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 to meet the need 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 and air temperature, including both Alaskan and lower 48 datasets. Data from the lower 48 were downloaded from here: https://www.fs.usda.gov/rm/boise/AWAE/projects/national-forest-climate-change-maps.html, and Alaskan data came from here: https://www.snap.uaf.edu/tools/data-downloads. Historical data are compared with RCP 8.5 projections from the 2080s.A Raster Function Template is available in this service that will classify the data as originally intended by OSC. The RFT currently works in AGOL but not in ArcGIS Pro.This 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: ISO-19139 metadata ArcGIS Hub Dataset ArcGIS GeoService For complete information, please visit https://data.gov.

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.

The National Forest Climate Change Maps project was developed to meet the need 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 and air temperature, including both Alaskan and lower 48 datasets. Data from the lower 48 were downloaded from here: https://www.fs.usda.gov/rm/boise/AWAE/projects/national-forest-climate-change-maps.html, and Alaskan data came from here: https://www.snap.uaf.edu/tools/data-downloads. Historical data are compared with RCP 8.5 projections from the 2080s.A Raster Function Template is available in this service that will classify the data as originally intended by OSC. The RFT currently works in AGOL but not in ArcGIS Pro.This 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: ISO-19139 metadata ArcGIS Hub Dataset ArcGIS GeoService For complete information, please visit https://data.gov.

Average Annual Rainfall, Africa, 1960-90, millimeters per year. Data from CCAFS/ILRI. Map published in Atlas of African Agriculture Research & Development (K. Sebastian (Ed.) 2014). p.38-39 Rainfall and Rainfall Variability. Contributor: Philip Thornton.For more information: http://agatlas.org/contents/rainfall-and-rainfall-variability/

The plate contains four maps of 24 hour rainfalls (in millimetres) for a 2 year return period, a 5 year return period, a 10 year return period and a 25 year return period. Each map has a detailed inset of the Vancouver area. These four maps were not analyzed for the mountainous parts of Canada in British Columbia and the Yukon because of the limited number of stations, the non-representative nature of the valley stations and the variability of precipitation owing to the orographic effects. From the incomplete data, it is impossible to draw accurate isolines of short duration rainfall amounts on maps of national scale. Point values for all stations west of the Rocky Mountain range and in the Yukon have been plotted for durations of less than 24 hours. For the Vancouver metropolitan area, recording rain gauges have been in operation for several years. For some of these stations point rainfall data have been plotted on inset maps. The density of climatological stations varies widely as does population density. In general, the accuracy of the analysis increases with station density. North of latitude 55 degrees North, there are only five stations. Therefore, the isoline analyses represent extrapolations beyond the station values. Whenever sufficient data were available for interpretation, isolines were drawn as solid lines. The scale of the map used for Canada dictates the use of an isoline interval of 12 millimetres.

Result of a long experience in cooperation with the African meteorological departments and of the management of data bases, this map displays the annual rainfalls over a 60-year period. Maps representing rainfall over the whole African continent are rare, and a map dealing with observed rainfall over such a long period has never been released. Measurements of almost 6,000 raingauges were used for the calculation of mean values. This dataset contains in shapefiles format ArcGis : 1-isohyets of the annual Rainfall Map of Africa 2-isohyets that show the shifting of the isohyetal lines on the small map . Grids of rainfall at a step of half square degree and at a monthly time step are provided on the website of SIEREM (Environmental Information System for Water Resources and Modelling). Fruit d'une longue expérience de coopération avec les services climatologiques africains et de gestion de bases de données, cette carte affiche les pluies annuelles sur une période de 60 ans. Rares sont les cartes représentant les pluies observées sur la totalité du continent africain, et inédite une carte traitant de ce sujet sur une période aussi longue. Les mesures de près de 6 000 postes ont été utilisées pour le calcul des valeurs moyennes. Tous les fichiers de données sont au format ArcGIS (shapefiles) et contiennent : 1- Isohyètes de la carte des pluies annuelles en Afrique 2- Isohyètes qui montrent le déplacement des isohyètes sur la période Des grilles de pluies au pas du demi-degré carré et au pas de temps mensuel sont mises à disposition sur le site de SIEREM (Système d'informations environnementales pour les ressources en eau et leur modélisation).

Precipitation is derived from water vapour in the air, and it includes all forms of moisture falling on the earth's surface. Condensed water vapour accumulates in clouds, and precipitation occurs when the constituent ice crystals or water droplets grow too large to resist gravitational attraction to earth. The atmospheric moisture lost through precipitation is replenished by transpiration from vegetation, and by evaporation from the soil and from water bodies. The oceans, which cover 71 per cent of the earth's surface, are the primary source, though large fresh water bodies may be important locally, particularly in more southern latitudes. The map shows the annual precipitation (in millimetres) based on the 30-year period 1941 – 1970. The map was prepared from measurements at stations in the national precipitation network. In 1974 this network consisted of about 2700 stations, however, many have been in existence for only short periods. For statistical analysis a long series of data is required. To begin the map, those stations having a complete 25-year record for the standard normal period 1941-1970 were selected. The average yearly precipitation value for each station was plotted on a 1:5,000,000-scale relief map. The density of stations was too coarse for isoline interpolation, particularly in arctic and mountainous regions. For additional detail, all stations with a continuous record of 10-24 years were then sorted from the archive file and scrutinized. It was possible in many cases to adjust the mean values to the 30-year normal period by assuming a constant difference between the short-period station and a nearby long-term reference station. The computed correction indices occasionally gave erroneous values however, even following elevation slope adjustments. It was assumed that these inconsistencies resulted from the reference station being too far distant or from dissimilarity in site characteristics. In the end, three sets of points were plotted, using colour codes to denote confidence. A station with a full record was considered accurate for that point; though isoline interpolation would take into account the surrounding terrain. A station with a shorter record, but which had been successfully adjusted, was considered almost as good as the long term station. Stations that could not be adjusted were treated as guidance points only. In remote areas greater reliance had to be allocated to these stations, but this was compensated by a more conservative approach to isoline selection. For reasons of scale the isoline interval is greater in the Western Cordillera than for the rest of Canada. Final modifications to the map were based on a review of previously constructed maps, and a survey of special precipitation measurements and research undertaken in mountainous and other imperfectly known regions.

This data set reflects National Weather Service (NWS) and National Resources Conservation Service (NRCS) stations for the state of Idaho. There are 213 stations in this data set and these are the stations used to compile the mean annual precipitation map for Idaho which was created by Myron Molnau.Source data for this web service can be downloaded from https://insideidaho.org/data/ago/ics/weatStns_id_ics.zip.Related data set: Precipitation for Idaho; Mean Annual (1961-90)

[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.

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.

Precipitation in Panama increased to 2565.07 mm in 2024 from 2258.81 mm in 2023. This dataset includes a chart with historical data for Panama Average Precipitation.

This EnviroAtlas dataset provides the average annual precipitation by 12-digit Hydrologic Unit (HUC). The values were estimated from maps produced by the PRISM Climate Group, Oregon State University. The original data was at the scale of 800 m grid cells representing average precipitation from 1981-2010 in mm. The data was converted to inches of precipitation and then zonal statistics were estimated for a final value of average annual precipitation for each 12 digit HUC. For more information about the original dataset please refer to the PRISM website at http://www.prism.oregonstate.edu/. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

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.

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.

Precipitation in Iraq increased to 194.25 mm in 2024 from 189.67 mm in 2023. This dataset includes a chart with historical data for Iraq Average Precipitation.

Projected change in average number of days of precipitation (>0.1 inch) between 1985-2005 and 2071-2090 (RCP 8.5) time periods

Precipitation is water released from clouds in the form of rain, sleet, snow, or hail. It is the primary source of recharge to the planet's fresh water supplies. This map contains a historical record showing the volume of precipitation that fell during each month from March 2000 to the present. Snow and hail are reported in terms of snow water equivalent - the amount of water that will be produced when they melt. Dataset SummaryThe GLDAS Precipitation layer is a time-enabled image service that shows average monthly precipitation from 2000 to the present, measured in millimeters. It is calculated by NASA using the Noah land surface model, run at 0.25 degree spatial resolution using satellite and ground-based observational data from the Global Land Data Assimilation System (GLDAS-1). The model is run with 3-hourly time steps and aggregated into monthly averages. Review the complete list of model inputs, explore the output data (in GRIB format), and see the full Hydrology Catalog for all related data and information!What can you do with this layer?This layer is suitable for both visualization and analysis. It can be used in ArcGIS Online in web maps and applications and can be used in ArcGIS for Desktop. It is useful for scientific modeling, but only at global scales.Time: This is a time-enabled layer. It shows the total evaporative loss during the map's time extent, or if time animation is disabled, a time range can be set using the layer's multidimensional settings. The map shows the sum of all months in the time extent. Minimum temporal resolution is one month; maximum is one year.Variables: This layer has two variables: rainfall and snowfall. By default the two are summed, but you can view either by itself using the multidimensional filter. You must disable time animation on the layer before using its multidimensional filter.Important: You must switch from the cartographic renderer to the analytic renderer in the processing template tab in the layer properties window before using this layer as an input to geoprocessing tools.This layer has query, identify, and export image services available.This layer is part of a larger collection of earth observation maps that you can use to perform a wide variety of mapping and analysis tasks.The Living Atlas of the World provides an easy way to explore the earth observation layers and many other beautiful and authoritative maps on hundreds of topics.Geonet is a good resource for learning more about earth observations layers and the Living Atlas of the World. Follow the Living Atlas on GeoNet.

This dataset provides lines of equal average annual precipitation for water years 1950-98 in the Black Hills area of South Dakota and Wyoming.

What does the data show?

This data shows annual averages of precipitation (mm/day) for 2050-2079 from the UKCP18 regional climate projections. The data is for the high emissions scenario (RCP8.5).

Limitations of the data

We recommend the use of multiple grid cells or an average of grid cells around a point of interest to help users get a sense of the variability in the area. This will provide a more robust set of values for informing decisions based on the data.

What are the naming conventions and how do I explore the data?

This data contains a field for the average over the period. They are named 'pr' (precipitation), the month, and 'upper' 'median' or 'lower'. E.g. 'pr Median' is the median value.

To understand how to explore the data, see this page: https://storymaps.arcgis.com/stories/457e7a2bc73e40b089fac0e47c63a578

Please note, if viewing in ArcGIS Map Viewer, the map will default to ‘pr January Median’ values.

What do the ‘median’, ‘upper’, and ‘lower’ values mean?

Climate models are numerical representations of the climate system. To capture uncertainty in projections for the future, an ensemble, or group, of climate models are run. Each ensemble member has slightly different starting conditions or model set-ups. Considering all of the model outcomes gives users a range of plausible conditions which could occur in the future.

For this dataset, the model projections consist of 12 separate ensemble members. To select which ensemble members to use, the annual averages of precipitation for 2050-2079 were calculated for each ensemble member and they were then ranked in order from lowest to highest for each location.

The ‘lower’ fields are the second lowest ranked ensemble member. The ‘upper’ fields are the second highest ranked ensemble member. The ‘median’ field is the central value of the ensemble.

This gives a median value, and a spread of the ensemble members indicating the range of possible outcomes in the projections. This spread of outputs can be used to infer the uncertainty in the projections. The larger the difference between the lower and upper fields, the greater the uncertainty.

Data source

pr_rcp85_land-rcm_uk_12km_12_ann-30y_200912-207911.nc (median)

pr_rcp85_land-rcm_uk_12km_05_ann-30y_200912-207911.nc (lower)

pr_rcp85_land-rcm_uk_12km_04_ann-30y_200912-207911.nc (upper)

UKCP18 v20190731 (downloaded 04/11/2021)

Useful links

Further information on the UK Climate Projections (UKCP). Further information on understanding climate data within the Met Office Climate Data Portal