The PRISM Climate Group gathers climate observations from a wide range of monitoring networks, applies sophisticated quality control measures, and develops spatial climate datasets to reveal short- and long-term climate patterns. The resulting datasets incorporate a variety of modeling techniques and are available at multiple spatial/temporal resolutions, covering the period from 1895 to the present.

Climate data--including 30-Year-normal data--provided by PRISM Climate Group at Oregon State University. Data is in raster formats.

The PRISM daily and monthly datasets are gridded climate datasets for the conterminous United States, produced by the PRISM Climate Group at Oregon State University. Grids are developed using PRISM (Parameter-elevation Regressions on Independent Slopes Model). PRISM interpolation routines simulate how weather and climate vary with elevation, and account for coastal effects, temperature inversions, and terrain barriers that can cause rain shadows. Station data are assimilated from many networks across the country. For more information, see the Descriptions of PRISM Spatial Climate Datasets.

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The PRISM NaNDA dataset provides daily weather data—minimum temperature (tmin), maximum temperature (tmax), and precipitation (ppt)—for all census tracts in the contiguous United States (CONUS) from 1981 to 2024. These data are derived from Oregon State University’s PRISM Climate Group (Northwest Alliance for Computational Science & Engineering & Oregon State University, 2025), which produces high-resolution (4 km x 4 km) gridded climate estimates.In addition to daily values, the dataset includes two types of annual tract-level summary measures:Percentiles (0.5th, 1st, 5th, 95th, 99th, and 99.5th), calculated using a rolling 10-year window of historical data, available for tmin, tmax, and ppt. Percents, representing the proportion of days per year that fall above or below these percentile thresholds, available for tmin and tmax only.These features enable robust analyses of long-term environmental trends, extreme weather events, and their potential impacts on population health.

This data set consists of PRSIM mean air temperature climatologies for Alaska in GeoTIFF format. The files in this data set are available from the PRISM Climate Group as text files but have been processed into GeoTIFFs. These are monthly climatologies with a resolution of 771m. Units are degrees Celsius. There are multiple climatological periods currently available through PRISM, but only one is currently available through SNAP in this dataset: 1971-2000.

Monthly 30-year "normal" dataset covering the conterminous U.S., including the Russian River watershed, averaged over the climatological period 1981-2010. Contains spatially gridded average monthly and average annual precipitation, maximum temperature, and minimum temperature at 800m grid cell resolution. Distribution of the point measurements to the spatial grid was accomplished using the PRISM model, developed and applied by Dr. Christopher Daly of the PRISM Climate Group at Oregon State University. This dataset was heavily peer reviewed, and is available free-of-charge on the PRISM website. The dataset was downloaded from the PRISM website in 2019

This dataset was created using the PRISM (Parameter-elevation Regressions on Independent Slopes Model) climate mapping system, developed by Dr. Christopher Daly, PRISM Climate Group director. PRISM is a unique knowledge-based system that uses point measurements of precipitation, temperature, and other climatic factors to produce continuous, digital grid estimates of monthly, yearly, and event-based climatic parameters. Continuously updated, this unique analytical tool incorporates point data, a digital elevation model, and expert knowledge of complex climatic extremes, including rain shadows, coastal effects, and temperature inversions. PRISM data sets are recognized world-wide as the highest-quality spatial climate data sets currently available. PRISM is the USDA's official climatological data. The latest snapshot of PRISM available free of charge and hosted here was developed with the AN81m method documented here: http://www.prism.oregonstate.edu/documents/PRISM_datasets.pdf

30-year "normal" dataset covering the conterminous U.S., averaged over the climatological period 1991-2020. Contains spatially gridded average daily mean temperature at 800m grid cell resolution. Distribution of the point measurements to the spatial grid was accomplished using the PRISM model, developed and applied by Dr. Christopher Daly of the PRISM Climate Group at Oregon State University. PRISM is an analytical model that uses point data and an underlying grid such as a digital elevation model (DEM) or a 30 yr climatological average to generate gridded estimates of monthly or annual precipitation and temperature (as well as other climatic parameters). PRISM is well suited to regions with mountainous terrain, because it incorporates a conceptual framework that addresses the spatial scale and pattern of orographic processes. Grids were modeled on a monthly basis. Annual grids were produced by averaging (temperature, vapor pressure, vapor pressure deficit, and solar radiation) or summing (precipitation) the monthly grids. These gridded normals supersede the 1991-2020 normals released in December 2022. Revisions were made to a limited number of grid cells along the US West Coast to align with the recently-developed daily normals for maximum, minimum and mean temperature, mean dew point, and maximum and minimum vapor pressure deficit. No revisions were made to the precipitation normals.

Monthly PRISM datasets covering the conterminous U.S., from 1981-2019 were used to calculate yearly average air temperature and spatially averaged yearly precipitation for selected counties in and near the Permian Basin. Distribution of the measurements was accomplished using the PRISM, developed and applied by Dr. Christopher Daly of the PRISM Climate Group at Oregon State University. The aggregated data was used to display and/or analyze spatially distributed yearly average air temperature and spatially averaged yearly precipitation for select counties in and near the Permian Basin from 1981-2019.

Metadata record for OSU's PRISM Data Explorer; link in record. This OSU PRISM Group web site provides access to the highest-quality spatial climate data sets currently available. These data sets were created using the PRISM climate mapping system, developed by Dr. Christopher Daly, PRISM Group director. PRISM is unique in that it incorporates a spatial climate knowledge base that accounts for rain shadows, temperature inversions, coastal effects, and more in the climate mapping process.

The PRISM Climate Mapping Program is an ongoing effort to produce and disseminate the most detailed, highest-quality spatial climate datasets currently available. These digital climate maps are created using PRISM (Parameter-elevation Regressions on Independent Slopes Model) an analytical tool that uses point data, a digital elevation model, and other spatial data sets to generate gridded estimates of monthly, yearly, and event-based climatic parameters, such as precipitation, temperature, snowfall, degree days, and dew point. PRISM derived data sets have been and are being used in applications of climatology, hydrology, natural resources, global climate change, land use, planning, relocation, education, and geography. PRISM is uniquely designed and constantly updated to map climate in the most difficult situations, including high mountains, rain shadows, temperature inversions, coastal regions, and other complex climatic regimes. PRISM climate mapping projects are being conducted in the United States, Canada, China, Mongolia, Europe, Pacific Islands, and elsewhere. The program is a collaboration between the Spatial Climate Analysis Service, directed by Dr. Christopher Daly, Assistant Professor, and the Oregon Climate Service, directed by George Taylor, State Climatologist. Both the SCAS and OCS are located on the Oregon State University campus in Corvallis. Source of the abstract:Spatial Climate Analysis Service/Oregon Climate Service (1999): http://www.ocs.orst.edu/prism/prism_new.html PRISM (Precipitation-elevation Regression Independent Slopes Model) is an analytical-interpolation model used to distribute monthly and annual precipitation on a regular grid for use in vegetation modeling, hydrologic calculations and climatic studies. This model is designed to be used to generate input for other models requiring this type of information. The model uses DEM (Digital Elevation Models) to estimate elevation or precipitation stations and proper orographic scales. It then groups stations into topographic scales. The model requires input in the form of monthly or annual precipitation measurements, and DEM at 2.5 or 5-minute resolutions. Output includes gridded monthly or annual precipitation estimates and a 95% prediction interval. Source of the abstract: CIESIN (CONSORTIUM FOR INTERNATIONAL EARTH SCIENCE INFORMATION NETWORK) : [ Modeling Paradigm: Multi-criteria analysis ] [ Model Ecosystem: Physical hazards (examples: fires, floods, air quality, water quality, carbon storage) ]

This OSU PRISM Group web site provides access to the highest-quality spatial climate data sets currently available. These data sets were created using the PRISM climate mapping system, developed by Dr. Christopher Daly, PRISM Group director. PRISM is unique in that it incorporates a spatial climate knowledge base that accounts for rain shadows, temperature inversions, coastal effects, and more in the climate mapping process. Daily maximum temperature [averaged over all days in the month].

This Resource serves to explain and contain the methodology, R codes, and results of the PRISM freshwater supply key indicator analysis for my thesis. For more information, see my thesis at the USU Digital Commons.

Freshwater availability in the state can be summarized using streamflow, reservoir level, precipitation, and temperature data. Climate data for this study have a period of record greater than 30 years, preferably extending beyond 1950, and are representative of natural conditions at the county-level.

Oregon State University, Northwest Alliance for Computational Science and Engineering PRISM precipitation and temperature gridded data are representative of statewide, to county-level, from 1895-2015. These data are available online from the PRISM Climate Group. Using the R ‘prism’ package, monthly PRISM 4km raster grids were downloaded. Boundary shapefiles of Utah state, and each county, were obtained online from the Utah Geospatial Resource Center webpage. Using the R ‘rgdal’ and ‘sp’ packages, these shapefiles were transformed from their native World Geodetic System 1984 coordinate system to match the PRISM BIL raster’s native North American Datum 1983 coordinate system. Using the R ‘raster’ package, medians of PRISM precipitation grids at each spatial area of interest were calculated and summed for water years and seasons. Medians were also calculated for PRISM temperature grids and averaged over water years and seasons. For analysis of single months, the median results were used for all PRISM indicators. Seasons were analyzed for the calendar year which they are in, Winter being the first season of each year. Freshwater availability key indicators were non-parametrically separated per temporal/spatial delineation into quintiles representing Very Wet/Very High/Hot (top 20% of values), Wet/High/Hot (60-80%), Moderate/Mid-level (40-60%), Dry/Low/Cool (20-40%), to Very Dry/Very Low/Cool (bottom 20%). Each quintile bin was assigned a rank value 1-5, with ‘5’ being the value of the top quintile, in preparation for the Kendall Tau-b correlation analysis. These results, along with USGS irrigation withdrawal and acreage data, were loaded into R. State-level quintile results were matched according to USGS report year. County quintile results were matched with corresponding USGS irrigation withdrawal and acreage county-level data per report year for all other areas of interest. Using the base R function cor(), with the “kendall” method selected (which is, by default, the Kendall Tau-b calculation), relationship correlation matrices were produced for all areas of interest. The USGS irrigation withdrawal and acreage data correlation analysis matrices were created using the R ‘corrplot’ package for all areas of interest.

See Word file for an Example PRISM Analysis, made by Alan Butler at the United States Bureau of Reclamation, which was used as a guide for this analysis.

This data set contains spatially gridded average monthly and annual maximum temperature for the climatological period 1981-2010. Distribution of the point measurements to a spatial grid was accomplished using the PRISM model, developed and applied by Chris Daly of the PRISM Climate Group at Oregon State University.

This is a dataset download, not a document. The Open button will start the download.This data layer is an element of the Oregon GIS Framework. Monthly 30-year "normal" dataset covering Oregon, averaged over the climatological period 1991-2020. Contains spatially gridded average annual total precipitation at 800m (30 arc-second) grid cell resolution. Distribution of the point measurements to the spatial grid was accomplished using the PRISM model, developed and applied by Dr. Christopher Daly of the PRISM Climate Group at Oregon State University. This dataset is available free-of-charge on the PRISM website.

Monthly totals of precipitation in millimeters (mm), monthly means of daily maximum air temperature in degrees Celsius (C), and monthly means of daily minimum air temperature (C) were developed at the 5 arc minute grid level for the conterminous United States (US) for the 1940-2006 period. Also, included are computed monthly mean of daily potential evapotranspiration (mm) and mean grid elevation in meters (m). These data were developed from PRISM (Parameter-elevation Regressions on Independent Slopes Model) data at the 2.5 arc minute scale and aggregated to the 5 arc minute grid scale. The county means were computed using a weighted mean of the 5 arc minute grids within the county.The USDA Forest Service (USFS) produces a periodic assessment of the condition and trends of the Nation's renewable resources as required by the Forest and Rangeland Renewable Resources Planning Act (RPA) of 1974. This RPA Assessment provides a snapshot of current US forest and rangeland conditions and trends on all ownerships, identifies drivers of change, and projects 50 years into the future (//www.fs.fed.us/research/rpa/, accessed 8/16/2009). For 2010 RPA Assessment, an integrated modeling framework is being used in which the potential implications of climate change can be analyzed across some resource areas (Langner in review). The nature of the climate variables needed to address climate change impacts for these resource analyses in the 2010 RPA Assessment were determined to be monthly precipitation and temperature variables at the county level spatial scale and for some resource analyses at the 5 arc minute grid scale.Original metadata date was 08/02/2010. Metadata modified on 04/22/2011 to adjust citation to include the addition of a DOI (digital object identifier). Minor metadata updates on 02/20/2013. Metadata modified on 07/22/2015 to update cross-reference citations and other minor updates. Additional minor metadata updates on 12/13/2016 and 04/19/2018.

Spatially distributed monthly and annual temperature. Each file represents 1 month of 1 year for the period 1895-1997. Distribution of the point measurements to a spatial grid was accomplished using the PRISM model, developed by Christopher Daly, Director, The PRISM Climate Group, Oregon State University. Care should be taken in estimating temperature values at any single point on the map. Temperature estimated for each grid cell is an average over the entire area of that cell; thus, point temperature can be estimated at a spatial precision no better than half the resolution of a cell. For example, the temperature data were distributed at a resolution of approximately 4km. Therefore, point temperature can be estimated at a spatial precision no better than 2km. However, the overall distribution of temperature features is thought to be accurate. For further information, the online PRISM homepage can be found at URL:http://prism.oregonstate.edu. Further information on the current state of this project can be found at URL:ftp://ftp.ncdc.noaa.gov/pub/data/prism100

Spatially distributed monthly and annual average maximum/minimum/dew point temperature. Each file represents 1 month of 1 year for the period January 1997 to the present. Distribution of the point measurements to a spatial grid was accomplished using the PRISM model, developed by Christopher Daly, Director, The PRISM Climate Group, Oregon State University. Care should be taken in estimating temperature values at any single point on the map. Temperature estimated for each grid cell is an average over the entire area of that cell; thus, point temperature can be estimated at a spatial precision no better than half the resolution of a cell. For example, the temperature data were distributed at a resolution of approximately 4km. Therefore, point temperature can be estimated at a spatial precision no better than 2km. However, the overall distribution of temperature features is thought to be accurate. For further information, the online PRISM homepage can be found at URL:http://prism.oregonstate.edu.

This metadata record describes a raster of unique PRISM (Parameter-elevation Relationships on Independent Slopes Model) identifier (PRISMID) values. The data are in ESRI's ArcInfo ASCII raster format, a non-proprietary text interchange format. PRISM climate data produced by the PRISM group at Oregon State University, such as time series of monthly precipitation and temperature, can be linked to the raster via the unique PRISMID values. In addition, model-estimated water budget components--including runoff (streamflow per unit area), evapotranspiration, snowfall and soil moisture storage--can be linked to the PRISM raster.