Nearshore parametric wave setup future projections (2020-2050) for the North and South Carolina coasts
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 ... |
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Nearshore parametric wave setup hindcast data (1979-2019) for the North and South Carolina coasts
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 ... |
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Nearshore water level, tide, and non-tidal residual future projections (2016-2050) for the North and South Carolina coasts
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 ... |
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Nearshore water level, tide, and non-tidal residual hindcasts (1979-2016) for the North and South Carolina coasts
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 ... |
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Nearshore parametric wave setup future projections (2020-2050) for the U.S. Atlantic coast
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 ... |
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Nearshore parametric wave setup hindcast data (1979-2019) for the U.S. Atlantic coast
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 ... |
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Nearshore water level, tide, and non-tidal residual future projections (2016-2050) for the U.S. Atlantic coast
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 ... |
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Nearshore water level, tide, and non-tidal residual hindcasts (1979-2016) for the U.S. Atlantic coast
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 ... |
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Modeled nearshore wave parameters
This portion of the USGS data release contains simulated nearshore wave parameters derived from a stand-alone spectral wave model of the Columbia River littoral cell, Washington and Oregon. The model output includes significant wave heights, peak wave periods, mean wave directions, and water depths for a series of 221 shore normal transects that extended from the coastline to the -15 m NAVD88 elevation (about 16.5 m average water depth). Data are provided at the seaward extent of each transect as well as at ... |
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Spectral wave model input files
A stand-alone wave model application was constructed using the spectral wave model SWAN within the Delft3D4 (version 4.04.01) modeling system to simulate nearshore wave dynamics along the coast of the Columbia River littoral cell, Washington and Oregon. Nearshore wave dynamics are solved at hourly intervals on a series of nested grids with resolutions varying between 750 m for the largest grid to about 80 m for the two detailed grids that cover the Grays Harbor and Columbia River inlets. The provided model ... |
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Projections of coastal flood hazards and flood potential for North Carolina and South Carolina
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 ... |
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Projections of coastal water depths for North Carolina and South Carolina
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 ... |
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Projections of coastal flood depths for the U.S. Atlantic coast
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 ... |
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Projections of coastal flood hazards and flood potential for the U.S. Atlantic coast
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 ... |
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Model input files for the lower Nooksack River and delta, western Washington State
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 ... |
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Projections of compound floodwater depths for the lower Nooksack River and delta, western Washington State
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 ... |
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CoSMoS Whatcom County model input files
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 ... |
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Projections of coastal flood depths for Whatcom County, Northwest Washington State coast (2015-2100)
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 ... |
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Projections of coastal flood durations for Whatcom County, Northwest Washington State coast (2015-2100)
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 ... |
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Projections of coastal flood extents for Whatcom County, Northwest Washington State coast (2015-2100)
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 ... |
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Projections of coastal flood velocities for Whatcom County, Northwest Washington State coast (2015-2100)
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 ... |
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Projections of coastal flood water levels for Whatcom County, Northwest Washington State coast (2015-2100)
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 ... |
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Projections of wave heights for Whatcom County, Northwest Washington State coast (2015-2100)
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 ... |
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Ocean wave time-series data along the Alaska coast simulated with a global-scale numerical wave model under the influence of CMIP6 wind and sea ice fields
This dataset presents projected hourly time-series of wave heights, wave periods, incident wave directions and directional spreading at distinct points along the open coast of Alaska for the years 2020 through 2050. The projections were developed by running the National Oceanic and Atmospheric Administration’s (NOAA’s) WAVEWATCHIII model. Wind and sea ice fields from seven different Global Climate or General Circulation Models from the CMIP6 High-Resolution Model Intercomparison Project were used to ... |
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Ocean wave time-series data along the U.S. Atlantic, Gulf of Mexico, and Puerto Rico coasts simulated with a global-scale numerical wave model under the influence of CMIP6 wind and sea ice fields
This dataset presents projected hourly time-series of wave heights, wave periods, incident wave directions, and directional spreading at distinct points along the U.S. Atlantic, Gulf of Mexico, and Puerto Rico coasts for the years 2020 through 2050. The projections were developed by running the National Oceanic and Atmospheric Administration’s (NOAA’s) WAVEWATCHIII model. Wind and sea ice fields from seven different Global Climate or General Circulation Models from the CMIP6 High-Resolution Model ... |
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Ocean wave time-series data along the U.S. West Coast and surrounding Hawai’i simulated with a global-scale numerical wave model under the influence of CMIP6 wind and sea ice fields
This dataset presents projected hourly time-series of wave heights, wave periods, incident wave directions, and directional spreading at distinct points along the U.S. West Coast and surrounding Hawai’i for the years 2020 through 2050. The projections were developed by running the National Oceanic and Atmospheric Administration’s (NOAA’s) WAVEWATCHIII model. Wind and sea-ice fields from seven different Global Climate or General Circulation Models from the CMIP6 High-Resolution Model Intercomparison ... |
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Ocean wave time-series data surrounding Hawai’i and U.S. territories in the Pacific Ocean simulated with a global-scale numerical wave model under the influence of CMIP6 wind and sea ice fields
This dataset presents projected hourly time-series of wave heights, wave periods, incident wave directions, and directional spreading at distinct points surrounding Hawai’i and U.S. territories in the Pacific Ocean, for the years 2020 through 2050. The projections were developed by running the National Oceanic and Atmospheric Administration’s (NOAA’s) WAVEWATCHIII model. Wind and sea ice fields from seven different Global Climate or General Circulation Models from the CMIP6 High-Resolution Model ... |
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Projected groundwater emergence and shoaling along the North and South Carolina coasts
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. |
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Projected groundwater head along the North and South Carolina coasts
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 ... |
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Projected water table depths along the North and South Carolina coasts
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 ... |
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Projected groundwater emergence and shoaling along the Virginia, Georgia, and Florida coasts
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. |
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Projected groundwater head along the Virginia, Georgia, and Florida coasts
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 ... |
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Projected water table depths along the Virginia, Georgia, and Florida coasts
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 ... |
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Vertical land motion rates for the years 2007 to 2020 for the North and South Carolina coasts
Rates of land subsidence and uplift for the North and South Carolina coasts are derived from Sentinel-1A/B (2015-2020) and ALOS (2007-2011) synthetic aperture radar (SAR) satellites, at approximately 50-75 m resolution and mm-level precision. The data consist of vertical land motion (VLM) rates and the 1-sigma error in land motion rates and are available as csv files. |
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Vertical land motion rates for the years 2007 to 2020 for the U.S. Atlantic coast
This dataset contains rates of land subsidence and uplift derived from Sentinel-1A/B (2015-2020) and ALOS (2007-2011) synthetic aperture radar (SAR) satellites, at approximately 50-75 m resolution and mm-level precision for the U.S. Atlantic coast except for the states of North and South Carolina. The data consist of vertical land motion (VLM) rates and the 1-sigma error in land motion rates and are available as csv files. Similar vertical land motion rates for North Carolina and South Carolina are ... |
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Projections of shoreline change of current and future (2005-2100) sea-level rise scenarios for North Carolina and South Carolina
This dataset contains projections of shoreline change and uncertainty bands for future scenarios of sea-level rise (SLR). Scenarios include 25, 50, 75, 100, 150, 200, and 300 centimeters (cm) of SLR by the year 2100. Output for SLR of 0 cm is also included, reflective of conditions in 2005, in accordance with recent SLR projections and guidance from the National Oceanic and Atmospheric Administration (NOAA; see process steps). Projections were made using the Coastal Storm Modeling System - Coastal One-line ... |
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Satellite-derived shorelines for North Carolina and South Carolina (1984-2021)
This dataset contains shoreline positions derived from available Landsat satellite imagery for North Carolina and South Carolina for the time period of 1984 to 2021. Positions were determined using CoastSat (Vos and others, 2019a and 2019b), an open-source mapping toolbox, was used to classify coastal Landsat imagery and detect shorelines at the sub-pixel scale. To understand shoreline evolution in complex environments and operate long-term simulations illustrating potential shoreline positions in the next ... |
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Projections of shoreline change of current and future (2005-2100) sea-level rise scenarios for the U.S. Atlantic Coast
This dataset contains projections of shoreline change and uncertainty bands for future scenarios of sea-level rise (SLR). Scenarios include 25, 50, 75, 100, 150, 200, and 300 centimeters (cm) of SLR by the year 2100. Output for SLR of 0 cm is also included, reflective of conditions in 2005, in accordance with recent SLR projections and guidance from the National Oceanic and Atmospheric Administration (NOAA; see process steps).Projections were made using the Coastal Storm Modeling System - Coastal One-line ... |
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Satellite-derived shorelines for the U.S. Atlantic coast (1984-2021)
This dataset contains shoreline positions derived from available Landsat satellite imagery for five states (Delaware, Maryland, Viginia, Georgia, and Florida) along the U.S. Atlantic coast for the time period 1984 to 2021. An open-source toolbox, CoastSat (Vos and others, 2019a and 2019b), was used to classify coastal Landsat imagery and detect shorelines at the sub-pixel scale. Resulting shorelines are presented in KMZ format. Significant uncertainty is associated with the locations of shorelines in ... |
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