This annual data was accessed from the PRISM project website (https://https://prism.oregonstate.edu/normals_other/public/pacisl/grids/) and has a spatial resolution of 3 arcsec (80 m). The three climatic variables included in the dataset are total precipitation (inches), maximum temperature (degrees Fahrenheit), and minimum temperature (degrees Fahrenheit). PRISM Climate Group at Oregon State University used climate observations from monitoring stations and interpolated to a gridded format using the PRISM model (Parameter-elevation Regressions on Independent Slopes Model). Interpolation was trained using a DEM (digital elevation model) to improve performance in mountainous regions. The PRISM temperature data were originally reported in °C but were converted to °F. The PRISM precipitation data were originally reported in millimeters but were converted to inches. For this project, Tutuila and Manua island domains were merged into one spatial domain for American Samoa using the "Mosaic to New Raster" tool in ArcGIS Pro. This dataset was processed by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets). From Original PRISM Metadata (https://prism.oregonstate.edu/normals_other/public/pacisl/metadata/): Abstract: This data set contains spatially gridded average monthly and annual precipitation and temperature for the climatological period 1971–2000. Distribution of the point measurements to a spatial grid was accomplished using the PRISM model, developed by Chris Daly of the PRISM Group, OSU. Purpose: Display and/or analyses requiring spatially distributed monthly or annual precipitation and temperature for the climatological period 1971–2000 Supplementary Information: There are many methods of interpolating climate from monitoring stations to grid points. Some provide estimates of acceptable accuracy in flat terrain, but few have been able to adequately explain the extreme, complex variations in climate that occur in mountainous regions. Significant progress in this area has been achieved through the development of PRISM (Parameter-elevation Regressions on Independent Slopes Model). PRISM is an analytical model that uses point data for a 30 yr climatological average (e.g. 1971- 2000 average) and an underlying grid such as a digital elevation model (DEM) to generate gridded estimates of monthly and annual precipitation and temperature (as well as other climatic parameters). PRISM is well suited to regions with mountainous terrain, because it incorporates a conceptual framework that addresses the spatial scale and pattern of orographic processes. Grids were modeled on a monthly basis. Annual grids of temperature were produced by averaging the monthly grids, and summing for precipitation. Reports and papers on PRISM can be obtained from the PRISM Group website Completeness Report: Point estimates of precipitation and temperature originated from some or all of the following sources: 1) National Weather Service (NWS) Cooperative (COOP) stations, 2) Natural Resources Conservation Service (NRCS) SNOTEL, 3) United States Forest Service (USFS) and Bureau of Land Management (BLM) RAWS Stations, 4) Bureau of Reclemation (AGRIMET) stations, 5) California Data Exchange Center (CDEC) stations, 6) Storage guages, 7) NRCS Snowcourse stations, 8) Other State and local station networks, 9) Estimated station data, 10) Canadian stations, 11) Upper air stations, and 12) NWS/Federal Aviation Administration

This annual data was accessed from the PRISM project website (https://https://prism.oregonstate.edu/normals_other/public/pacisl/grids/) and has a spatial resolution of 15 arcsec (400 m). The three climatic variables included in the dataset are total precipitation (inches), maximum temperature (degrees Fahrenheit), and minimum temperature (degrees Fahrenheit). PRISM Climate Group at Oregon State University used climate observations from monitoring stations and interpolated to a gridded format using the PRISM model (Parameter-elevation Regressions on Independent Slopes Model). Interpolation was trained using a DEM (digital elevation model) to improve performance in mountainous regions. The PRISM temperature data were originally reported in °C but were converted to °F. The PRISM precipitation data were originally reported in millimeters but were converted to inches. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets). From Original PRISM Metadata (https://prism.oregonstate.edu/normals_other/public/pacisl/metadata/): Abstract: This data set contains spatially gridded average monthly and annual precipitation and temperature for the climatological period 1971–2000. Distribution of the point measurements to a spatial grid was accomplished using the PRISM model, developed by Chris Daly of the PRISM Group, OSU. Purpose: Display and/or analyses requiring spatially distributed monthly or annual precipitation and temperature for the climatological period 1971–2000 Supplementary Information: There are many methods of interpolating climate from monitoring stations to grid points. Some provide estimates of acceptable accuracy in flat terrain, but few have been able to adequately explain the extreme, complex variations in climate that occur in mountainous regions. Significant progress in this area has been achieved through the development of PRISM (Parameter-elevation Regressions on Independent Slopes Model). PRISM is an analytical model that uses point data for a 30 yr climatological average (e.g. 1971- 2000 average) and an underlying grid such as a digital elevation model (DEM) to generate gridded estimates of monthly and annual precipitation and temperature (as well as other climatic parameters). PRISM is well suited to regions with mountainous terrain, because it incorporates a conceptual framework that addresses the spatial scale and pattern of orographic processes. Grids were modeled on a monthly basis. Annual grids of temperature were produced by averaging the monthly grids, and summing for precipitation. Reports and papers on PRISM can be obtained from the PRISM Group website Completeness Report: Point estimates of precipitation and temperature originated from some or all of the following sources: 1) National Weather Service (NWS) Cooperative (COOP) stations, 2) Natural Resources Conservation Service (NRCS) SNOTEL, 3) United States Forest Service (USFS) and Bureau of Land Management (BLM) RAWS Stations, 4) Bureau of Reclemation (AGRIMET) stations, 5) California Data Exchange Center (CDEC) stations, 6) Storage guages, 7) NRCS Snowcourse stations, 8) Other State and local station networks, 9) Estimated station data, 10) Canadian stations, 11) Upper air stations, and 12) NWS/Federal Aviation Administration (FAA) Automated surface observation stations (ASOS). All COOP station data were subjected to quality control checks by the National Climatic Data Center (NCDC).

This dataset was assembled using statistically downscaled climate projections from the NASA Earth Exchange-Global Daily Downscaled Projections (NEX-GDDP) project. These climate change scenarios have been developed using global climate models (GCMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6) and four different future scenarios, known as Shared Socioeconomic Pathways (SSPs). The four SSPs involved in this project are SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5. The raw NEX-GDDP-CMIP6 data has a spatial resolution of 0.25 degrees and a daily temporal resolution. The NEX-GDDP-CMIP6 data was processed to calculate change in climatic variables for each season (fall, spring, summer, winter) and annually for 30-year periods. The five period comparisons available in the dataset are as follows: 1976-2005 to 2025-2054, 1976-2005 to 2045-2074, 1976-2005 to 2070-2099, 2025-2054 to 2045 to 2074, and 2025-2054 to 2070 to 2099. The six climatic variables included in the dataset are change in: total precipitation [in], total precipitation [%], total potential evapotranspiration [in], total potential evapotranspiration [%], maximum temperature [degF], and minimum temperature [degF]. This data was then used to produce an ensemble median of all available NEX-GDDP downscaled GCMs for each variable. Not all GCMs downscaled in NEX-GDDP had availability for every variable and scenario combination. The ensemble data was summarized by HUC-12 feature classes described above. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheets (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

This dataset was assembled using statistically downscaled climate projections from the NASA Earth Exchange-Global Daily Downscaled Projections (NEX-GDDP) project. These climate change scenarios have been developed using global climate models (GCMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6) and four different future scenarios, known as Shared Socioeconomic Pathways (SSPs). The four SSPs involved in this project are SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5. The raw NEX-GDDP-CMIP6 data has a spatial resolution of 0.25 degrees and a daily temporal resolution. The NEX-GDDP-CMIP6 data was processed to calculate change in climatic variables for each season (fall, spring, summer, winter) and annually for 30-year periods. The five period comparisons available in the dataset are as follows: 1976-2005 to 2025-2054, 1976-2005 to 2045-2074, 1976-2005 to 2070-2099, 2025-2054 to 2045 to 2074, and 2025-2054 to 2070 to 2099. The six climatic variables included in the dataset are change in: total precipitation [in], total precipitation [%], total potential evapotranspiration [in], total potential evapotranspiration [%], maximum temperature [degF], and minimum temperature [degF]. This data was then used to produce an ensemble median of all available NEX-GDDP downscaled GCMs for each variable. Not all GCMs downscaled in NEX-GDDP had availability for every variable and scenario combination. The ensemble data was summarized by HUC-12 feature classes described above. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheets (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

This annual data was accessed from the PRISM project website (https://prism.oregonstate.edu/normals/) and has a spatial resolution of 30 arcsec (800 m). The three climatic variables included in the dataset are total precipitation (inches), maximum temperature (degrees Fahrenheit), and minimum temperature (degrees Fahrenheit). PRISM Climate Group at Oregon State University used climate observations from monitoring stations and interpolated to a gridded format using the PRISM model (Parameter-elevation Regressions on Independent Slopes Model). Interpolation was trained using a DEM (digital elevation model) to improve performance in mountainous regions. The PRISM temperature data were originally reported in °C but were converted to °F. The PRISM precipitation data were originally reported in millimeters but were converted to inches. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets). From Original Metadata (https://prism.oregonstate.edu/normals/): Abstract: Monthly 30-year "normal" dataset covering the conterminous U.S., averaged over the climatological period 1991–2020. Contains spatially gridded average annual total precipitation and temperature at 4km grid cell resolution. Distribution of the point measurements to the spatial grid was accomplished using the PRISM model, developed and applied by Dr. Christopher Daly of the PRISM Climate Group at Oregon State University. This dataset is available free-of-charge on the PRISM website. Purpose: Display and/or analysis requiring spatially distributed annual total precipitation and temperature for the climatological period 1991–2020. Supplementary Information: There are many methods of interpolating climate from monitoring stations to grid points. Some provide estimates of acceptable accuracy in flat terrain, but few have been able to adequately explain the extreme, complex variations in climate that occur in mountainous regions. Significant progress in this area has been achieved through the development of PRISM (Parameter-elevation Regressions on Independent Slopes Model). PRISM is an analytical model that uses point data and an underlying grid such as a digital elevation model (DEM) or a 30 yr climatological average to generate gridded estimates of monthly or annual precipitation and temperature (as well as other climatic parameters). PRISM is well suited to regions with mountainous terrain, because it incorporates a conceptual framework that addresses the spatial scale and pattern of orographic processes. Grids were modeled on a monthly basis. Annual grids were produced by averaging (temperatures, dew point, vapor pressure deficit, and solar radiation) or summing (precipitation) the monthly grids. These gridded normals supersede the 1991–2020 normals produced in October 2021. Improvements over the previous version include more stable adjustments of short-period station data to represent the 1991–2020 period, and additional quality control measures.

This dataset was assembled using statistically downscaled climate projections from the NASA Earth Exchange-Global Daily Downscaled Projections (NEX-GDDP) project. These climate change scenarios have been developed using global climate models (GCMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6) and four different future scenarios, known as Shared Socioeconomic Pathways (SSPs). The four SSPs involved in this project are SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5. The raw NEX-GDDP-CMIP6 data has a spatial resolution of 0.25 degrees and a daily temporal resolution. The NEX-GDDP-CMIP6 data was processed to calculate change in climatic variables for each season (fall, spring, summer, winter) and annually for 30-year periods. The five period comparisons available in the dataset are as follows: 1976-2005 to 2025-2054, 1976-2005 to 2045-2074, 1976-2005 to 2070-2099, 2025-2054 to 2045 to 2074, and 2025-2054 to 2070 to 2099. The six climatic variables included in the dataset are change in: total precipitation [in], total precipitation [%], total potential evapotranspiration [in], total potential evapotranspiration [%], maximum temperature [degF], and minimum temperature [degF]. This data was then used to produce an ensemble median of all available NEX-GDDP downscaled GCMs for each variable. Not all GCMs downscaled in NEX-GDDP had availability for every variable and scenario combination. The ensemble data was summarized by HUC-12 feature classes described above. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheets (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

This dataset was assembled using statistically downscaled climate projections from the NASA Earth Exchange-Global Daily Downscaled Projections (NEX-GDDP) project. These climate change scenarios have been developed using global climate models (GCMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6) and four different future scenarios, known as Shared Socioeconomic Pathways (SSPs). The four SSPs involved in this project are SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5. The raw NEX-GDDP-CMIP6 data has a spatial resolution of 0.25 degrees and a daily temporal resolution. The NEX-GDDP-CMIP6 data was processed to calculate change in climatic variables for each season (fall, spring, summer, winter) and annually for 30-year periods. The five period comparisons available in the dataset are as follows: 1976-2005 to 2025-2054, 1976-2005 to 2045-2074, 1976-2005 to 2070-2099, 2025-2054 to 2045 to 2074, and 2025-2054 to 2070 to 2099. The six climatic variables included in the dataset are change in: total precipitation [in], total precipitation [%], total potential evapotranspiration [in], total potential evapotranspiration [%], maximum temperature [degF], and minimum temperature [degF]. This data was then used to produce an ensemble median of all available NEX-GDDP downscaled GCMs for each variable. Not all GCMs downscaled in NEX-GDDP had availability for every variable and scenario combination. The ensemble data was summarized by HUC-12 feature classes described above. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheets (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

This annual data was accessed from the PRISM project website (https://prism.oregonstate.edu/normals_other/public/pacisl/grids/) and has a spatial resolution of 3 arcsec (80 m). The three climatic variables included in the dataset are total precipitation (inches), maximum temperature (degrees Fahrenheit), and minimum temperature (degrees Fahrenheit). PRISM Climate Group at Oregon State University used climate observations from monitoring stations and interpolated to a gridded format using the PRISM model (Parameter-elevation Regressions on Independent Slopes Model). Interpolation was trained using a DEM (digital elevation model) to improve performance in mountainous regions. The PRISM temperature data were originally reported in °C but were converted to °F. The PRISM precipitation data were originally reported in millimeters but were converted to inches. For this project, Guam and CNMI domains were merged into one spatial domain using the "Mosaic to New Raster" tool in ArcGIS Pro. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets). From Original PRISM Metadata (https://prism.oregonstate.edu/normals_other/public/pacisl/metadata/): Abstract: This data set contains spatially gridded average monthly and annual precipitation and temperature for the climatological period 1971–2000. Distribution of the point measurements to a spatial grid was accomplished using the PRISM model, developed by Chris Daly of the PRISM Group, OSU. Purpose: Display and/or analyses requiring spatially distributed monthly or annual precipitation and temperature for the climatological period 1971–2000 Supplementary Information: There are many methods of interpolating climate from monitoring stations to grid points. Some provide estimates of acceptable accuracy in flat terrain, but few have been able to adequately explain the extreme, complex variations in climate that occur in mountainous regions. Significant progress in this area has been achieved through the development of PRISM (Parameter-elevation Regressions on Independent Slopes Model). PRISM is an analytical model that uses point data for a 30 yr climatological average (e.g. 1971- 2000 average) and an underlying grid such as a digital elevation model (DEM) to generate gridded estimates of monthly and annual precipitation and temperature (as well as other climatic parameters). PRISM is well suited to regions with mountainous terrain, because it incorporates a conceptual framework that addresses the spatial scale and pattern of orographic processes. Grids were modeled on a monthly basis. Annual grids of temperature were produced by averaging the monthly grids, and summing for precipitation. Reports and papers on PRISM can be obtained from the PRISM Group website Completeness Report: Point estimates of precipitation and temperature originated from some or all of the following sources: 1) National Weather Service (NWS) Cooperative (COOP) stations, 2) Natural Resources Conservation Service (NRCS) SNOTEL, 3) United States Forest Service (USFS) and Bureau of Land Management (BLM) RAWS Stations, 4) Bureau of Reclemation (AGRIMET) stations, 5) California Data Exchange Center (CDEC) stations, 6) Storage guages, 7) NRCS Snowcourse stations, 8) Other State and local station networks, 9) Estimated station data, 10) Canadian stations, 11) Upper air stations, and 12) NWS/Federal Aviation Administration (FAA) Automated surface observation

This dataset was created by USGS and is being hosted by US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets). The original raster dataset has additional categories to differentiate between permafrost probability areas and other land cover categories. In the USGS raster, values range from 0 to 105, with values above 100 representing the following: 101 = open water; 102 = perennial ice/snow; 103 = developed; 104 = barren, and; 105 = cultivated areas. These values has been modified by the EnviroAtlas team to change values above 100 to "-1" to produce a dataset with modeled likelihood values ranging from 0 to 100 only. Abstract: Pastick et al., 2015 : "This medium resolution (i.e. 30-m pixels) spatial dataset provides an estimate of the occurrence of near-surface (within 1 m of the ground surface) permafrost in Alaska. The dataset was developed using a decision-tree model that statistically and spatially extended late-season field observations (n ~ 17,000) using remotely sensed imagery, climatic data, and thematic maps of a wide range of surface and subsurface biophysical characteristics. To circumvent the use of seasonal frost observations, only thaw-depth measurements taken during late-season months (late July to mid-September) or measurements designated to have no near-surface (within 1m) permafrost were used for model calibration and validation. Individual pixel values represent the probability of encountering near-surface permafrost (i.e. 0 to 100 %), as derived from a tree ensemble model, and pixel values greater than 100 correspond to masked land cover types (i.e. 101 = open water; 102 = perennial ice/snow; 103 = developed; 104 = barren, and; 105 = cultivated areas) as defined by the 2001 National Land Cover Database. Decision tree models and resultant maps were tested using independent field observations and f-fold cross validations, which indicated that the map product has an overall accuracy of approximately 85 % when using a probability threshold of 50 % (i.e. less than 50 % = near-surface permafrost absent; greater than or equal to 50 % = near-surface permafrost present)" Pastick, N. J., Jorgenson, M. T., Wylie, B. K., Nield, S. J., Johnson, K. D., & Finley, A. O. (2015). Distribution of near-surface permafrost in Alaska: Estimates of present and future conditions. Remote Sensing of Environment, 168, 301-315. https://doi.org/10.1016/j.rse.2015.07.019

The EnviroAtlas Climate Scenarios were generated from NASA Earth Exchange (NEX) Downscaled Climate Projections (NEX-DCP30) ensemble averages (the average of over 30 available climate models) for each of the four representative concentration pathways (RCP) for the contiguous U.S. at 30 arc-second (approx. 800 m2) spatial resolution. NEX-DCP30 mean monthly minimum temperature for the 4 RCPs (2.6, 4.5, 6.0, 8.5) were organized by season (Winter, Spring, Summer, and Fall) and annually for the years 2006 – 2099. Additionally, mean monthly minimum temperature for the ensemble average of all historic runs is organized similarly for the years 1950 – 2005. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://cds.nccs.nasa.gov/nex/) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).