This dataset provides values for PRECIPITATION reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

The average for 2022 based on 53 countries was 1004 mm per year. The highest value was in Sao Tome and Principe: 3200 mm per year and the lowest value was in Egypt: 18 mm per year. The indicator is available from 1961 to 2022. Below is a chart for all countries where data are available.

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/

Precipitation in South Africa decreased to 417.47 mm in 2024 from 495.09 mm in 2023. This dataset includes a chart with historical data for South Africa Average Precipitation.

This map features the GLDAS total monthly precipitation modeled globally by NASA. The map shows the monthly precipitation for the period of May 2016 to May 2018, focused on Africa. You can click the Play button on the time slider to see precipitation over time.Great parts of Northern Africa and Southern Africa, as well as the whole Horn of Africa, mainly have a hot desert climate, or a hot semi-arid climate for the wetter locations. The equatorial region near the Intertropical Convergence Zone is the wettest portion of the continent. Annually, the rain belt across the country marches northward into Sub-Saharan Africa by August, then moves back southward into south-central Africa by March.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-2.1). The model is run with 3-hourly time steps and aggregated into monthly averages. A complete list of the model inputs can be seen here, and the output data (in GRIB format) is available here.Phenomenon Mapped: PrecipitationUnits: MillimetersTime Interval: MonthlyTime Extent: 2000/01/01 to presentCell Size: 28 kmSource Type: ScientificPixel Type: Signed IntegerData Projection: GCS WGS84Mosaic Projection: Web Mercator Auxiliary SphereExtent: Global Land SurfaceSource: NASAUpdate Cycle: SporadicWhat 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.By applying the "Calculate Anomaly" processing template, it is also possible to view these data in terms of deviation from the mean, instead of total evapotranspiration. Mean evapotranspiration for a given month is calculated over the entire period of record - 2000 to present.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 eight years.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, or by applying the relevant raster function. 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.

The 'Climate change in Africa' dataset was provided by the U.S global change research program.

Dataset description : This dataset contains historical data about the daily min, max and average temperature fluctuation in 5 African countries (Egypt, Tunisia, Cameroon, Senegal, Angola) between 1980 and 2023.

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).

Average Rainfall for the Months (June to September) from 2010 to 2019

This data set describes rainfall distribution statistics over the African continent, including Madagascar. The rainfall estimates are based on data from the NASA Tropical Rainfall Measuring Mission (TRMM) measured between 1998 and 2012. Rainfall patterns were quantified using a gamma-based function and two Markov chain parameters with the aim to summarize the rainfall pattern to a small number of parameters and processes. These summary statistics are suitable for temporal downscaling.These data provide gridded (0.25 x 0.25-degree) estimates of 14-year mean monthly rainfall total amount (mm), frequency (count), intensity (mm/hr), and duration (hrs) of rainfall, as well as Markov chain and gamma-distribution parameters for use in temporal downscaling. The data are presented as a series of 12 netCDF (*.nc) files.

The Microwave InfraRed Algorithm (MIRA) is used to produce an imagery data set of daily mean rain rates at 0.1 degree spatial resolution over southern Africa for the period 1993-2001. MIRA combines passive microwave (PMW) from the Special Sensor Microwave/Imager (SSM/I) on board the DMSP F10 and F14 satellites at a resolution of 0.5 degrees and infrared (IR) data from the Meteosat 4, 5, 6, and 7 satellites in 2-hour slots at a resolution of 5 km. This approach accounts for the limitations of both data types in estimating precipitation. Rainfall estimates are produced at the high spatial and temporal frequency of the IR data using rainfall information from the PMW data. An IR/rain rate relationship, variable in space and time, is derived from coincident observations of IR and PMW rain rate (accumulated over a calibration domain) using the probability matching method. The IR/rain rate relationship is then applied to IR imagery at full temporal resolution. The results presented here are the daily means of those derived rain rates at 0.1 degree spatial resolution.The rainfall data sets are flat binary images with no headers. They are compressed band sequential (bsq) files that contain all of the daily images for the given year. Each image is an array of 341 lines, each with 401 binary floating-point numbers, containing rainfall at 0.1 degree resolution for the area 10 to 50 degrees longitude and 0 to -34 degrees latitude. The number of band sequential images in each annual file and the associated dates can be found in the file MIRA_data_dates.csv.

Maps on monthly total rainfall amount (in millimeters) and monthly rainfall percentage of normals 1961-1990 (in percentage) from August 2004 to October 2008 are available here for download for Western Africa. Rainfall data are also available in GeoNetwork for the whole African continent and the following Regions : Northern Africa, Western Africa, Eastern Africa and Southern Africa. An interpolation method (Kriging) is applied to input data. Data input for rainfall maps are provided by Global Precipitation Climatology Centre (GPCC) operated by the Deutscher Wetterdienst (DWD, National Meteorological Service of Germany). GPCC First Guess Product, gauge-based gridded monthly precipitation data sets for the global land surface, at spatial resolutions of 1.0 x 1.0 degrees geographical latitude by longitude are used. The First Guess Product of the monthly precipitation anomaly is based on interpolated precipitation anomalies from about 6,000 stations worldwide. Data sources are synoptic weather observation data (SYNOP) received at DWD via the WMO Global Telecommunication System (GTS) and climatic mean (mainly 1961-1990) monthly precipitation totals at the same stations extracted from GPCC s global normals collection. An automatic-only quality-control (QC) is applied to these data. Since September 2003, GPCC First Guess monthly precipitation analyses are available within 5 days after end of an observation month.

The average for 2022 based on 47 countries was 1113 mm per year. The highest value was in Sao Tome and Principe: 3200 mm per year and the lowest value was in Mauritania: 92 mm per year. The indicator is available from 1961 to 2022. Below is a chart for all countries where data are available.

East Africa is a drought prone, food and water insecure region with a highly variable climate. This complexity makes rainfall estimation challenging, and this challenge is compounded by low rain gauge densities and inhomogeneous monitoring networks. The dearth of observations is particularly problematic over the past decade, since the number of records in globally accessible archives has fallen precipitously. This lack of data coincides with an increasing scientific and humanitarian need to place recent seasonal and multi-annual East African precipitation extremes in a deep historic context. To serve this need, scientists from the UC Santa Barbara Climate Hazards Group and Florida State University have pooled their station archives and expertise to produce a high quality gridded 'Centennial Trends' precipitation dataset. Additional observations have been acquired from the national meteorological agencies and augmented with data provided by other universities. Extensive quality control of the data was carried out and seasonal anomalies interpolated using kriging. This paper documents the CenTrends methodology and data.

South Africa: Precipitation, mm per year: The latest value from 2022 is 495 mm per year, unchanged from 495 mm per year in 2021. In comparison, the world average is 1176 mm per year, based on data from 176 countries. Historically, the average for South Africa from 1961 to 2022 is 495 mm per year. The minimum value, 495 mm per year, was reached in 1961 while the maximum of 495 mm per year was recorded in 1961.

Exploring the predictability of weather-within-climate variability of rainfall using the North Atlantic SST Relative Index (NARI) - Total Rainfall - Number of Wet Days - Rainfall Intensity - Number of Dry Spells - Number of Wet Spells 3 rainfall datasets (TAMSAT v3, CHIRPS, and ARC2) are used individually with the NARI to calculate the tercile probabilities of 5 rainfall characteristics of West Africa 1983-2014.

Precipitation in Central African Republic decreased to 1319.98 mm in 2024 from 1400.99 mm in 2023. This dataset includes a chart with historical data for Central African Republic Average Precipitation.

This archived Paleoclimatology Study is available from the NOAA National Centers for Environmental Information (NCEI), under the World Data Service (WDS) for Paleoclimatology. The associated NCEI study type is Lake. The data include parameters of climate reconstructions|insect|paleolimnology with a geographic location of Kenya, Eastern Africa. The time period coverage is from 1070 to -44 in calendar years before present (BP). See metadata information for parameter and study location details. Please cite this study when using the data.

Sharon Nicholson at Florida State University compiled this dataset of monthly rainfall totals for African stations. The period covered is 1901 to 1984.

Climate change, that is a threat to ecosystems and the livelihoods of those that depend on them, is increasingly manifesting as an increased frequency and intensity of severe weather events such as droughts and floods (Déqué et al., 2017). Climate change has created an urgent need for early warning aids or models to enhance the sub-Saharan African health systems ability to prepare for, and cope with escalations in treatment needs of climate sensitive diseases (Nhamo & Muchuru, 2019). This dataset was created from the health and weather data of nine purposively selected study districts in Uganda, whose health and weather data were available for the development of an early warning health model (https://github.com/CHAIUGA/chasa-model) and an accompanying prediction web app (https://github.com/CHAIUGA/chasa-webapp). The districts were selected based on the following criteria: (a) were experiencing climate change and variability, (b) represented different climatologic, and agro-ecological zones, (c) availability of climate information and health information from a health facility within a 40 kilometres radius of a functional weather station. Historical weather data was retrieved from the Uganda National Meteorological Association databases, as monthly averages. The weather variables in this data included: atmospheric pressure, rainfall, solar radiation, humidity, temperature (maximum, minimum and mean), and wind (gusts and average wind speed). The monthly health aggregated data for the period starting September 2018 to December 2019, was retrieved from the National Health Repository (DHIS2) for referral hospitals within the selected districts. Only data for a selection of climate-sensitive disease aggregates was obtained. The dataset contains 436 complete matched disease and weather records. Ethical issues: Both the de-identified aggregate monthly disease diagnosis count data and weather data in this dataset are from national data available to the public on request.

The TAMSAT rainfall estimates are based on Meteosat thermal infrared imagery, calibrated against ground-based rain gauge measurements, and cover all of Africa. The products also include rainfall anomalies. They are available in different frequencies: daily, pentadal, dekadal, monthly and seasonal.