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.

Dataset Card for PRISM

PRISM is a diverse human feedback dataset for preference and value alignment in Large Language Models (LLMs). It maps the characteristics and stated preferences of humans from a detailed survey onto their real-time interactions with LLMs and contextual preference ratings

  Dataset Details

There are two sequential stages: first, participants complete a Survey where they answer questions about their demographics and stated preferences, then proceed to… See the full description on the dataset page: https://huggingface.co/datasets/HannahRoseKirk/prism-alignment.

Climate data provided by the National Water & Climate CenterThis record was taken from the USDA Enterprise Data Inventory that feeds into the https://data.gov catalog. Data for this record includes the following resources: PRISM For complete information, please visit https://data.gov.

Source data for manuscript figures

This data set consists of PRSIM precipitation 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 millimeters. There are multiple climatological periods currently available through PRISM, but only one is currently available through SNAP in this dataset: 1971-2000.

Asap7772/prism-alignment dataset hosted on Hugging Face and contributed by the HF Datasets community

Raw data tables and the statistical analysis applied to the data. Files are labeled by figure number. Within each file, each table and linked graph and analysis is annotated by figure number and panel letter. All files are generated in graphpad prism.

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.

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 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 collection provides access to the ALOS-1 PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) L1B data acquired by ESA stations in the ADEN zone plus some data requested by European scientists over their areas of interest around the world. The ADEN zone (https://earth.esa.int/eogateway/documents/20142/37627/ALOS-ADEN-Zone.pdf) was the area belonging to the European Data node and covered both the European and African continents, a large part of Greenland and the Middle East.

The full mission is covered, though with gaps outside of the ADEN zone:

Time window: from 2006-07-09 to 2011-03-31 Orbits: from 2425 to 24189 Path (corresponds to JAXA track number): from 1 to 668 Row (corresponds to JAXA scene centre frame number): from 55 to 7185. Two different Level 1B product types (Panchromatic images in VIS-NIR bands, 2.5 m resolution at nadir) are offered, one for each available sensor mode:

PSM_OB1_11 -> composed of up to three views; Nadir, Forward and Backward at 35 km swath PSM_OB2_11 -> composed of up to two views; Nadir view at 70 km width and Backward view at 35 km width. All ALOS PRISM EO-SIP products have, at least, the Nadir view which is used for the frame number identification. All views are packaged together; each view, in CEOS format, is stored in a directory named according to the view ID according to the JAXA naming convention.

Meteorological map products that show annual precipitation (mm/in) and temperature minimum and maximum (C) averages. Please us link to PRISM Home website below for most current PRISM data.

Prism AI

## Overview

Prism AI is a dataset for object detection tasks - it contains Car Damage annotations for 4,000 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

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.

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.

{{description}}

USSS contract and procurment management dataset built off of Unison's PRISM COTS application (to be decommissioned and procurement data set merges into CLM on 6/15/2022)

Monthly 30-year 'normal' dataset covering the conterminous U.S., averaged over the climatological period 1981-2010. Contains spatially gridded average annual precipitation 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.

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