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: https://www.sciencebase.gov/catalog/item/6811381bd4be0276ecc84958 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: https://www.sciencebase.gov/catalog/item/681134d7d4be0276ecc84941 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: https://www.sciencebase.gov/catalog/file/get/6811381bd4be0276ecc84958?name=CR_NE_Graphic.jpg&allowOpen=true 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: https://www.sciencebase.gov/catalog/item/61781f88d34e4c6b7fe2a444 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: https://earth.gov/sealevel/us/internal_resources/756/noaa-nos-techrpt01-global-regional-SLR-scenarios-US.pdf 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: Network_Address: Network_Resource_Name: https://doi.org/10.5066/P13JKJUT Network_Resource_Name: https://www.sciencebase.gov/catalog/item/6811381bd4be0276ecc84958 Network_Resource_Name: https://www.sciencebase.gov/catalog/item/681134d7d4be0276ecc84941 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