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1,027 results returned

  1. Title: Gary and Tolleston Indiana

    • Not specified
    • 1908
    Contributors:

    Summary: Title devised by cataloger. "Complements of Gary and Tolleston Reality Co." Imprint: Chicago : Will H. Moore, [1908] Dimensions: 22 x 28 cm, on sheet 44 x 56 cm; Scale: Scale not given. Coordinates: W0872601 W0871319 N0413919 N0413118

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  2. Title: Road map of northeastern Indiana

    • Road maps
    • 1947
    Contributors:

    Summary: Blueline. Imprint: [Fort Wayne, Ind.?]: [H.H. Mortorff], 1947. Scale: 1:200,000; Dimensions: 44 x 53 cm Coordinates: W0860000 W0844800 N0414100 N0410400

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  3. Title: Map of the action at Drainsville, Va., December 20th 1861. U.S. forces commanded by Brig Gen. E.O.C. Ord.

    • Not specified
    • 1861
    Contributors:

    Summary: Scale not given; 1 map: color; 40 x 26 cm Dranesville (Va.)--History--Civil War, 1861-1865--Maps

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  4. Title: Map of Indiana showing county boundaries, township and range lines

    • Not specified
    • 1952
    Contributors:

    Summary: "January 1952." Black line print. "Traced from Map of Indiana, edition of 1950, published by U.S. Geological Survey. Minor revisions and additions made from county base maps published by Geological Survey of Indiana. Land grant outlines compiled from original land survey sheets." Imprint: [Indianapolis?] : Geological Survey, 1952 Dimensions: 92 x 59 cm; Scale: 1:500,000 Coordinates: W0880500 W0844700 N0414500 N0374600

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  5. Title: Map of Indiana showing county boundaries, township and range lines

    • Not specified
    • 1951
    Contributors:

    Summary: Photocopy, 118 x 77 cm "November, 1951." "Traced from compilation proof sheets of new base map of Indiana, prepared by the U.S. Geological Survey. Minor additions made from Indiana Transportation Map, edition of 1947, which was also prepared by the U.S. Geological Survey." Blue line print. Imprint: Bloomington, Ind.: Indiana Geological Survey, 1951. Scale: 1:380,160; Dimensions: 118 x 77 cm Coordinates: W0880500 W0844700 N0414500 N0374600

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  6. Title: County map of Ohio and Indiana.

    • Not specified
    • 1870
    Contributors:

    Summary: Prime meridian: top of map is from Greenwich, bottom of map is from Washington. Hand painted. Imprint: Philadelphia : S. Augustus Mitchell, 1870. Dimensions: 30 x 36 cm; Scale: 1:1,800,000 Coordinates: W0874100 W0802000 N0420000 N0375400

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  7. Title: Solar Insolation, Minnesota] (2006-2012)

    • LiDAR
    • 2015
    Contributors:

    Summary: The Minnesota Solar Suitability Analysis attempts to provide solar insolation analysis for the entire State of Minnesota. As far as we are aware, it is the only project of its scale in existence; similar studies have been limited to metro areas or focus on rooftop insolation. The project's existence is feasible because of statewide, freely available aerial lidar coverage. And the commitment of the team to work long hours on this unfunded project. The project finds itself at the intersection of renewable energy, big data analysis, geospatial technology, and open data availability. This data provides a measure of incedent solar radiation as it is intercepted by the earth surface, or features (such as vegetation and buildings) standing above the earth surface. The data is intended to be used to assess the suitability of a site for solar panel (photovoltaic cell) installations. The analysis used to produce this dataset looks at geographic location, surface slope, surface aspect, and the effects of shading based on local topography and adjacent structures. A digital surface model was generated from raw LiDAR data. Then, using this DSM, an individual locations on a grid surface were assessed for the amount of direct and indirect radiation that reaches the surface. This analysis was conducted at a 1m resolution for the entire state of Minnesota.

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  8. Title: Digital Surface Model [Minnesota] (2006-2012)

    • LiDAR
    • 2015
    Contributors:

    Summary: A 1m resolution digital surface model that was generated from raw lidar data. This dataset was an intermediate product of a process to model potential solar insolation for the state of Minnesota. The Digital Surface Model (DSM) was created to represent the terrain and all object present on that terrain. This included buildings, tree cover, roads, and other natural and human-altered landscapes. In effect, the DSM is a three dimensional representation of Minnesota. It was generated using a Streaming Delauney Triangulation process through rapidlasso's LAStools software package. In this process, triangles are iteratively generated using nearby lidar returns and values for each point are determined by extracting interpolated elevation from the surface of the triangle. The result is a 1 meter resolution raster covering the state. Lidar is a form of active remote sensing technology that uses light pulses, most commonly in the near-infrared wavelengths, to collected surface elevation data. A laser scanner, mounted in an aircraft and combined with high-accuracy GPS, collects light returns that are interpolated into a point cloud. Each point represents one return from a laser pulse. The laser pulse has the ability to penetrate vegetation, multiple laser returns can be gathered for each pulse including the returns from below the vegetation.The accuracy of lidar returns allow for a unique, multi-faceted analytical dataset. The first point returns can be used to interpolate a topology of Minnesota that models the objects (i.e. building, trees, etc) and geography resting upon the terrain. The lidar point files for the state of Minnesota used in the study were collected between 2006 and 2012 through an intergovernmental initiative with the primary object of providing improved elevation data for flood mapping. In some regions, existing lidar data was acquired and transformed to new state standards. Areas where data did not exist or could not be transformed, were collected by contracted vendors. The composite data forms a seamless coverage of the state with a resolutions of at least 1.5 meters. Refer to metadata.html for full details.

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  9. Title: The Eagle Map of the United States Engraved for Rudiments of National Knowledge 1833 (Raster Image)

    • Raster data
    • 2015
    Contributors:

    Summary: This layer is a georeferenced image of a map of the United States, originally created by James and Joseph Churchman and I.W. Moore in 1833. The states are shown in outline color with the eagle transparently sitting atop the nation.The historic map layers in the Google Earth Rumsey Map Collection have been selected by David Rumsey from his large collection of historical maps, as well as some from other collections with which he collaborates. All the maps contain rich information about the past and represent a sampling of time periods, scales, and cartographic art, resulting in visual history stories that only old maps can tell. Each map has been georeferenced by Rumsey, thus creating unique digital map images that allow the old maps to appear in their correct places on the modern globe. Some of the maps fit perfectly in their modern spaces, while othersgenerally earlier period mapsreveal interesting geographical misconceptions of their time. Cultural features on the maps can be compared to the modern satellite views using the slider bars to adjust transparency. The result is an exploration of time as well as space, a marriage of historic cartographic masterpieces with innovative contemporary software tools.

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  10. Title: Road Map of Southeastern Indiana and Northeastern Kentucky

    • Road maps
    • 1930
    Contributors:

    Summary: Imprint: [Greenwood, Ill. : I.H. Ragsdale, [1930] Scale: Scale not given.; Dimensions: 20 x 17 cm Coordinates: W0861547 W0843029 N0393235 N0375834

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  11. Title: Average Monthly Precipitation for March (Inches & Millimeters): California, 1981-2010 (800m)

    • Raster data
    • 2007
    Contributors:

    Summary: This raster layer contains the average monthly precipitation levels in millimeters and inches for March 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 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 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 March (Inches & Millimeters): California, 1981-2010 (800m). California Department of Fish and Wildlife. Available at: http://purl.stanford.edu/hr974vj4583. 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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  12. Title: Average Monthly Precipitation for February: California, 1961-1990 (4km)

    • Raster data
    • 2007
    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 Wildlife. (2007). Average Monthly Precipitation for February: California, 1961-1990 (4km). California Department of Fish and Wildlife. Available at: http://purl.stanford.edu/bs206hr1420. 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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  13. Title: Average Monthly Precipitation for September: California, 1961-1990 (4km)

    • Raster data
    • 2007
    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 September: California, 1961-1990 (4km). California Department of Fish and Game. Available at: http://purl.stanford.edu/jb595jm4002. 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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  14. Title: Average Monthly Precipitation for April (Inches): California, 1981-2010 (800m)

    • Raster data
    • 2007
    Contributors:

    Summary: This raster layer contains the average monthly precipitation levels in inches for April 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 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 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 April: California, 1981-2010 (800m). California Department of Fish and Wildlife. Available at: http://purl.stanford.edu/jb752mv4420 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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  15. Title: Average Monthly Precipitation for November (Inches): California, 1981-2010 (800m)

    • Raster data
    • 2007
    Contributors:

    Summary: This raster layer contains the average monthly precipitation levels in inches for November 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 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 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 November (Inches): California, 1981-2010 (800m). California Department of Fish and Wildlife. Available at: http://purl.stanford.edu/jb494sv2423. 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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  16. Title: Average Monthly Precipitation for January (Inches): California, 1981-2010 (800m)

    • Raster data
    • 2007
    Contributors:

    Summary: This raster layer contains the average monthly precipitation levels in inches 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 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 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): California, 1981-2010 (800m). California Department of Fish and Wildlife. Available at: http://purl.stanford.edu/sq859wc1354. 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 December (Inches): California, 1981-2010 (800m)

    • Raster data
    • 2007
    Contributors:

    Summary: This raster layer contains the average monthly precipitation levels in inches for December 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 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 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 December: 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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  18. Title: Average Monthly Precipitation for May (Inches & Millimeters): California, 1981-2010 (800m)

    • Raster data
    • 2007
    Contributors:

    Summary: This raster layer contains the average monthly precipitation levels in millimeters and inches 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 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 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/nn108md5744. 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 September (Inches & Millimeters): California, 1981-2010 (800m)

    • Raster data
    • 2007
    Contributors:

    Summary: This raster layer contains the average monthly precipitation levels in millimeters and inches for September 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 and inches with integers. 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 September (Inches & Millimeters): California, 1981-2010 (800m). California Department of Fish and Wildlife. Available at: http://purl.stanford.edu/rz538cz7999. 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 Annual Precipitation (Millimeters): California, 1981-2010 (800m)

    • Raster data
    • 2007
    Contributors:

    Summary: This raster layer contains the average annual precipitation levels in millimeters for 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 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 (Millimeters): California, 1981-2010 (800m). California Department of Fish and Wildlife. Available at: http://purl.stanford.edu/cg097mp2593. 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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