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Terrestrial Condition Assessment (TCA) Climate Exposure Precipitation Summer Percent (Map Service)
The percent difference in Summer precipitation (in) between the reference time period of 1900-2014 and the current time period 2015-2019. Summer months include June, July, August. Data used are sourced from PRISM, Oregon State University. Data were summarized at the Subsection scale of the USFS National Hierarchy of Ecological Units and applied to the corresponding LTA.
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Terrestrial Condition Assessment (TCA) Climate Exposure Temperature Fall (Map Service)
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The difference in Fall temperature (F) between the reference time period of 1900-2014 and the current time period 2015-2019. Fall months include September, October, and November. Data used are sourced from PRISM, Oregon State University. Data were summarized at the Subsection scale of the USFS National Hierarchy of Ecological Units and applied to the corresponding LTA.
Terrestrial Condition Assessment (TCA) Climate Exposure Precipitation Winter Percent (Map Service)
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The percent difference in Winter precipitation (in) between the reference time period of 1900-2014 and the current time period 2015-2019. Winter months include December, January, and February. Data used are sourced from PRISM, Oregon State University. Data were summarized at the Subsection scale of the USFS National Hierarchy of Ecological Units and applied to the corresponding LTA.
Terrestrial Condition Assessment (TCA) Alaska Climate Exposure Temperature Spring (Map Service)
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The difference in Spring temperature (F) between the reference time period of 1980-2014 and the current time period 2015-2019. Winter months include March, April, and May. Data used are sourced from DAYMET, Daily Surface Weather and Climatological Summaries, Oak Ridge National Laboratory. Data were summarized at the Subsection scale of the USFS National Hierarchy of Ecological Units and applied to the corresponding LTA.
Terrestrial Condition Assessment (TCA) Climate Exposure Precipitation Percent (Image Service)
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Modeled change in the Seasonality between 1931-1940 and the 1971-2000 Normal period
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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).
Modeled change in the Seasonality between 1901-1910 and the 1971-2000 Normal period
공공데이터포털
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).
Modeled change in the Seasonality between the modeled 2041-2070 period (GFDL-CM3 r1i1p1 model) and the 1971-2000 Normal period
공공데이터포털
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 and model (in title) and the 1971-2000 Normal period (1 = same season, 0 = earlier season, 2 = later season).
Modeled change in the Seasonality between the modeled 2041-2070 period (CCSM4 r4i1p1 model) and the 1971-2000 Normal period
공공데이터포털
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 and model (in title) and the 1971-2000 Normal period (1 = same season, 0 = earlier season, 2 = later season).
Modeled change in the Seasonality between 1931-1940 and the 1971-2000 Normal period
공공데이터포털
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).