_Southern_California_Bight:_Summary_of_data_and_methods (available at https://www.sciencebase.gov/catalog/file/get/57f1d4f3e4b0bc0bebfee139?name=CoSMoS_SoCalv3_Phase2_summary_of_methods.pdf). Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the Summary of methods and inspect output carefully. Data are complete for the information presented.

Model-derived significant wave height (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Model details and data sources are outlined in CoSMoS_3.0_Phase_2_Southern_California_Bight:_Summary_of_data_and_methods (available at https://www.sciencebase.gov/catalog/file/get/57f1d4f3e4b0bc0bebfee139?name=CoSMoS_SoCalv3_Phase2_summary_of_methods.pdf). Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the Summary of methods and inspect output carefully. Data are complete for the information presented.

Model-derived significant wave height (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Model details and data sources are outlined in CoSMoS_3.0_Phase_2_Southern_California_Bight:_Summary_of_data_and_methods (available at https://www.sciencebase.gov/catalog/file/get/57f1d4f3e4b0bc0bebfee139?name=CoSMoS_SoCalv3_Phase2_summary_of_methods.pdf). Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the Summary of methods and inspect output carefully. Data are complete for the information presented.

These data contain maximum depth of flooding (cm) in the region landward of the present-day shoreline for the sea-level change and storm condition indicated.

These data contain maximum depth of flooding (cm) in the region landward of the present-day shoreline for the sea-level rise (SLR) and storm condition indicated.

These data contain maximum depth of flooding (cm) in the region landward of the present-day shoreline for the sea-level change and storm condition indicated.

These data contain geographic extents of projected coastal flooding, low-lying vulnerable areas, and maximum/minimum flood potential (flood uncertainty) associated with the sea-level change and storm condition indicated.

These data contain geographic extents of projected coastal flooding, low-lying vulnerable areas, and maximum/minimum flood potential (flood uncertainty) associated with the sea-level rise (SLR) and storm condition indicated.

These data contain geographic extents of projected coastal flooding, low-lying vulnerable areas, and maximum/minimum flood potential (flood uncertainty) associated with the storm and sea-level condition indicated.

These data contain maximum model-derived ocean currents (in meters per second) for the sea-level change and storm condition indicated.

These data contain maximum model-derived ocean currents (in meters per second) for the sea-level rise (SLR) and storm condition indicated.

These data contain maximum model-derived ocean currents (in meters per second) for the sea-level change and storm condition indicated.

These data contain model-derived maximum water levels (in meters) for the sea-level change and storm condition indicated.

These data contain model-derived maximum water levels (in meters) for the sea-level rise (SLR) and storm condition indicated.

These data contain model-derived maximum water levels (in meters) for the sea-level change and storm condition indicated.

These data contain maximum model-derived significant wave height (in meters) for the sea-level change and storm condition indicated.

These data contain maximum model-derived significant wave height (in meters) for the sea-level rise (SLR) and storm condition indicated.

These data contain maximum model-derived significant wave height (in meters) for the sea-level change and storm condition indicated.

This data contains maximum depth of flooding (cm) in the region landward of the present-day shoreline for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018). Please read metadata and inspect output carefully. Data are complete for the information presented. Due to file size constraints, data are available in two parts: part 1 includes SLR conditions 0 - 1.5 m, and part 2 includes SLR conditions 2.0 - 5.0 m.

This data contains maximum depth of flooding (cm) in the region landward of the present-day shoreline for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018). Please read metadata and inspect output carefully. Data are complete for the information presented. Due to file size constraints, data are available in two parts: part 1 includes SLR conditions 0 - 1.5 m, and part 2 includes SLR conditions 2.0 - 5.0 m.

This data contains maximum depth of flooding (cm) in the region landward of the present-day shoreline for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018). Please read metadata and inspect output carefully. Data are complete for the information presented. Due to file size constraints, data are available in two parts: part 1 includes SLR conditions 0 - 1.5 m, and part 2 includes SLR conditions 2.0 - 5.0 m.

This data contains maximum depth of flooding (cm) in the region landward of the present-day shoreline for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018). Please read metadata and inspect output carefully. Data are complete for the information presented. Due to file size constraints, data are available in two parts: part 1 includes SLR conditions 0 - 1.5 m, and part 2 includes SLR conditions 2.0 - 5.0 m.

This data contains geographic extents of projected coastal flooding, low-lying vulnerable areas, and maximum/minimum flood potential (flood uncertainty) associated with the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018). Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains geographic extents of projected coastal flooding, low-lying vulnerable areas, and maximum/minimum flood potential (flood uncertainty) associated with the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018). Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains geographic extents of projected coastal flooding, low-lying vulnerable areas, and maximum/minimum flood potential (flood uncertainty) associated with the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018). Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains geographic extents of projected coastal flooding, low-lying vulnerable areas, and maximum/minimum flood potential (flood uncertainty) associated with the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018). Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains maximum model-derived ocean currents (in meters per second) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018). Please read metadata and inspect output carefully. Data are complete for the information presented. Due to file size constraints, data are available in two parts: part 1 includes SLR conditions 0 - 1.5 m, and part 2 includes SLR conditions 2.0 - 5.0 m.

This data contains maximum model-derived ocean currents (in meters per second) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018). Please read metadata and inspect output carefully. Data are complete for the information presented. Due to file size constraints, data are available in two parts: part 1 includes SLR conditions 0 - 1.5 m, and part 2 includes SLR conditions 2.0 - 5.0 m.

This data contains maximum model-derived ocean currents (in meters per second) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018). Please read metadata and inspect output carefully. Data are complete for the information presented. Due to file size constraints, data are available in two parts: part 1 includes SLR conditions 0 - 1.5 m, and part 2 includes SLR conditions 2.0 - 5.0 m.

This data contains maximum model-derived ocean currents (in meters per second) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018). Please read metadata and inspect output carefully. Data are complete for the information presented. Due to file size constraints, data are available in two parts: part 1 includes SLR conditions 0 - 1.5 m, and part 2 includes SLR conditions 2.0 - 5.0 m.

This data contains model-derived total water elevation (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018). Please read metadata and inspect output carefully. Data are complete for the information presented. Due to file size constraints, data are available in two parts: part 1 includes SLR conditions 0 - 1.5 m, and part 2 includes SLR conditions 2.0 - 5.0 m.

This data contains model-derived total water elevation (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018). Please read metadata and inspect output carefully. Data are complete for the information presented. Due to file size constraints, data are available in two parts: part 1 includes SLR conditions 0 - 1.5 m, and part 2 includes SLR conditions 2.0 - 5.0 m.

This data contains model-derived total water elevation (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018). Please read metadata and inspect output carefully. Data are complete for the information presented. Due to file size constraints, data are available in two parts: part 1 includes SLR conditions 0 - 1.5 m, and part 2 includes SLR conditions 2.0 - 5.0 m.

This data contains model-derived total water elevation (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018). Please read metadata and inspect output carefully. Data are complete for the information presented. Due to file size constraints, data are available in two parts: part 1 includes SLR conditions 0 - 1.5 m, and part 2 includes SLR conditions 2.0 - 5.0 m.

This data contains maximum model-derived significant wave height (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018). Please read metadata and inspect output carefully. Data are complete for the information presented. Due to file size constraints, data are available in two parts: part 1 includes SLR conditions 0 - 1.5 m, and part 2 includes SLR conditions 2.0 - 5.0 m.

This data contains maximum model-derived significant wave height (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018). Please read metadata and inspect output carefully. Data are complete for the information presented. Due to file size constraints, data are available in two parts: part 1 includes SLR conditions 0 - 1.5 m, and part 2 includes SLR conditions 2.0 - 5.0 m.

This data contains maximum model-derived significant wave height (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018). Please read metadata and inspect output carefully. Data are complete for the information presented. Due to file size constraints, data are available in two parts: part 1 includes SLR conditions 0 - 1.5 m, and part 2 includes SLR conditions 2.0 - 5.0 m.

This data contains maximum model-derived significant wave height (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018). Please read metadata and inspect output carefully. Data are complete for the information presented. Due to file size constraints, data are available in two parts: part 1 includes SLR conditions 0 - 1.5 m, and part 2 includes SLR conditions 2.0 - 5.0 m.

This data contains maximum depth of flooding (cm) in the region landward of the present-day shoreline for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018). Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains maximum depth of flooding (cm) in the region landward of the present-day shoreline for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018). Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains maximum depth of flooding (cm) in the region landward of the present-day shoreline for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018). Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains maximum depth of flooding (cm) in the region landward of the present-day shoreline for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018). Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains geographic extents of projected coastal flooding, low-lying vulnerable areas, and maximum/minimum flood potential (flood uncertainty) associated with the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018). Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains geographic extents of projected coastal flooding, low-lying vulnerable areas, and maximum/minimum flood potential (flood uncertainty) associated with the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018). Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains geographic extents of projected coastal flooding, low-lying vulnerable areas, and maximum/minimum flood potential (flood uncertainty) associated with the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018). Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains geographic extents of projected coastal flooding, low-lying vulnerable areas, and maximum/minimum flood potential (flood uncertainty) associated with the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018). Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains maximum model-derived ocean currents (in meters per second) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018). Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains maximum model-derived ocean currents (in meters per second) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018). Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains maximum model-derived ocean currents (in meters per second) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018). Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains maximum model-derived ocean currents (in meters per second) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018). Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains model-derived total water levels (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018). Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains model-derived total water levels (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018). Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains model-derived total water levels (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018). Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains model-derived total water levels (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018). Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains maximum model-derived significant wave height (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018). Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains maximum model-derived significant wave height (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018). Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains maximum model-derived significant wave height (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018). Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains maximum model-derived significant wave height (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018). Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains maximum depth of flooding (cm) in the region landward of the present-day shoreline for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018).Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains maximum depth of flooding (cm) in the region landward of the present-day shoreline for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018).Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains maximum depth of flooding (cm) in the region landward of the present-day shoreline for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018).Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains maximum depth of flooding (cm) in the region landward of the present-day shoreline for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018).Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains geographic extents of projected coastal flooding, low-lying vulnerable areas, and maximum/minimum flood potential (flood uncertainty) associated with the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018).Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains geographic extents of projected coastal flooding, low-lying vulnerable areas, and maximum/minimum flood potential (flood uncertainty) associated with the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018).Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains geographic extents of projected coastal flooding, low-lying vulnerable areas, and maximum/minimum flood potential (flood uncertainty) associated with the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018).Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains geographic extents of projected coastal flooding, low-lying vulnerable areas, and maximum/minimum flood potential (flood uncertainty) associated with the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018).Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains maximum model-derived ocean currents (in meters per second) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018).Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains maximum model-derived ocean currents (in meters per second) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018).Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains maximum model-derived ocean currents (in meters per second) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018).Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains maximum model-derived ocean currents (in meters per second) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018).Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains model-derived total water levels (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018).Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains model-derived total water levels (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018).Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains model-derived total water levels (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018).Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains model-derived total water levels (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018).Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains maximum model-derived significant wave height (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018).Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains maximum model-derived significant wave height (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018).Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains maximum model-derived significant wave height (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018).Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains maximum model-derived significant wave height (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018).Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains maximum depth of flooding (cm) in the region landward of the present-day shoreline for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018).Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains maximum depth of flooding (cm) in the region landward of the present-day shoreline for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018).Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains maximum depth of flooding (cm) in the region landward of the present-day shoreline for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018).Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains maximum depth of flooding (cm) in the region landward of the present-day shoreline for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018).Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains geographic extents of projected coastal flooding, low-lying vulnerable areas, and maximum/minimum flood potential (flood uncertainty) associated with the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018).Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains geographic extents of projected coastal flooding, low-lying vulnerable areas, and maximum/minimum flood potential (flood uncertainty) associated with the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018).Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains geographic extents of projected coastal flooding, low-lying vulnerable areas, and maximum/minimum flood potential (flood uncertainty) associated with the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018).Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains geographic extents of projected coastal flooding, low-lying vulnerable areas, and maximum/minimum flood potential (flood uncertainty) associated with the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018).Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains maximum model-derived ocean currents (in meters per second) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018).Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains maximum model-derived ocean currents (in meters per second) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018).Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains maximum model-derived ocean currents (in meters per second) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018).Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains maximum model-derived ocean currents (in meters per second) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018).Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains model-derived total water levels (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018).Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains model-derived total water levels (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018).Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains model-derived total water levels (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018).Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains model-derived total water levels (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018).Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains maximum model-derived significant wave height (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018).Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains maximum model-derived significant wave height (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018).Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains maximum model-derived significant wave height (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018).Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains maximum model-derived significant wave height (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018).Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains maximum depth of flooding (cm) in the region landward of the present-day shoreline for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018).Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains maximum depth of flooding (cm) in the region landward of the present-day shoreline for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018).Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains maximum depth of flooding (cm) in the region landward of the present-day shoreline for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018).Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains maximum depth of flooding (cm) in the region landward of the present-day shoreline for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018).Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains geographic extents of projected coastal flooding, low-lying vulnerable areas, and maximum/minimum flood potential (flood uncertainty) associated with the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018).Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains geographic extents of projected coastal flooding, low-lying vulnerable areas, and maximum/minimum flood potential (flood uncertainty) associated with the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018).Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains geographic extents of projected coastal flooding, low-lying vulnerable areas, and maximum/minimum flood potential (flood uncertainty) associated with the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018).Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains geographic extents of projected coastal flooding, low-lying vulnerable areas, and maximum/minimum flood potential (flood uncertainty) associated with the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018).Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains maximum model-derived ocean currents (in meters per second) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018).Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains maximum model-derived ocean currents (in meters per second) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018).Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains maximum model-derived ocean currents (in meters per second) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018).Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains maximum model-derived ocean currents (in meters per second) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018).Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains model-derived total water levels (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018).Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains model-derived total water levels (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018).Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains model-derived total water levels (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018).Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains model-derived total water levels (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018).Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains maximum model-derived significant wave height (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018).Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains maximum model-derived significant wave height (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018).Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains maximum model-derived significant wave height (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018).Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains maximum model-derived significant wave height (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018).Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains maximum depth of flooding (cm) in the region landward of the present-day shoreline for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018). Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains maximum depth of flooding (cm) in the region landward of the present-day shoreline for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018). Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains maximum depth of flooding (cm) in the region landward of the present-day shoreline for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018). Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains maximum depth of flooding (cm) in the region landward of the present-day shoreline for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018). Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains geographic extents of projected coastal flooding, low-lying vulnerable areas, and maximum/minimum flood potential (flood uncertainty) associated with the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018). Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains geographic extents of projected coastal flooding, low-lying vulnerable areas, and maximum/minimum flood potential (flood uncertainty) associated with the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018). Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains geographic extents of projected coastal flooding, low-lying vulnerable areas, and maximum/minimum flood potential (flood uncertainty) associated with the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018). Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains geographic extents of projected coastal flooding, low-lying vulnerable areas, and maximum/minimum flood potential (flood uncertainty) associated with the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018). Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains maximum model-derived ocean currents (in meters per second) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018). Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains maximum model-derived ocean currents (in meters per second) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018). Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains maximum model-derived ocean currents (in meters per second) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018). Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains maximum model-derived ocean currents (in meters per second) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018). Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains model-derived total water levels (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018). Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains model-derived total water levels (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018). Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains model-derived total water levels (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018). Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains model-derived total water levels (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018). Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains maximum model-derived significant wave height (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018). Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains maximum model-derived significant wave height (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018). Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains maximum model-derived significant wave height (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018). Please read metadata and inspect output carefully. Data are complete for the information presented.

This data contains maximum model-derived significant wave height (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated 1-year/20-year/100-year return interval coastal storms. Methods and processes used in Central California are replicated from and described in O'Neill and others (2018). Please read metadata and inspect output carefully. Data are complete for the information presented.