Typical annual rainfall data were summarized from monthly precipitation data and provided in millimeters (mm). The monthly climate data for global land areas were generated from a large network of weather stations by the WorldClim project. Precipitation and temperature data were collected from the weather stations and aggregated across a target temporal range of 1970-2000.

Weather station data (between 9,000 and 60,000 stations) were interpolated using thin-plate splines with covariates including elevation, distance to the coast, and MODIS-derived minimum and maximum land surface temperature. Spatial interpolation was first done in 23 regions of varying size depending on station density, instead of the common approach to use a single model for the entire world. The satellite imagery data were most useful in areas with low station density. The interpolation technique allowed WorldClim to produce high spatial resolution (approximately 1 km2) raster data sets.

The National Forest Climate Change Maps project was developed by the Rocky Mountain Research Station (RMRS) and the Office of Sustainability and Climate to meet the needs of national forest managers for information on projected climate changes at a scale relevant to decision making processes, including forest plans. The maps use state-of-the-art science and are available for every national forest in the contiguous United States with relevant data coverage. Currently, the map sets include variables related to precipitation, air temperature, snow (including snow residence time and April 1 snow water equivalent), and stream flow.Historical (1975-2005) and future (2071-2090) precipitation and temperature data for the contiguous United States are ensemble mean values across 20 global climate models from the CMIP5 experiment (https://journals.ametsoc.org/doi/abs/10.1175/BAMS-D-11-00094.1), downscaled to a 4 km grid. For more information on the downscaling method and to access the data, please see Abatzoglou and Brown, 2012 (https://rmets.onlinelibrary.wiley.com/doi/full/10.1002/joc.2312) and the Northwest Knowledge Network (https://climate.northwestknowledge.net/MACA/). We used the MACAv2- Metdata monthly dataset; monthly precipitation values (mm) were summed over the season of interest (annual, winter, or summer). Absolute and percent change were then calculated between the historical and future time periods.Raster data are also available for download from RMRS site (https://www.fs.usda.gov/rm/boise/AWAE/projects/NFS-regional-climate-change-maps/categories/us-raster-layers.html), along with pdf maps and detailed metadata (https://www.fs.usda.gov/rm/boise/AWAE/projects/NFS-regional-climate-change-maps/downloads/NationalForestClimateChangeMapsMetadata.pdf).

This map is part of a series of global climate images produced by the Agrometeorology Group and based on data for mean monthly values of temperature, precipitation and cloudiness prepared in 1991 by R. Leemans and W. Cramer and published by the International Institute for Applied Systems Analysis (IIASA). For each of the weather stations used data have been assembled over a long time period - usually between 1961 and 1990 - and then averaged. Annual totals for rainfall were derived from the monthly values.

The WMS Service (Web Map Service) called Annual Average Precipitation (1940/41-2005/06) allows the visualization and consultation of this cartography that contains, in each pixel, the annual average precipitation in the period 1940-2005 in natural regime used for the calculation of the contributions from the SIMPA model. The URL of the WMS Service is: https://wms.mapama.gob.es/sig/water/EvalRecHidricos/1940_2005/Precipitacion/wms.aspx The reference systems offered by this service are: - For geographical coordinates: CRS: 84, EPSG: 4230 (ED50), EPSG:4326 (WGS 84), EPSG:4258 (ETRS 89). - For U.T.M coordinates: EPSG:32628 (WGS 84 / UTM zone 28N), EPSG:32629 (WGS 84 / UTM zone 29N), EPSG:32630 (WGS 84 / UTM zone 30N), EPSG:32631 (WGS 84 / UTM zone 31N), EPSG:25828 (ETRS 89 / UTM zone 28N), EPSG:25829 (ETRS 89 / UTM zone 29N), EPSG:25830 (ETRS 89 / UTM zone 30N), EPSG:25831 (ETRS 89 / UTM zone 31N), EPSG:23028 (ED50 / UTM zone 28N), EPSG:23029 (ED50 / UTM zone 29N), EPSG:23030 (ED50 / UTM zone 30N), EPSG:23031 (ED50 / UTM zone 31N).

Information on precipitation includes mean annual precipitation (MAP) ± the standard deviation of annual precipitation and (in parentheses) the minimum annual precipitation recorded in 1971–2006. Because rainfall data from Kuke do not exist, the values reported are from Ghanzi.

Contained within the 3rd Edition (1957) of the Atlas of Canada is a plate that shows two maps for the annual total precipitation. Annual precipitation is defined as the sum of rainfall and the assumed water equivalent of snowfall for a given year. A specific gravity of 0.1 for freshly fallen snow is used, which means that ten inches (25.4 cm) of freshly fallen snow is assumed to be equal to one inch (2.54 cm) of rain. The mean annual total precipitation and snowfall maps on this plate are primarily based on thirty-year data during the period 1921 to 1950 inclusive.

1km gridded Rainfall map - interpolation over DEM. Rainfall data scattered well except Western and Southern Highlands Provinces. With the Digicel Towers (mounted with rainfall instruments) network nation-wide. The Rainfall Map can be improved.

[Metadata] Mean Annual Rainfall Isohyets in Millimeters for the Islands of Hawai‘i, Kaho‘olawe, Kaua‘i, Lāna‘i, Maui, Moloka‘i and O‘ahu. Source: 2011 Rainfall Atlas of Hawaii, https://www.hawaii.edu/climate-data-portal/rainfall-atlas. Note that Moloka‘I data/maps were updated in 2014. Please see Rainfall Atlas final report appendix for full method details: https://www.hawaii.edu/climate-data-portal/rainfall-atlas. Statewide GIS program staff downloaded data from UH Geography Department, Rainfall Atlas of Hawaii, February, 2019. Annual and monthly isohyets of mean rainfall were available for download. The statewide GIS program makes available only the annual layer. Both the monthly layers and the original annual layer are available from the Rainfall Atlas of Hawaii website, referenced above. Note: Contour attribute value represents the amount of annual rainfall, in millimeters, for that line/isohyet. For additional information, please see metadata at https://files.hawaii.gov/dbedt/op/gis/data/isohyets.pdf or contact Hawaii Statewide GIS Program, Office of Planning and Sustainable Development, State of Hawaii; PO Box 2359, Honolulu, Hi. 96804; (808) 587-2846; email: gis@hawaii.gov; Website: https://planning.hawaii.gov/gis.

The National Forest Climate Change Maps project was developed by the Rocky Mountain Research Station (RMRS) and the Office of Sustainability and Climate to meet the needs of national forest managers for information on projected climate changes at a scale relevant to decision making processes, including forest plans. The maps use state-of-the-art science and are available for every national forest in the contiguous United States with relevant data coverage. Currently, the map sets include variables related to precipitation, air temperature, snow (including snow residence time and April 1 snow water equivalent), and stream flow.Historical (1975-2005) and future (2071-2090) precipitation and temperature data for the state of Alaska were developed by the Scenarios Network for Alaska and Arctic Planning (SNAP) (https://snap.uaf.edu). Monthly precipitation values (mm) were summed over the season of interest (annual, winter, or summer). These datasets have several important differences from the MACAv2-Metdata (https://climate.northwestknowledge.net/MACA/) products, used in the contiguous U.S. They were developed using different global circulation models and different downscaling methods, and were downscaled to a different scale (771 m instead of 4 km). While these cover the same time periods and use broadly similar approaches, caution should be used when directly comparing values between Alaska and the contiguous United States.Raster data are also available for download from RMRS site (https://www.fs.usda.gov/rm/boise/AWAE/projects/NFS-regional-climate-change-maps/categories/us-raster-layers.html), along with pdf maps and detailed metadata (https://www.fs.usda.gov/rm/boise/AWAE/projects/NFS-regional-climate-change-maps/downloads/NationalForestClimateChangeMapsMetadata.pdf).

The Annual Mean Rainfall dataset was created using ANUCLIM software and the 1 second SRTM DEM-S (smoothed Digital Elevation Model) data. Climate variables generated by ANUCLIM (Version 6.1 MTHCLIM module) depend on a digital elevation model. Monthly mean climate values for the 1976-2005 periods are used to generate the surface. Grid resolution is 1 second or approximately 30m.

This dataset provides lines of equal average annual precipitation for water years 1961-90 in the Black Hills area of South Dakota.

Rain is vital for life – it supplies the water we need to drink and to grow our food, keeps our ecosystems healthy, and supplies our electricity. New Zealand’s mountainous terrain and location in the roaring forties mean rainfall varies across the country. Changes in rainfall amount or timing can significantly affect agriculture, energy, recreation, and the environment. For example, an increase or decrease of rainfall in spring can have marked effects on crops or fish populations.
More information on this dataset and how it relates to our environmental reporting indicators and topics can be found in the attached data quality pdf.

This dataset contains annual average precipitation from the four models and two greenhouse gas (RCP) scenarios included in the four model ensemble for the years 1950-2099. The downscaling and selection of models for inclusion in ten and four model ensembles is described in Pierce et al. 2018, but summarized here. Thirty two global climate models (GCMs) were identified to meet the modeling requirements. From those, ten that closely simulate California’s climate were selected for additional analysis (Table 1, Pierce et al. 2018) and to form a ten model ensemble. From the ten model ensemble, four models, forming a four model ensemble, were identified to provide coverage of the range of potential climate outcomes in California. The models in the four model ensemble and their general climate projection for California are: HadGEM2-ES (warm/dry),CanESM2 (average), CNRM-CM5 (cooler/wetter),and MIROC5 the model least like the others to improve coverage of the range of outcomes. These data were downloaded from Cal-Adapt and prepared for use within CA Nature by California Natural Resource Agency and ESRI staff. Cal-Adapt. (2018). LOCA Derived Data [GeoTIFF]. Data derived from LOCA Downscaled CMIP5 Climate Projections. Cal-Adapt website developed by University of California at Berkeley’s Geospatial Innovation Facility under contract with the California Energy Commission. Retrieved from https://cal-adapt.org/ Pierce, D. W., J. F. Kalansky, and D. R. Cayan, (Scripps Institution of Oceanography). 2018. Climate, Drought, and Sea Level Rise Scenarios for the Fourth California Climate Assessment. California’s Fourth Climate Change Assessment, California Energy Commission. Publication Number: CNRA-CEC-2018-006.

The National Forest Climate Change Maps project was developed by the Rocky Mountain Research Station (RMRS) and the Office of Sustainability and Climate to meet the needs of national forest managers for information on projected climate changes at a scale relevant to decision making processes, including forest plans. The maps use state-of-the-art science and are available for every national forest in the contiguous United States with relevant data coverage. Currently, the map sets include variables related to precipitation, air temperature, snow (including snow residence time and April 1 snow water equivalent), and stream flow.\Historical (1975-2005) and future (2071-2090) precipitation and temperature data for the contiguous United States are ensemble mean values across 20 global climate models from the CMIP5 experiment (https://journals.ametsoc.org/doi/abs/10.1175/BAMS-D-11-00094.1), downscaled to a 4 km grid. For more information on the downscaling method and to access the data, please see Abatzoglou and Brown, 2012 (https://rmets.onlinelibrary.wiley.com/doi/full/10.1002/joc.2312) and the Northwest Knowledge Network (https://climate.northwestknowledge.net/MACA/). We used the MACAv2- Metdata monthly dataset; monthly precipitation values (mm) were summed over the season of interest (annual, winter, or summer). Absolute and percent change were then calculated between the historical and future time periods.Historical (1975-2005) and future (2071-2090) precipitation and temperature data for the state of Alaska were developed by the Scenarios Network for Alaska and Arctic Planning (SNAP) (https://snap.uaf.edu). These datasets have several important differences from the MACAv2-Metdata (https://climate.northwestknowledge.net/MACA/) products, used in the contiguous U.S. They were developed using different global circulation models and different downscaling methods, and were downscaled to a different scale (771 m instead of 4 km). While these cover the same time periods and use broadly similar approaches, caution should be used when directly comparing values between Alaska and the contiguous United States.Raster data are also available for download from RMRS site (https://www.fs.usda.gov/rm/boise/AWAE/projects/NFS-regional-climate-change-maps/categories/us-raster-layers.html), along with pdf maps and detailed metadata (https://www.fs.usda.gov/rm/boise/AWAE/projects/NFS-regional-climate-change-maps/downloads/NationalForestClimateChangeMapsMetadata.pdf).

These data represent mean annual precipitation (in inches) for Idaho for the climatological period 1961-90. Average annual precipitation is the average of the annual amount of precipitation for a location over a year. Data used to delineate these boundaries are from Idaho weather stations (1961-90).Source data for this web service can be downloaded from https://insideidaho.org/data/ago/ics/ppt_id_ics.zip.A printed map is available: https://alliance-primo.hosted.exlibrisgroup.com/permalink/f/m1uotc/CP71168920310001451 from the University of Idaho Map Room. Additionally, a related research report is available: https://alliance-primo.hosted.exlibrisgroup.com/permalink/f/m1uotc/CP71180601950001451.Related data set: Weather Stations Used to Compile the Mean Annual Precipitation Map for Idaho

Average annual rainfall in Djibouti, Eritrea, Ethiopia, Kenya, Somalia, Sudan and Uganda.

Total annual precipitation is shown along with elevation hillshade using the NAGI method. Hillshade is from Esri Elevation Service, and precipitation data is taken from WMO and FAO rain gages in addition to a number of national datasets. The annual and monthly averages for the period 1950-2000 was calculated and interpolated by WorldClim.org, a collaboration between the University of California, Berkeley, the International Cetner for Tropical Agrilculture, and the Cooperative Research Centre for Tropical Rainforest Ecology and Management.

The soil map of Valle d'Aosta, drawn up on a scale of 1:100,000, represents a fundamental tool for land management. It constitutes a synthesis of the types of soil present at the regional level, helping to provide indispensable information for resource management agro-forestry and environmental aspects of the region.

Precipitation in Mali increased to 377.27 mm in 2024 from 309.75 mm in 2023. This dataset includes a chart with historical data for Mali Average Precipitation.