10-meter rasters of coastal response type probabilities with respect to projected sea-level change for the Northeastern U.S. for the 2030s, 2050s, 2080s and 2100s

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Metadata:

Identification_Information:
Citation:
Citation_Information:
Originator: Marie K. Bartlett
Originator: Julia L. Heslin
Originator: Kathryn M. Weber
Originator: Erika E. Lentz
Publication_Date: 20250717
Title:
10-meter rasters of coastal response type probabilities with respect to projected sea-level change for the Northeastern U.S. for the 2030s, 2050s, 2080s and 2100s
Edition: 1.0
Geospatial_Data_Presentation_Form: raster digital data
Series_Information:
Series_Name: data release
Issue_Identification: DOI:10.5066/P13JKJUT
Publication_Information:
Publication_Place: Woods Hole Coastal and Marine Science Center, Woods Hole, MA
Publisher:
U.S. Geological Survey, Coastal and Marine Hazards and Resources Program
Online_Linkage: https://doi.org/10.5066/P13JKJUT
Online_Linkage: Larger_Work_Citation:
Citation_Information:
Originator: Marie K. Bartlett
Originator: Julia L. Heslin
Originator: Kathryn M. Weber
Originator: Erika E. Lentz
Publication_Date: 2025
Title:
Coastal landscape response to sea-level change for the northeastern United States
Edition: 1.0
Geospatial_Data_Presentation_Form: raster digital data
Series_Information:
Series_Name: data release
Issue_Identification: DOI:10.5066/P13JKJUT
Publication_Information:
Publication_Place: Reston, VA
Publisher:
U.S. Geological Survey, Coastal and Marine Hazards and Resources Program
Other_Citation_Details:
Suggested citation: Bartlett, M.K., Heslin, J.L., Weber, K.M., and Lentz, E.E., 2025, Coastal landscape response to sea-level rise assessment for the northeastern United States: U.S. Geological Survey data release, https://doi.org/10.5066/P13JKJUT.
Online_Linkage: https://doi.org/10.5066/P13JKJUT
Online_Linkage:
Description:
Abstract:
This data release presents an update to the Coastal Response Likelihood (CRL) model (Lentz and others 2015); a spatially explicit, probabilistic model that evaluates coastal response for the Northeastern U.S. under various sea-level scenarios. The model considers the variable nature of the coast and provides outputs at spatial and temporal scales suitable for decision support. Updated model results provide higher spatial resolution predictions (from 30 meters (m) to 10 m) of adjusted land elevation ranges (AE) with respect to projected relative sea-level scenarios, a likelihood estimate of this outcome (PAE), and a probability of coastal response (CR), characterized as either static (inundated) or dynamic (maintaining or changing state). The predictions span the coastal zone vertically from 10 m below to 10 m above mean high water (MHW). Results are produced at a horizontal resolution of 10 meters for four decades (2030, 2050, 2080 and 2100) and two possible sea-level change scenarios (Intermediate Low (IL), Intermediate High (IH)) as defined by Sweet and others (2022). Adjusted elevations and their respective probabilities are generated using regional geospatial datasets of relative sea-level scenarios and current elevation data. Coastal response outcomes are determined by combining adjusted elevation outputs with land cover data and expert judgment (Lentz and others 2015) to assess whether an area is likely to maintain its existing land class, or transition to a new one (dynamic), or become submerged (static). The intended users of these data include scientific researchers, coastal planners, and natural resource managers.
Purpose:
These raster layers represent the probability of observing a static versus dynamic coastal response (CR) for the Northeastern U.S., with respect to Intermediate High (IH) and Intermediate Low (IL) predicted sea-level rise (SLR) scenarios—for the 2030s, 2050s, 2080s, and 2100s. The data are derived from a probabilistic framework (Bayesian network) that integrates relative SLR scenarios, elevation data, and land cover information. The outputs provide a probability value for a binary outcome (static or dynamic response) for each projection year. Because these responses are mutually exclusive, the probability of a dynamic response can be calculated by subtracting the static response probability from 1 (and vice versa). These layers are intended to show the spatial distribution of likely coastal response types over a broad area and should be interpreted qualitatively (see Horizontal Positional Accuracy Report for limitations).
Supplemental_Information:
These data layers are a model output produced as part of the U.S. Geological Survey Future Landscape Adaptation and Coastal Change (FLACC) project.
Time_Period_of_Content:
Time_Period_Information:
Single_Date/Time:
Calendar_Date: 2025
Currentness_Reference:
Ground condition as represented by the 2023 Coastal Change Likelihood Fabric dataset, as cited in the Sourch Citation section of this metadata record
Status:
Progress: Complete
Maintenance_and_Update_Frequency: None planned
Spatial_Domain:
Bounding_Coordinates:
West_Bounding_Coordinate: -77.5278
East_Bounding_Coordinate: -66.9432
North_Bounding_Coordinate: 45.1918
South_Bounding_Coordinate: 36.5437
Keywords:
Theme:
Theme_Keyword_Thesaurus: ISO 19115 Topic Category
Theme_Keyword: geoscientificInformation
Theme_Keyword: oceans
Theme:
Theme_Keyword_Thesaurus: None
Theme_Keyword: U.S. Geological Survey
Theme_Keyword: USGS
Theme_Keyword: Coastal and Marine Hazards and Resources Program
Theme_Keyword: Natural Hazards Mission Area
Theme_Keyword: Elevation
Theme_Keyword: Interpretation
Theme_Keyword: Landcover
Theme_Keyword: Land Cover
Theme_Keyword: Sea Level Rise
Theme_Keyword: ArcPy
Theme:
Theme_Keyword_Thesaurus: USGS Thesaurus
Theme_Keyword: coastal processes
Theme_Keyword: sea-level change
Theme_Keyword: mathematical modeling
Theme_Keyword: geospatial datasets
Theme_Keyword: scientific interpretation
Theme_Keyword: land use and land cover
Theme_Keyword: bathymetry
Theme_Keyword: topography
Theme:
Theme_Keyword_Thesaurus: USGS Metadata Identifier
Theme_Keyword: USGS:6811381bd4be0276ecc84958
Place:
Place_Keyword_Thesaurus: None
Place_Keyword: Northeast US
Place_Keyword: Maine
Place_Keyword: New Hampshire
Place_Keyword: Massachusetts
Place_Keyword: Rhode Island
Place_Keyword: Connecticut
Place_Keyword: New York
Place_Keyword: New Jersey
Place_Keyword: Delaware
Place_Keyword: Maryland
Place_Keyword: Virginia
Place_Keyword: United States
Access_Constraints: None. Please see 'Distribution Info' for details.
Use_Constraints:
Not to be used for navigation. Public domain data from the U.S. Government are freely redistributable with proper metadata and source attribution. Please recognize the U.S. Geological Survey (USGS) as the source of this information. Additionally, there are limitations associated with coastal change hazard assessments.
Point_of_Contact:
Contact_Information:
Contact_Organization_Primary:
Contact_Organization: U.S. Geological Survey
Contact_Person: Marie K. Bartlett
Contact_Address:
Address_Type: Mailing and Physical
Address: 384 Woods Hole Rd
City: Woods Hole
State_or_Province: MA
Postal_Code: 02543
Contact_Voice_Telephone: 508-548-8700 x2306
Contact_Electronic_Mail_Address: mbartlett@usgs.gov
Browse_Graphic:
Browse_Graphic_File_Name: Browse_Graphic_File_Description: Example of CR output at Plum Island, Massachusetts
Browse_Graphic_File_Type: JPEG
Native_Data_Set_Environment: Windows 11 build 22631.5039; ESRI ArcGIS Pro v3.3.0
Cross_Reference:
Citation_Information:
Originator: Erika E. Lentz
Originator: Sawyer R. Stippa
Originator: E. Robert Thieler
Originator: Nathaniel G. Plant
Originator: Dean B. Gesch
Originator: Radley M. Horton
Publication_Date: 2015
Title:
Evaluating coastal landscape response to sea-level rise in the northeastern United States: approach and methods
Edition:
Version 1.0: Originally posted February 13, 2015; Version 2.0: December 21, 2015
Geospatial_Data_Presentation_Form: publication
Series_Information:
Series_Name: Open-File Report
Issue_Identification: 2014-1252
Publication_Information:
Publication_Place: Reston, VA
Publisher: U.S. Geological Survey
Online_Linkage: https://doi.org/10.3133/ofr20141252
Cross_Reference:
Citation_Information:
Originator: Julia L. Heslin
Originator: Kathryn M. Weber
Originator: Erika E. Lentz
Originator: Donya P. Frank-Gilchrist
Originator: Jason J. Mercer
Publication_Date: 2024
Title: Coastal Response Likelihood
Series_Information:
Series_Name: software release
Issue_Identification: DOI:10.5066/P1SQIVEW
Publication_Information:
Publication_Place: Reston, VA
Publisher: U.S. Geological Survey
Other_Citation_Details: Only available to internal users within U.S. Geological Survey
Online_Linkage: https://doi.org/10.5066/p1sqivew
Cross_Reference:
Citation_Information:
Originator: Elizabeth A. Pendleton
Originator: Erika E. Lentz
Originator: Travis K. Sterne
Originator: Rachel E. Henderson
Publication_Date: 2023
Title:
Development and application of a coastal change likelihood assessment for the northeast region, Maine to Virginia
Geospatial_Data_Presentation_Form: publication
Series_Information:
Series_Name: Data Report
Issue_Identification: 1169
Publication_Information:
Publication_Place: Reston, VA
Publisher: U.S. Geological Survey
Other_Citation_Details:
Suggested citation: Pendleton, E.A., Lentz, E.E., Sterne, T.K., and Henderson, R.E., 2023, Development and application of a coastal change likelihood assessment for the northeast region, Maine to Virginia: U.S. Geological Survey Data Report 1169, 56 p., https://doi.org/10.3133/dr1169. The CCL data release (https://doi.org/10.5066/P96A2Q5X) is associated with the CCL Data Report (https://doi.org/10.3133/dr1169)
Online_Linkage: https://doi.org/10.3133/dr1169
Online_Linkage: https://pubs.er.usgs.gov/publication/dr1169
Data_Quality_Information:
Attribute_Accuracy:
Attribute_Accuracy_Report:
These GeoTIFFs were generated from attributed point data that underwent quality assurance and quality control (QA/QC) procedures to ensure consistency and accuracy. As a result, the GeoTIFFs are considered to accurately represent the results of the modeling process and the original source data used for attribution.
Logical_Consistency_Report:
The raster dataset representing coastal response probabilities (values from 0 to 1) is spatially consistent, with a uniform 10-meter grid resolution across the entire extent. QA/QC checks confirmed that all cells contain valid data within the expected range or designated NoData values. No anomalies or formatting errors were found. The dataset conforms to standard raster formatting and alignment protocols.
Completeness_Report:
Data from approximately 777,740,279 coastal grid points throughout the Northeast from Maine to Virginia were used to make coastal response predictions. Model inputs (raster format) were either upscaled or downscaled to provide inputs at the 10 m horizontal resolution of the land cover data. Each cell in this data layer displays the probability of a static or dynamic response on a scale of 0 to 1, respectively. Values greater than 0.5 are dynamic whereas values less than 0.5 are static (values equal to 0.5 highlight greatest uncertainty). Forecast values were calculated for select decades between 2030 to 2100, and will vary if performed on a different time period, if different models are used, or if different model inputs (such as updated elevation data, revised relative sea-level estimates, updated land cover information) were chosen.
Positional_Accuracy:
Horizontal_Positional_Accuracy:
Horizontal_Positional_Accuracy_Report:
A probabilistic model (Bayesian Network) is used to generate the forecast of coastal response type shown in this data layer. Because the overall horizontal accuracy of the dataset depends on the accuracy of the model, the forcing values used, expert knowledge, the underlying inputs (i.e., relative sea-level scenarios, elevation, land cover), the spatial accuracy of this dataset cannot be meaningfully quantified. These maps are intended to provide a qualitative and relative regional assessment of sea-level impacts to the landscape at the 10 m horizontal resolution displayed. Users are advised not to use the dataset to determine specific values quantitatively at any particular geographic location. For more information regarding the horizontal accuracy of source data, see Sterne and others (2023) listed in the Source Citation section.
Vertical_Positional_Accuracy:
Vertical_Positional_Accuracy_Report:
This dataset is derived from topographic and bathymetric data compiled by Sterne and others (2023), who merged USGS and NOAA source elevation data (listed below) into a seamless elevation surface with an overall expected vertical accuracy of less than 0.5 meters. This merged elevation dataset was combined with sea level rise (SLR) scenarios from Sweet and others (2022) for selected future decades (2030, 2050, 2080, and 2100). The resulting values were binned into the following adjusted elevation (flooded surface) classes: -10 to -1 m, -1 to 0 m, 0 to 1 m, 1 to 5 m, and 5 to 10 m. The integration of projected SLR data with elevation, along with the binning process used for Bayesian analysis, introduces additional uncertainty relative to the original depth values. Users are encouraged to consult the original elevation datasets from Sterne and others (2023) for detailed, unbinned depth values. This dataset is referenced to the Mean High Water (MHW) tidal datum. Source elevation data were originally referenced to the North American Vertical Datum of 1988 (NAVD 88) and were transformed to MHW using NOAA’s VDatum tool (https://vdatum.noaa.gov/).
Lineage:
Source_Information:
Source_Citation:
Citation_Information:
Originator: Travis K. Sterne
Originator: Elizabeth A. Pendleton
Originator: Erika E. Lentz
Originator: Rachel E. Henderson
Publication_Date: 2023
Title:
Coastal Change Likelihood in the U.S. Northeast Region: Maine to Virginia - Fabric Dataset
Geospatial_Data_Presentation_Form: raster digital data
Series_Information:
Series_Name: data release
Issue_Identification: DOI:10.5066/P96A2Q5X
Publication_Information:
Publication_Place: Woods Hole Coastal and Marine Science Center, Woods Hole, MA
Publisher: U.S. Geological Survey, Coastal and Marine Geology Program
Online_Linkage: https://doi.org/10.5066/P96A2Q5X
Online_Linkage:
Type_of_Source_Media: Digital
Source_Time_Period_of_Content:
Time_Period_Information:
Range_of_Dates/Times:
Beginning_Date: 2010
Ending_Date: 2021
Source_Currentness_Reference: ground condition
Source_Citation_Abbreviation: Fabric
Source_Contribution:
Contains source elevation and landcover data used to create point data which was ingested into the CRL code
Source_Information:
Source_Citation:
Citation_Information:
Originator: William V. Sweet
Originator: Benjamin D. Hamlington
Originator: Robert E. Kopp
Originator: Christopher P. Weaver
Originator: Patrick L. Barnard
Originator: David Bekaert
Originator: William Brooks
Originator: Michael Craghan
Originator: Gregory Dusek
Originator: Thomas Frederikse
Originator: Gregory Garner
Originator: Ayesha S. Genz
Originator: John P. Krasting
Originator: Eric Larour
Originator: Doug Marcy
Originator: John J. Marra
Originator: Jayantha Obeysekera
Originator: Mark Osler
Originator: Matthew Pendleton
Originator: Daniel Roman
Originator: Lauren Schmied
Originator: Will Veatch
Originator: Kathleen D. White
Originator: Casey Zuzak
Publication_Date: 202202
Title:
Global and Regional Sea Level Rise Scenarios for the United States: Updated Mean Projections and Extreme Water Level Probabilities Along U.S. Coastlines
Geospatial_Data_Presentation_Form: CSV
Series_Information:
Series_Name: NOAA Technical Report
Issue_Identification: NOS 01
Publication_Information:
Publication_Place: Silver Springs
Publisher: National Oceanic and Atmospheric Administration
Other_Citation_Details:
Sweet, W.V., Hamlington, B.D., Kopp, R.E., Weaver, C.P., Barnard, P.L., Bekaert, D., Brooks, W., Craghan, M., Dusek, G., Frederikse, T., Garner, G., Genz, A.S., Krasting, J.P., Larour, E., Marcy, D., Marra, J.J., Obeysekera, J., Osler, M., Pendleton, M., Roman, D., Schmied, L., Veatch, W., White, K.D., and Zuzak, C., 2022, Global and regional sea level rise scenarios for the United States—Updated mean projections and extreme water level probabilities along U.S. coastlines: NOAA Technical Report NOS 01, National Oceanic and Atmospheric Administration, National Ocean Service, Silver Spring, MD, 111 pp. https://earth.gov/sealevel/us/internal_resources/756/noaa-nos-techrpt01-global-regional-SLR-scenarios-US.pdf
Online_Linkage:
Type_of_Source_Media: Digital
Source_Time_Period_of_Content:
Time_Period_Information:
Multiple_Dates/Times:
Single_Date/Time:
Calendar_Date: 2030
Single_Date/Time:
Calendar_Date: 2050
Single_Date/Time:
Calendar_Date: 2080
Single_Date/Time:
Calendar_Date: 2100
Source_Currentness_Reference: ground condition of source data
Source_Citation_Abbreviation: SLR Data
Source_Contribution:
Contains sea-level change data used to create point data ingested into the CRL code. Outcomes are based on the 2030, 2050, 2080, and 2100 scenarios.
Source_Information:
Source_Citation:
Citation_Information:
Originator: Jeffrey Danielson
Originator: Dean Tyler
Publication_Date: 2018
Title: Coastal National Elevation Database
Geospatial_Data_Presentation_Form: raster digital data
Online_Linkage: https://www.usgs.gov/core-science-systems/eros/coned
Type_of_Source_Media: Digital
Source_Time_Period_of_Content:
Time_Period_Information:
Single_Date/Time:
Calendar_Date: 2018
Source_Currentness_Reference: publication date
Source_Citation_Abbreviation: CONED
Source_Contribution: Elevation
Source_Information:
Source_Citation:
Citation_Information:
Originator: B.D. Andrews
Originator: W.E. Baldwin
Originator: D.W. Sampson
Originator: W.C. Schwab
Publication_Date: 20191227
Title:
Continuous bathymetry and elevation models of the Massachusetts coastal zone and continental shelf
Edition: Version 3
Geospatial_Data_Presentation_Form: raster digital data
Series_Information:
Series_Name: data release
Issue_Identification: DOI:10.5066/F72806T7
Publication_Information:
Publication_Place: Reston, VA
Publisher: U.S. Geological Survey
Online_Linkage: https://doi.org/10.5066/F72806T7
Type_of_Source_Media: Digital
Source_Time_Period_of_Content:
Time_Period_Information:
Single_Date/Time:
Calendar_Date: 20191227
Source_Currentness_Reference: publication date
Source_Citation_Abbreviation: CZM Topobathy
Source_Contribution: Elevation
Source_Information:
Source_Citation:
Citation_Information:
Originator: Office for Coastal Management
Publication_Date: 2016
Title:
NOAA Office for Coastal Management Sea Level Rise Data: 1-10ft Seal Level Rise Inundation Extent
Geospatial_Data_Presentation_Form: raster digital data
Online_Linkage: https://www.fisheries.noaa.gov/inport/item/48106
Type_of_Source_Media: Digital
Source_Time_Period_of_Content:
Time_Period_Information:
Single_Date/Time:
Calendar_Date: 2016
Source_Currentness_Reference: publication date
Source_Citation_Abbreviation: NOAA SLR Topo
Source_Contribution: Elevation
Process_Step:
Process_Description:
Three input data are required for the CRL model: SLR scenarios, digital elevation model (DEM) data used to generate the Coastal Change Likelihood (CCL) Fabric dataset and land cover data used in the CCL Fabric dataset. Each SLR scenario from Sweet and others (2022) used for this data release was converted into a one-degree raster grid representing the corresponding SLR value. For detailed processing steps used to generate the CCL Fabric dataset, refer to the metadata provided by Pendleton and others (2023) and Sterne and others (2023). This step and the subsequent step were completed by Julia Heslin. Any further steps that mention the use of “tools” or “functions” refer to geoprocessing tools utilized in ArcGIS Pro.
Source_Used_Citation_Abbreviation: SLR Data
Source_Used_Citation_Abbreviation: Fabric
Source_Used_Citation_Abbreviation: CZM Topobathy
Source_Used_Citation_Abbreviation: CONED
Source_Used_Citation_Abbreviation: NOAA SLR Topo
Process_Date: 2024
Process_Contact:
Contact_Information:
Contact_Person_Primary:
Contact_Person: Julia L. Heslin
Contact_Address:
Address_Type: Mailing and Physical
Address: 384 Woods Hole Rd
City: Woods Hole
State_or_Province: MA
Postal_Code: 02543
Contact_Voice_Telephone: 508-548-8700 x2230
Contact_Electronic_Mail_Address: jheslin@usgs.gov
Process_Step:
Process_Description:
To maximize processing efficiency, input data were split into smaller sections and converted to CSV format.
1. First, an extent polygon of the study area is required to split the data into sections. The input land cover raster was converted to a polygon by reclassifying the raster to a single value with the Reclassify tool then inputting that raster in the Raster to Polygon tool.
2. The study area extent polygon was split into 20 sections using the Subdivide Polygon tool in ArcGIS Pro. For each section, the land cover raster was converted to points using the Raster to Point tool. There were approximately 38-39 million points per section.
3. The Extract Multi Value to Point tool was used to extract the elevation and SLR scenarios to the attribute table of the land cover point file.
4. Easting and northing fields are added to the attribute table using the Calculate Geometry tool to determine the X and Y coordinates for each of the points. The attribute tables were then exported as CSV files.
Process_Date: 2024
Process_Step:
Process_Description:
The exported CSV files containing landcover, elevation, and SLR scenarios were run through the newly published CRL code, listed in the cross-reference section of this metadata (https://doi.org/10.5066/P1SQIVEW). For each section, the code outputs shapefile point files in WGS 84 Web Mercator (auxiliary sphere). Code runs were completed by Marie Bartlett and Kathy Weber.
Process_Date: 2024
Process_Contact:
Contact_Information:
Contact_Person_Primary:
Contact_Person: Marie K. Bartlett
Contact_Address:
Address_Type: physical
Address: 384 Woods Hole Rd
City: Woods Hole
State_or_Province: MA
Postal_Code: 02540
Contact_Voice_Telephone: 508-548-8700 x2306
Contact_Electronic_Mail_Address: mbartlett@usgs.gov
Process_Step:
Process_Description:
Remaining post-processing steps were completed by Marie Bartlett using ESRI ArcGIS Pro Version 3.3.0 geospatial software. Steps were automated when possible using the ArcPy package for python programming.
1. Shapefile points for each section were converted to Esri GRIDs using the Point to Raster Conversion tool, and aggregated based on type of output (CR, AE, PAE), year (2030, 2050, 2080, 2100) and scenario (IH, IL) using the Mosaic to New Raster tool.
2. GRIDS were exported to TIFF format using the Export Raster tool and selecting LZW compression to reduce file size while maintaining precision.
3. Probability output values (CR, PAE) were rounded to reflect the accuracy of the source data using the Integer function within an ArcPy script: Int(raster * 100 + 0.5) / 100
Process_Date: 2025
Spatial_Data_Organization_Information:
Direct_Spatial_Reference_Method: Raster
Raster_Object_Information:
Raster_Object_Type: Grid Cell
Row_Count: 127607
Column_Count: 117827
Vertical_Count: 1
Spatial_Reference_Information:
Horizontal_Coordinate_System_Definition:
Planar:
Map_Projection:
Map_Projection_Name: WGS 1984 Web Mercator (auxiliary sphere)
Map_Projection_Parameters:
False_Easting: 0.0
False_Northing: 0.0
Latitude_of_Projection_Origin: 0.0
Longitude_of_Central_Meridian: 0.0
Standard_Parallel: 0.0
Standard_Parallel: 0.0
Planar_Coordinate_Information:
Planar_Coordinate_Encoding_Method: row and column
Coordinate_Representation:
Abscissa_Resolution: 10.0
Ordinate_Resolution: 10.0
Planar_Distance_Units: meters
Geodetic_Model:
Horizontal_Datum_Name: WGS_1984
Ellipsoid_Name: WGS 84
Semi-major_Axis: 6378137.0
Denominator_of_Flattening_Ratio: 298.257223563
Vertical_Coordinate_System_Definition:
Altitude_System_Definition:
Altitude_Datum_Name: North American Vertical Datum of 1988
Altitude_Resolution: 0.01
Altitude_Distance_Units: meters
Altitude_Encoding_Method:
Explicit elevation coordinate included with horizontal coordinates
Entity_and_Attribute_Information:
Overview_Description:
Entity_and_Attribute_Overview:
A companion ArcGIS Pro LayerFile (CR_symbology.lyrx) is intended to be used when viewing each of the Coastal Response (CR) raster outputs for ease of interpretation. A color ramp has been selected to clearly distinguish between response types: orange represents higher probabilities of a dynamic response (values closer to 1), while blue represents higher probabilities of an inundated (static) response (values closer to 0). Colors in the middle of the ramp represent probabilities around 0.5 and indicate areas of greater uncertainty in the model's prediction of coastal response. A specific value of 0.78 has been turned off (not rendered) in the layer file, as this value typically represents deeper water areas below -1 meter in elevation. These areas are often less relevant for end users and have higher associated uncertainty. This decision was made to improve visual clarity and focus on nearshore dynamics. Users may choose to turn this value back on in the symbology settings if desired.
Entity_and_Attribute_Detail_Citation:
This raster dataset does not contain a traditional attribute table. Pixel values represent either probabilistic outcomes or classified elevation bins, as described in the accompanying documentation and metadata. Symbology (.lyrx) files are included to define the display of value ranges and categories. See Lentz and others (2015), and Heslin and others (2024) for more information on the model framework and output descriptions.
Distribution_Information:
Distributor:
Contact_Information:
Contact_Organization_Primary:
Contact_Organization: U.S. Geological Survey - ScienceBase
Contact_Address:
Address_Type: mailing and physical address
Address: Denver Federal Center, Building 810, Mail Stop 302
City: Denver
State_or_Province: CO
Postal_Code: 80225
Country: US
Contact_Voice_Telephone: 1-888-275-8747
Contact_Electronic_Mail_Address: sciencebase@usgs.gov
Resource_Description:
This dataset contains the raster data layer (.tif) and associated files (.tfw, .ovr) needed to view and edit the information it contains, as well as the FGDC CSDGM metadata in XML format. The .lyrx is an ArcGIS Pro LayerFile provided to display the data, the .tfw world file is a text file used to georeference the GeoTIFF, and the .ovr file contains the pyramids used by a GIS to display the data at different scales.
Distribution_Liability:
Unless otherwise stated, all data, metadata and related materials are considered to satisfy the quality standards relative to the purpose for which the data were collected. Although these data and associated metadata have been reviewed for accuracy and completeness and approved for release by the U.S. Geological Survey (USGS), no warranty expressed or implied is made regarding the display or utility of the data on any other system or for general or scientific purposes, nor shall the act of distribution constitute any such warranty.
Standard_Order_Process:
Digital_Form:
Digital_Transfer_Information:
Format_Name: GeoTIFF
Format_Version_Number: ESRI ArcGIS Pro v3.3.0
Transfer_Size: 1000
Digital_Transfer_Option:
Online_Option:
Computer_Contact_Information: Access_Instructions:
The first link is to the USGS publication page, the second link is to the CR child page, and the third link is to the larger work landing page. Because the GeoTIFFs are large (over 1 GB), it is recommended to download each file individually
Fees: None
Metadata_Reference_Information:
Metadata_Date: 20250717
Metadata_Contact:
Contact_Information:
Contact_Organization_Primary:
Contact_Organization: U.S. Geological Survey
Contact_Person: Marie K. Bartlett
Contact_Position: Physical Scientist
Contact_Address:
Address_Type: Mailing and Physical
Address: 384 Woods Hole Rd
City: Woods Hole
State_or_Province: MA
Postal_Code: 02543-1598
Contact_Voice_Telephone: 508-548-8700 x2306
Contact_Electronic_Mail_Address: whsc_data_contact@usgs.gov
Contact_Instructions:
The metadata contact email address is a generic address in the event the metadata author is no longer with the USGS.
Metadata_Standard_Name:
Content Standard for Digital Geospatial Metadata, FGDC-STD-001-1998
Metadata_Standard_Version: FGDC-STD-001.1-1998

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