,This dataset contains a 30-year rolling average of annual average precipitation from the four models and two greenhouse gas (RCP) scenarios included in the four model ensemble for the years 1950-2099. The year identified is the mid-point of the 30-year average. eg. The year 2050 includes the values from 2036 to 2065.,The downscaling and selection of models for inclusion in ten and four model ensembles is described in Pierce et al. 2018, but summarized here. Thirty two global climate models (GCMs) were identified to meet the modeling requirements. From those, ten that closely simulate California’s climate were selected for additional analysis (Table 1, Pierce et al. 2018) and to form a ten model ensemble. From the ten model ensemble, four models, forming a four model ensemble, were identified to provide coverage of the range of potential climate outcomes in California. The models in the four model ensemble and their general climate projection for California are:,,,These data were downloaded from Cal-Adapt and prepared for use within CA Nature by California Natural Resource Agency and ESRI staff.,Cal-Adapt. (2018). LOCA Derived Data [GeoTIFF]. Data derived from LOCA Downscaled CMIP5 Climate Projections. Cal-Adapt website developed by University of California at Berkeley’s Geospatial Innovation Facility under contract with the California Energy Commission. Retrieved from https://cal-adapt.org/,Pierce, D. W., J. F. Kalansky, and D. R. Cayan, (Scripps Institution of Oceanography). 2018. Climate, Drought, and Sea Level Rise Scenarios for the Fourth California Climate Assessment. California’s Fourth Climate Change Assessment, California Energy Commission. Publication Number: CNRA-CEC-2018-006.,

This dataset includes model projections of seasonal temperature (T), precipitation (P), and runoff (R) from 214 climate simulations from coupled model intercomparison project (CMIP) 3 and CMIP5 scenarios for 19-year periods centered on 2030, 2060, and 2090. The summaries of the climate model projections are presented as percentiles (5th, 25th, 50th, 75th, and 95th) of seasonal (October through March, January through March, April through June, and July through September) changes in T, P, and R for the 214 climate models. The metrics are calculated from variables previously summarized across the conterminous United States for hydrologic response units of the Geospatial Fabric for National Hydrologic Modeling (Viger and Bock, 2014). T, P, and R were previously derived using a monthly water balance model (Bock and others, 2016; 2017). Names, sources, and references of the climate inputs are described in Bock and others (2017).

Originators: US Environmental Protection Agency Publisher: US EPA Office of Research & Development (ORD) - National Health and Environmental Effects Research Laboratory (NHEERL) Publication place: Corvallis, OR Publication date: Time Period of Data: 1900-2010; Projected data for 2041-2070. Data location: GeoPlatform ("https://www.geoplatform.gov/") and EPA Environmental Dataset Gateway (https://edg.epa.gov/). Abstract: We apply the hydrologic landscapes (HL) concept to assess the hydrologic vulnerability of the western United States (U.S.) to projected climate conditions. Our goal is to understand the potential impacts for stakeholder-defined interests across large geographic areas. The basic assumption of the HL approach is that catchments that share similar physical and climatic characteristics are expected to have similar hydrologic characteristics. We map climate vulnerability by integrating the HL approach into a retrospective analysis of historical data to assess variability in future climate projections and hydrology, which includes temperature, precipitation, potential evapotranspiration, snow accumulation, climatic moisture, surplus water, and seasonality of water surplus. Projections that are not within two-standard deviations of the historical decadal average contribute to the vulnerability index for each metric. The resulting vulnerability maps show that temperature and potential evapotranspiration are consistently projected to have high vulnerability indices for the western U.S. Precipitation vulnerability is not as spatially-uniform as temperature. The highest elevation areas with snow are projected to experience significant changes in snow accumulation. The seasonality vulnerability map shows that specific mountainous areas in the West are most prone to changes in seasonality, whereas many transitional terrains are moderately susceptible. This paper illustrates how the HL approach can help assess climatic and hydrologic vulnerability across large spatial scales. By combining the HL concept and climate vulnerability analyses, we provide a planning approach that could allow resource managers to consider how future climate conditions may impact important economic and conservation resources. Purpose: These data were created in support of the US EPA’s ACE CIVA 2.3, Task Project (QAPP: E-WED-0030854). However, these climate data and hydrologic landscape summaries should have broad applicability for hydrological, geomorphic, or ecological modeling, management, and restoration. This raster contains the modeled change in the seasonality of the month of maximum surplus precipitation between the target time period (in title) and the 1971-2000 Normal period (1 = same season, 0 = earlier season, 2 = later season).

Originators: US Environmental Protection Agency Publisher: US EPA Office of Research & Development (ORD) - National Health and Environmental Effects Research Laboratory (NHEERL) Publication place: Corvallis, OR Publication date: Time Period of Data: 1900-2010; Projected data for 2041-2070. Data location: GeoPlatform ("https://www.geoplatform.gov/") and EPA Environmental Dataset Gateway (https://edg.epa.gov/). Abstract: We apply the hydrologic landscapes (HL) concept to assess the hydrologic vulnerability of the western United States (U.S.) to projected climate conditions. Our goal is to understand the potential impacts for stakeholder-defined interests across large geographic areas. The basic assumption of the HL approach is that catchments that share similar physical and climatic characteristics are expected to have similar hydrologic characteristics. We map climate vulnerability by integrating the HL approach into a retrospective analysis of historical data to assess variability in future climate projections and hydrology, which includes temperature, precipitation, potential evapotranspiration, snow accumulation, climatic moisture, surplus water, and seasonality of water surplus. Projections that are not within two-standard deviations of the historical decadal average contribute to the vulnerability index for each metric. The resulting vulnerability maps show that temperature and potential evapotranspiration are consistently projected to have high vulnerability indices for the western U.S. Precipitation vulnerability is not as spatially-uniform as temperature. The highest elevation areas with snow are projected to experience significant changes in snow accumulation. The seasonality vulnerability map shows that specific mountainous areas in the West are most prone to changes in seasonality, whereas many transitional terrains are moderately susceptible. This paper illustrates how the HL approach can help assess climatic and hydrologic vulnerability across large spatial scales. By combining the HL concept and climate vulnerability analyses, we provide a planning approach that could allow resource managers to consider how future climate conditions may impact important economic and conservation resources. Purpose: These data were created in support of the US EPA’s ACE CIVA 2.3, Task Project (QAPP: E-WED-0030854). However, these climate data and hydrologic landscape summaries should have broad applicability for hydrological, geomorphic, or ecological modeling, management, and restoration. This raster contains the modeled change in the seasonality of the month of maximum surplus precipitation between the target time period (in title) and the 1971-2000 Normal period (1 = same season, 0 = earlier season, 2 = later season).

Originators: US Environmental Protection Agency Publisher: US EPA Office of Research & Development (ORD) - National Health and Environmental Effects Research Laboratory (NHEERL) Publication place: Corvallis, OR Publication date: Time Period of Data: 1900-2010; Projected data for 2041-2070. Data location: GeoPlatform ("https://www.geoplatform.gov/") and EPA Environmental Dataset Gateway (https://edg.epa.gov/). Abstract: We apply the hydrologic landscapes (HL) concept to assess the hydrologic vulnerability of the western United States (U.S.) to projected climate conditions. Our goal is to understand the potential impacts for stakeholder-defined interests across large geographic areas. The basic assumption of the HL approach is that catchments that share similar physical and climatic characteristics are expected to have similar hydrologic characteristics. We map climate vulnerability by integrating the HL approach into a retrospective analysis of historical data to assess variability in future climate projections and hydrology, which includes temperature, precipitation, potential evapotranspiration, snow accumulation, climatic moisture, surplus water, and seasonality of water surplus. Projections that are not within two-standard deviations of the historical decadal average contribute to the vulnerability index for each metric. The resulting vulnerability maps show that temperature and potential evapotranspiration are consistently projected to have high vulnerability indices for the western U.S. Precipitation vulnerability is not as spatially-uniform as temperature. The highest elevation areas with snow are projected to experience significant changes in snow accumulation. The seasonality vulnerability map shows that specific mountainous areas in the West are most prone to changes in seasonality, whereas many transitional terrains are moderately susceptible. This paper illustrates how the HL approach can help assess climatic and hydrologic vulnerability across large spatial scales. By combining the HL concept and climate vulnerability analyses, we provide a planning approach that could allow resource managers to consider how future climate conditions may impact important economic and conservation resources. Purpose: These data were created in support of the US EPA’s ACE CIVA 2.3, Task Project (QAPP: E-WED-0030854). However, these climate data and hydrologic landscape summaries should have broad applicability for hydrological, geomorphic, or ecological modeling, management, and restoration. This raster contains the modeled change in the seasonality of the month of maximum surplus precipitation between the target time period (in title) and the 1971-2000 Normal period (1 = same season, 0 = earlier season, 2 = later season).

Originators: US Environmental Protection Agency Publisher: US EPA Office of Research & Development (ORD) - National Health and Environmental Effects Research Laboratory (NHEERL) Publication place: Corvallis, OR Publication date: Time Period of Data: 1900-2010; Projected data for 2041-2070. Data location: GeoPlatform ("https://www.geoplatform.gov/") and EPA Environmental Dataset Gateway (https://edg.epa.gov/). Abstract: We apply the hydrologic landscapes (HL) concept to assess the hydrologic vulnerability of the western United States (U.S.) to projected climate conditions. Our goal is to understand the potential impacts for stakeholder-defined interests across large geographic areas. The basic assumption of the HL approach is that catchments that share similar physical and climatic characteristics are expected to have similar hydrologic characteristics. We map climate vulnerability by integrating the HL approach into a retrospective analysis of historical data to assess variability in future climate projections and hydrology, which includes temperature, precipitation, potential evapotranspiration, snow accumulation, climatic moisture, surplus water, and seasonality of water surplus. Projections that are not within two-standard deviations of the historical decadal average contribute to the vulnerability index for each metric. The resulting vulnerability maps show that temperature and potential evapotranspiration are consistently projected to have high vulnerability indices for the western U.S. Precipitation vulnerability is not as spatially-uniform as temperature. The highest elevation areas with snow are projected to experience significant changes in snow accumulation. The seasonality vulnerability map shows that specific mountainous areas in the West are most prone to changes in seasonality, whereas many transitional terrains are moderately susceptible. This paper illustrates how the HL approach can help assess climatic and hydrologic vulnerability across large spatial scales. By combining the HL concept and climate vulnerability analyses, we provide a planning approach that could allow resource managers to consider how future climate conditions may impact important economic and conservation resources. Purpose: These data were created in support of the US EPA’s ACE CIVA 2.3, Task Project (QAPP: E-WED-0030854). However, these climate data and hydrologic landscape summaries should have broad applicability for hydrological, geomorphic, or ecological modeling, management, and restoration. This raster contains the modeled change in the seasonality of the month of maximum surplus precipitation between the target time period (in title) and the 1971-2000 Normal period (1 = same season, 0 = earlier season, 2 = later season).

Originators: US Environmental Protection Agency Publisher: US EPA Office of Research & Development (ORD) - National Health and Environmental Effects Research Laboratory (NHEERL) Publication place: Corvallis, OR Publication date: Time Period of Data: 1900-2010; Projected data for 2041-2070. Data location: GeoPlatform ("https://www.geoplatform.gov/") and EPA Environmental Dataset Gateway (https://edg.epa.gov/). Abstract: We apply the hydrologic landscapes (HL) concept to assess the hydrologic vulnerability of the western United States (U.S.) to projected climate conditions. Our goal is to understand the potential impacts for stakeholder-defined interests across large geographic areas. The basic assumption of the HL approach is that catchments that share similar physical and climatic characteristics are expected to have similar hydrologic characteristics. We map climate vulnerability by integrating the HL approach into a retrospective analysis of historical data to assess variability in future climate projections and hydrology, which includes temperature, precipitation, potential evapotranspiration, snow accumulation, climatic moisture, surplus water, and seasonality of water surplus. Projections that are not within two-standard deviations of the historical decadal average contribute to the vulnerability index for each metric. The resulting vulnerability maps show that temperature and potential evapotranspiration are consistently projected to have high vulnerability indices for the western U.S. Precipitation vulnerability is not as spatially-uniform as temperature. The highest elevation areas with snow are projected to experience significant changes in snow accumulation. The seasonality vulnerability map shows that specific mountainous areas in the West are most prone to changes in seasonality, whereas many transitional terrains are moderately susceptible. This paper illustrates how the HL approach can help assess climatic and hydrologic vulnerability across large spatial scales. By combining the HL concept and climate vulnerability analyses, we provide a planning approach that could allow resource managers to consider how future climate conditions may impact important economic and conservation resources. Purpose: These data were created in support of the US EPA’s ACE CIVA 2.3, Task Project (QAPP: E-WED-0030854). However, these climate data and hydrologic landscape summaries should have broad applicability for hydrological, geomorphic, or ecological modeling, management, and restoration. This raster contains the modeled change in the seasonality of the month of maximum surplus precipitation between the target time period (in title) and the 1971-2000 Normal period (1 = same season, 0 = earlier season, 2 = later season).

This digital dataset contains the gridded future climate data for the same modeled extent as the Paso Robles Groundwater Basin Model (GEOSCIENCE and Todd Groundwater, 2015). The monthly climate data for the Paso Robles Hydrologic Model are based on the Salinas and Carmel River Basins Study (SCRBS) future climate scenarios (Henson and others, 2024). SCRBS considers one baseline climate scenario that represents recent historical climate conditions and five future climate scenarios: Hot-Wet (HW), Warm-Wet (WW), Hot-Dry (HD), Warm-Dry (WD), and Central Tendency (CT) (Henson and others, 2024). To develop the monthly climate grids, the regional climate data was resampled to a monthly timescale and area weighted to the model grid. The climate data includes spatially distributed monthly precipitation and potential evapotranspiration for the model grid for January 2016 to December 2099.

This data release contains monthly 270-meter resolution Basin Characterization Model (BCMv8) climate and hydrologic variables for Localized Constructed Analog (LOCA; Pierce et al., 2014)-downscaled HadGEM2-ES Global Climate Model (GCM) for Representative Concentration Pathway (RCP) 4.5 (medium-low emissions) and 8.5 (high emissions) for hydrologic California. The LOCA climate scenarios span water years 1950 to 2099 with greenhouse-gas forcings beginning in 2006. The LOCA downscaling method has been shown to produce better estimates of extreme events and reduces the common downscaling problem of too many low-precipitation days (Pierce et al., 2014). Ten GCMs were selected from the full ensemble of models from the fifth Coupled Model Intercomparison Project from the World Climate Research Programme (CMIP5) based on GCM historical performance to address specific needs for California water-resource planning (California Department of Water Resources Climate Change Technical Advisory Group, 2015). The 10 GCMs with RCP 4.5 and 8.5 each were statistically downscaled using the LOCA method (Pierce et al., 2014) from 2-degree (approximately 222-kilometer; km) quadrangles to 6-km resolution. Next, the scenarios were spatially downscaled from 6 km to 270 meters (Flint and Flint, 2012) and run through the BCMv8 using the same model parameters and input files as the historical BCM model (BCMv8; Flint et al., 2021). Downscaled gridded climate variables include precipitation (ppt), minimum temperature (tmn), maximum temperature (tmx), and potential evapotranspiration (pet). Gridded hydrologic variables include: actual evapotranspiration (aet), climatic water deficit (cwd), snowpack (pck), recharge (rch), runoff (run), and soil storage (str). The units for temperature variables are degrees Celsius, and all other variables are in millimeters per month. Monthly variables from water years 1951 to 2099 are summarized into water year files (for example, water year 1951 includes October 1950 - September 1951) and 30-year average summaries from 1951 to 2099. Raster grids are in the NAD83 California Teale Albers, (meters) projection in an open format ascii text file (*.asc). This data release includes a child item for each RCP (4.5 & 8.5) for the HadGEM2-ES GCM. Each RCP child item contains 4 child items: 1. 30-year summaries (Water year files averaged for selected 30-year periods, zipped by variable) 2. Monthly BCM hydrology variables (monthly BCM hydrology variables zipped by decade) 3. Monthly climate variables (monthly climate variables zipped by decade) 4. Water year summaries (monthly files summed (aet, cwd, pck, rch, run, str, pet, and ppt) or averaged (tmn and tmx) by water year, zipped by variable) References cited: California Department of Water Resources Climate Change Technical Advisory Group, 2015, Perspectives and guidance for climate change analysis: Sacramento, Calif., California Department of Water Resources Technical Information Record, 142 p. Flint, L.E., Flint, A.L., and Stern, M.A., 2021, The Basin Characterization Model - A monthly regional water balance software package (BCMv8) data release and model archive for hydrologic California (ver. 3.0, June 2023): U.S. Geological Survey data release, https://doi.org/10.5066/P9PT36UI. Flint, L.E., and Flint, A.L., 2012, Downscaling future climate scenarios to fine scales for hydrologic and ecological modeling and analysis: Ecological Processes, v. 1, no. 2, 15 p., https://doi.org/10.1186/2192-1709-1-2. Pierce, D.W., Cayan, D.R. and Thrasher, B.L., 2014. Statistical downscaling using localized constructed analogs (LOCA). Journal of hydrometeorology, 15(6), pp.2558-2585.