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  1. Title: Rainfall Totals, greater Green Bay, WI area 2017

    Contributors:

    Summary: This data represents rainfall totals for the greater Green Bay, Wisconsin area in the year 2017 (from 01/04 to 12/05) at various time intervals. [Rainfall patterns for large storm events within 230 kilometers of the Green Bay, WI Next-Generation Radar (NEXRAD) station (KGRB). The files are Storm Total Precipitation (NTP) for 2003 to 2014 and Storm Total Accumulation (PTA) for 2015 to 2017 downloaded from the NEXRAD Inventory at the NOAA National Climatic Data Center and visualized through the Fox-Wolf Hydrologic Dashboard.]

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  2. Title: Rainfall Totals, greater Green Bay, WI area 2016

    Contributors:

    Summary: This data represents rainfall totals for the greater Green Bay, Wisconsin area in the year 2016 (from 01/10 to 12/26) at various time intervals.[Rainfall patterns for large storm events within 230 kilometers of the Green Bay, WI Next-Generation Radar (NEXRAD) station (KGRB). The files are Storm Total Precipitation (NTP) for 2003 to 2014 and Storm Total Accumulation (PTA) for 2015 to 2017 downloaded from the NEXRAD Inventory at the NOAA National Climatic Data Center and visualized through the Fox-Wolf Hydrologic Dashboard.]

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  3. Title: Rainfall Totals, greater Green Bay, WI area 2015

    Contributors:

    Summary: This data represents rainfall totals for the greater Green Bay, Wisconsin area in the year 2015 (from 03/25 to 12/30) at various time intervals.[Rainfall patterns for large storm events within 230 kilometers of the Green Bay, WI Next-Generation Radar (NEXRAD) station (KGRB). The files are Storm Total Precipitation (NTP) for 2003 to 2014 and Storm Total Accumulation (PTA) for 2015 to 2017 downloaded from the NEXRAD Inventory at the NOAA National Climatic Data Center and visualized through the Fox-Wolf Hydrologic Dashboard.]

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  4. Title: Rainfall Totals, greater Green Bay, WI area 2014

    Contributors:

    Summary: This data represents rainfall totals for the greater Green Bay, Wisconsin area in the year 2014 (from 03/28 to 09/21) at various time intervals. [Rainfall patterns for large storm events within 230 kilometers of the Green Bay, WI Next-Generation Radar (NEXRAD) station (KGRB). The files are Storm Total Precipitation (NTP) for 2003 to 2014 and Storm Total Accumulation (PTA) for 2015 to 2017 downloaded from the NEXRAD Inventory at the NOAA National Climatic Data Center and visualized through the Fox-Wolf Hydrologic Dashboard.]

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  5. Title: Rainfall Totals, greater Green Bay, WI area 2013

    Contributors:

    Summary: This data represents rainfall totals for the greater Green Bay, Wisconsin area in the year 2013 (from 04/10 to 10/06) at various time intervals.[Rainfall patterns for large storm events within 230 kilometers of the Green Bay, WI Next-Generation Radar (NEXRAD) station (KGRB). The files are Storm Total Precipitation (NTP) for 2003 to 2014 and Storm Total Accumulation (PTA) for 2015 to 2017 downloaded from the NEXRAD Inventory at the NOAA National Climatic Data Center and visualized through the Fox-Wolf Hydrologic Dashboard.]

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  6. Title: Rainfall Totals, greater Green Bay, WI area 2012

    Contributors:

    Summary: This data represents rainfall totals for the greater Green Bay, Wisconsin area in the year 2012 (from 04/16 to 10/15) at various time intervals.[Rainfall patterns for large storm events within 230 kilometers of the Green Bay, WI Next-Generation Radar (NEXRAD) station (KGRB). The files are Storm Total Precipitation (NTP) for 2003 to 2014 and Storm Total Accumulation (PTA) for 2015 to 2017 downloaded from the NEXRAD Inventory at the NOAA National Climatic Data Center and visualized through the Fox-Wolf Hydrologic Dashboard.]

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  7. Title: Rainfall Totals, greater Green Bay, WI area 2011

    Contributors:

    Summary: This data represents rainfall totals for the greater Green Bay, Wisconsin area in the year 2011 (from 04/11 to 11/08) at various time intervals.[Rainfall patterns for large storm events within 230 kilometers of the Green Bay, WI Next-Generation Radar (NEXRAD) station (KGRB). The files are Storm Total Precipitation (NTP) for 2003 to 2014 and Storm Total Accumulation (PTA) for 2015 to 2017 downloaded from the NEXRAD Inventory at the NOAA National Climatic Data Center and visualized through the Fox-Wolf Hydrologic Dashboard.]

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  8. Title: Rainfall Totals, greater Green Bay, WI area 2010

    Contributors:

    Summary: This data represents rainfall totals for the greater Green Bay, Wisconsin area in the year 2010 (from 04/09 to 09/03) at various time intervals.[Rainfall patterns for large storm events within 230 kilometers of the Green Bay, WI Next-Generation Radar (NEXRAD) station (KGRB). The files are Storm Total Precipitation (NTP) for 2003 to 2014 and Storm Total Accumulation (PTA) for 2015 to 2017 downloaded from the NEXRAD Inventory at the NOAA National Climatic Data Center and visualized through the Fox-Wolf Hydrologic Dashboard.]

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  9. Title: Rainfall Totals, greater Green Bay, WI area 2009

    Contributors:

    Summary: This data represents rainfall totals for the greater Green Bay, Wisconsin area in the year 2009 (from 03/25 to 10/24) at various time intervals.[Rainfall patterns for large storm events within 230 kilometers of the Green Bay, WI Next-Generation Radar (NEXRAD) station (KGRB). The files are Storm Total Precipitation (NTP) for 2003 to 2014 and Storm Total Accumulation (PTA) for 2015 to 2017 downloaded from the NEXRAD Inventory at the NOAA National Climatic Data Center and visualized through the Fox-Wolf Hydrologic Dashboard.]

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  10. Title: Rainfall Totals, greater Green Bay, WI area 2008

    Contributors:

    Summary: This data represents rainfall totals for the greater Green Bay, Wisconsin area in the year 2008 (from 04/09 to 08/29) at various time intervals.[Rainfall patterns for large storm events within 230 kilometers of the Green Bay, WI Next-Generation Radar (NEXRAD) station (KGRB). The files are Storm Total Precipitation (NTP) for 2003 to 2014 and Storm Total Accumulation (PTA) for 2015 to 2017 downloaded from the NEXRAD Inventory at the NOAA National Climatic Data Center and visualized through the Fox-Wolf Hydrologic Dashboard.]

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  11. Title: Rainfall Totals, greater Green Bay, WI area 2007

    Contributors:

    Summary: This data represents rainfall totals for the greater Green Bay, Wisconsin area in the year 2007 (from 01/01 to 10/16) at various time intervals.[Rainfall patterns for large storm events within 230 kilometers of the Green Bay, WI Next-Generation Radar (NEXRAD) station (KGRB). The files are Storm Total Precipitation (NTP) for 2003 to 2014 and Storm Total Accumulation (PTA) for 2015 to 2017 downloaded from the NEXRAD Inventory at the NOAA National Climatic Data Center and visualized through the Fox-Wolf Hydrologic Dashboard.]

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  12. Title: Rainfall Totals, greater Green Bay, WI area 2006

    Contributors:

    Summary: This data represents rainfall totals for the greater Green Bay, Wisconsin area in the year 2006 (from 05/19 to 10/03) at various time intervals.[Rainfall patterns for large storm events within 230 kilometers of the Green Bay, WI Next-Generation Radar (NEXRAD) station (KGRB). The files are Storm Total Precipitation (NTP) for 2003 to 2014 and Storm Total Accumulation (PTA) for 2015 to 2017 downloaded from the NEXRAD Inventory at the NOAA National Climatic Data Center and visualized through the Fox-Wolf Hydrologic Dashboard.]

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  13. Title: Rainfall Totals, greater Green Bay, WI area 2005

    Contributors:

    Summary: This data represents rainfall totals for the greater Green Bay, Wisconsin area in the year 2005 (from 04/20 to 09/26) at various time intervals.[Rainfall patterns for large storm events within 230 kilometers of the Green Bay, WI Next-Generation Radar (NEXRAD) station (KGRB). The files are Storm Total Precipitation (NTP) for 2003 to 2014 and Storm Total Accumulation (PTA) for 2015 to 2017 downloaded from the NEXRAD Inventory at the NOAA National Climatic Data Center and visualized through the Fox-Wolf Hydrologic Dashboard.]

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  14. Title: Rainfall Totals, greater Green Bay, WI area 2004

    Contributors:

    Summary: This data represents rainfall totals for the greater Green Bay, WI area in the year 2004 (from 05/11 to 08/27) at various time intervals.[Rainfall patterns for large storm events within 230 kilometers of the Green Bay, WI Next-Generation Radar (NEXRAD) station (KGRB). The files are Storm Total Precipitation (NTP) for 2003 to 2014 and Storm Total Accumulation (PTA) for 2015 to 2017 downloaded from the NEXRAD Inventory at the NOAA National Climatic Data Center and visualized through the Fox-Wolf Hydrologic Dashboard.]

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  15. Title: Rainfall Totals, greater Green Bay, WI area 2003

    Contributors:

    Summary: This data represents rainfall totals for the Green Bay, Wisconsin area in the year 2003 (from 03/29 to 09/16) at various time intervals.[Rainfall patterns for large storm events within 230 kilometers of the Green Bay, WI Next-Generation Radar (NEXRAD) station (KGRB). The files are Storm Total Precipitation (NTP) for 2003 to 2014 and Storm Total Accumulation (PTA) for 2015 to 2017 downloaded from the NEXRAD Inventory at the NOAA National Climatic Data Center and visualized through the Fox-Wolf Hydrologic Dashboard.]

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  16. Title: Average Annual Precipitation (Inches): California, 1981-2010 (800m)

    Contributors:

    Summary: This raster layer contains the average annual precipitation levels in inches for California from 1981 to 2010. This dataset incorporates a conceptual framework that uniquely addresses the spatial scale and pattern of orographic precipitation. The original PRISM dataset covered the United States. This is a California-only version subsetted from the original data set and converted to California Teale Albers NAD83 using bilinear interpolation by the California Department of Fish and Game (CDFG) at 800m resolution. The grid units are presented in inches with floating point. Care should be taken in estimating precipitation values at any single point on the map. Precipitation estimated for each grid cell is an average over the entire area of that cell; thus, point precipitation can be estimated at a spatial precision no better than half the resolution of a cell. Accuracy of this data set is based on the original specification of the Defense Mapping Agency (DMA) 1 degree digital elevation models (DEMs). The stated accuracy of the original DEMs is 130m circular error with 90% probability. The Parameter-elevation Regressions on Independent Slopes Model (PRISM) Climate Group works on a range of projects, some of which support the development of spatial climate datasets. These PRISM datasets provide estimates of the basic climate element of precipitation (ppt), or the daily total precipitation averaged over a month for both rain and melted snow. These datasets are modeled with PRISM using a digital elevation model (DEM) as the predictor grid and provide baselines describing average annual precipitation between 1981 and 2000 to be used for display and/or analyses requiring spatially distributed annual precipitation. Annual grids were produced by averaging (temperatures) or summing (precipitation) the monthly grids. California Department of Fish and Wildlife. (2007). Average Annual Precipitation (Inches): California, 1981-2010 (800m). California Department of Fish and Wildlife. Available at: http://purl.stanford.edu/cp513wz4565. There are many methods of interpolating precipitation 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 precipitation 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 a digital elevation model (DEM) to generate gridded estimates of monthly and annual precipitation (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 precipitation. This layer is presented in the WGS84 coordinate system for web display purposes. Downloadable data are provided in native coordinate system or projection.

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  17. Title: Average Monthly Precipitation for January (Millimeters): California, 1981-2010 (800m)

    Contributors:

    Summary: This raster layer contains the average monthly precipitation levels in millimeters for January 1981-2010. This dataset incorporates a conceptual framework that uniquely addresses the spatial scale and pattern of orographic precipitation. The original PRISM dataset covered the United States. This is a California-only version subsetted from the original data set and converted to California Teale Albers NAD83 using bilinear interpolation by the California Department of Fish and Game (CDFG) at 800m resolution. The grid units are presented in millimeters with floating point. Care should be taken in estimating precipitation values at any single point on the map. Precipitation estimated for each grid cell is an average over the entire area of that cell; thus, point precipitation can be estimated at a spatial precision no better than half the resolution of a cell. Accuracy of this data set is based on the original specification of the Defense Mapping Agency (DMA) 1 degree digital elevation models (DEMs). The stated accuracy of the original DEMs is 130m circular error with 90% probability. The Parameter-elevation Regressions on Independent Slopes Model (PRISM) Climate Group works on a range of projects, some of which support the development of spatial climate datasets. These PRISM datasets provide estimates of the basic climate element of precipitation (ppt), or the Daily total precipitation averaged over a month for both rain and melted snow. These datasets are modeled with PRISM using a digital elevation model (DEM) as the predictor grid and provide baselines describing average monthly precipitation between 1981 and 2000 to be used for display and/or analyses requiring spatially distributed monthly or annual precipitation. Grids were modeled on a monthly basis. Annual grids were produced by averaging (temperatures) or summing (precipitation) the monthly grids. California Department of Fish and Wildlife. (2007). Average Monthly Precipitation for January (Millimeters): California, 1981-2010 (800m). California Department of Fish and Wildlife. Available at: http://purl.stanford.edu/sd483rh8562. There are many methods of interpolating precipitation 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 precipitation 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 a digital elevation model (DEM) to generate gridded estimates of monthly and annual precipitation (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 precipitation. This layer is presented in the WGS84 coordinate system for web display purposes. Downloadable data are provided in native coordinate system or projection.

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  18. Title: Average Monthly Precipitation for May (Millimeters): California, 1981-2010 (800m)

    Contributors:

    Summary: This raster layer contains the average monthly precipitation levels in millimeters for May 1981-2010. This dataset incorporates a conceptual framework that uniquely addresses the spatial scale and pattern of orographic precipitation. The original PRISM dataset covered the United States. This is a California-only version subsetted from the original data set and converted to California Teale Albers NAD83 using bilinear interpolation by the California Department of Fish and Game (CDFG) at 800m resolution. The grid units are presented in millimeters with floating point. Care should be taken in estimating precipitation values at any single point on the map. Precipitation estimated for each grid cell is an average over the entire area of that cell; thus, point precipitation can be estimated at a spatial precision no better than half the resolution of a cell. Accuracy of this data set is based on the original specification of the Defense Mapping Agency (DMA) 1 degree digital elevation models (DEMs). The stated accuracy of the original DEMs is 130m circular error with 90% probability. The Parameter-elevation Regressions on Independent Slopes Model (PRISM) Climate Group works on a range of projects, some of which support the development of spatial climate datasets. These PRISM datasets provide estimates of the basic climate element of precipitation (ppt), or the Daily total precipitation averaged over a month for both rain and melted snow. These datasets are modeled with PRISM using a digital elevation model (DEM) as the predictor grid and provide baselines describing average monthly precipitation between 1981 and 2000 to be used for display and/or analyses requiring spatially distributed monthly or annual precipitation. Grids were modeled on a monthly basis. Annual grids were produced by averaging (temperatures) or summing (precipitation) the monthly grids. California Department of Fish and Wildlife. (2007). Average Monthly Precipitation for May (Inches & Millimeters): California, 1981-2010 (800m). California Department of Fish and Wildlife. Available at: http://purl.stanford.edu/ct784rv5363. There are many methods of interpolating precipitation 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 precipitation 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 a digital elevation model (DEM) to generate gridded estimates of monthly and annual precipitation (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 precipitation. This layer is presented in the WGS84 coordinate system for web display purposes. Downloadable data are provided in native coordinate system or projection.

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  19. Title: Average Monthly Precipitation for June: California, 1961-1990 (4km)

    Contributors:

    Summary: This raster dataset incorporates a conceptual framework that uniquely addresses the spatial scale and pattern of orographic precipitation. The original PRISM dataset covered the United States. This is a California-only version subsetted from the original data set and converted to California Teale Albers NAD83 using bilinear interpolation by the California Department of Fish and Game (CDFG) at 2.5 arc-minutes resolution (approximately 4km). Care should be taken in estimating precipitation values at any single point on the map. Precipitation estimated for each grid cell is an average over the entire area of that cell; thus, point precipitation can be estimated at a spatial precision no better than half the resolution of a cell. Accuracy of this data set is based on the original specification of the Defense Mapping Agency (DMA) 1 degree digital elevation models (DEMs). The stated accuracy of the original DEMs is 130m circular error with 90% probability. The Parameter-elevation Regressions on Independent Slopes Model (PRISM) Climate Group works on a range of projects, some of which support the development of spatial climate datasets. These PRISM datasets provide estimates of the basic climate element of precipitation (ppt), or the Daily total precipitation averaged over a month for both rain and melted snow. These datasets are modeled with PRISM using a digital elevation model (DEM) as the predictor grid and provide baselines describing average monthly precipitation between 1961 and 1990 to be used for display and/or analyses requiring spatially distributed monthly or annual precipitation. California Department of Fish and Game. (2007). Average Monthly Precipitation for June: California, 1961-1990 (4km). California Department of Fish and Game. Available at: http://purl.stanford.edu/vt457dj3607. There are many methods of interpolating precipitation 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 precipitation 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 a digital elevation model (DEM) to generate gridded estimates of monthly and annual precipitation (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 precipitation. This layer is presented in the WGS84 coordinate system for web display purposes. Downloadable data are provided in native coordinate system or projection.

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  20. Title: Average Monthly Precipitation for June (Millimeters): California, 1981-2010 (800m)

    Contributors:

    Summary: This raster layer contains the average monthly precipitation levels in millimeters for June 1981-2010. This dataset incorporates a conceptual framework that uniquely addresses the spatial scale and pattern of orographic precipitation. The original PRISM dataset covered the United States. This is a California-only version subsetted from the original data set and converted to California Teale Albers NAD83 using bilinear interpolation by the California Department of Fish and Game (CDFG) at 800m resolution. The grid units are presented in millimeters with floating point. Care should be taken in estimating precipitation values at any single point on the map. Precipitation estimated for each grid cell is an average over the entire area of that cell; thus, point precipitation can be estimated at a spatial precision no better than half the resolution of a cell. Accuracy of this data set is based on the original specification of the Defense Mapping Agency (DMA) 1 degree digital elevation models (DEMs). The stated accuracy of the original DEMs is 130m circular error with 90% probability. The Parameter-elevation Regressions on Independent Slopes Model (PRISM) Climate Group works on a range of projects, some of which support the development of spatial climate datasets. These PRISM datasets provide estimates of the basic climate element of precipitation (ppt), or the Daily total precipitation averaged over a month for both rain and melted snow. These datasets are modeled with PRISM using a digital elevation model (DEM) as the predictor grid and provide baselines describing average monthly precipitation between 1981 and 2000 to be used for display and/or analyses requiring spatially distributed monthly or annual precipitation. Grids were modeled on a monthly basis. Annual grids were produced by averaging (temperatures) or summing (precipitation) the monthly grids. California Department of Fish and Wildlife. (2007). Average Monthly Precipitation for January (Inches & Millimeters): California, 1981-2010 (800m). California Department of Fish and Wildlife. Available at: http://purl.stanford.edu/vt854zj8399. There are many methods of interpolating precipitation 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 precipitation 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 a digital elevation model (DEM) to generate gridded estimates of monthly and annual precipitation (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 precipitation. This layer is presented in the WGS84 coordinate system for web display purposes. Downloadable data are provided in native coordinate system or projection.

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