Africa climate and weather data

Dekadal (10 days) Combined Drought Indicator (CDI) as implemented in the East Africa Drought Watch, and which is used for detecting and monitoring areas that either are affected or have the potential to be affected by meteorological, agricultural and/or hydrological drought.

Monthly Combined Drought Indicator (CDI) as implemented in the East Africa Drought Watch, and which is used for detecting and monitoring areas that either are affected or have the potential to be affected by meteorological, agricultural and/or hydrological drought.

Dekadal (10 days) Combined Drought Indicator (CDI) as implemented in the East Africa Drought Watch, and which is used for detecting and monitoring areas that either are affected or have the potential to be affected by meteorological, agricultural and/or hydrological drought.

Monthly Combined Drought Indicator (CDI) as implemented in the East Africa Drought Watch, and which is used for detecting and monitoring areas that either are affected or have the potential to be affected by meteorological, agricultural and/or hydrological drought.

Dekadal (10 days) Combined Drought Indicator (CDI) as implemented in the East Africa Drought Watch, and which is used for detecting and monitoring areas that either are affected or have the potential to be affected by meteorological, agricultural and/or hydrological drought.

Monthly Combined Drought Indicator (CDI) as implemented in the East Africa Drought Watch, and which is used for detecting and monitoring areas that either are affected or have the potential to be affected by meteorological, agricultural and/or hydrological drought.

Monthly Combined Drought Indicator (CDI) as implemented in the East Africa Drought Watch, and which is used for detecting and monitoring areas that either are affected or have the potential to be affected by meteorological, agricultural and/or hydrological drought.

Dekadal(10days) Combined Drought Indicator (CDI) as implemented in the East Africa Drought Watch, and which is used for detecting and monitoring areas that either are affected or have the potential to be affected by meteorological, agricultural and/or hydrological drought.

Dekadal(10days) Combined Drought Indicator (CDI) as implemented in the East Africa Drought Watch, and which is used for detecting and monitoring areas that either are affected or have the potential to be affected by meteorological, agricultural and/or hydrological drought.

Monthly Combined Drought Indicator (CDI) as implemented in the East Africa Drought Watch, and which is used for detecting and monitoring areas that either are affected or have the potential to be affected by meteorological, agricultural and/or hydrological drought.

Dekadal (10 days) Combined Drought Indicator (CDI) as implemented in the East Africa Drought Watch, and which is used for detecting and monitoring areas that either are affected or have the potential to be affected by meteorological, agricultural and/or hydrological drought.

Monthly Combined Drought Indicator (CDI) as implemented in the East Africa Drought Watch, and which is used for detecting and monitoring areas that either are affected or have the potential to be affected by meteorological, agricultural and/or hydrological drought.

Dekadal (10 days) Combined Drought Indicator (CDI) as implemented in the East Africa Drought Watch, and which is used for detecting and monitoring areas that either are affected or have the potential to be affected by meteorological, agricultural and/or hydrological drought.

Monthly Combined Drought Indicator (CDI) as implemented in the East Africa Drought Watch, and which is used for detecting and monitoring areas that either are affected or have the potential to be affected by meteorological, agricultural and/or hydrological drought.

Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) is a 35+ year quasi-global rainfall data set. It is a gridded rainfall time series for trend analysis and seasonal drought monitoring, spans 50°S-50°N (and all longitudes) and ranges from 1981 to near-present. The anomaly refers to the difference between current rainfall and the average rainfall that occurred between 1981 and 2010 in millimeters. For more information visit the CHIRPS site. This dataset contains the latest available CHIRPS anomaly data. The full list of data available is available from USGS for Mar-May data, Oct-Dec data, and others. Additionally, subnational statistics (mean, min, max) have been calculated for Ethiopia, Kenya, and Somalia and are available in the csv resource.

This version of the Combined Drought Indicator (CDI) utilizes ERA5 reanalysis data as the primary input for the precipitation component (SPI), rather than gauge-only or other satellite-blended products. ERA5, produced by ECMWF, offers comprehensive spatial coverage and temporal consistency, making it valuable for regions where gauge networks are failing or sparse. Like the standard CDI, this dataset synthesizes rainfall deficits (via ERA5), soil moisture anomalies, and vegetation stress into a single classification system to monitor the evolution of drought episodes.

The Standardized Precipitation Index (SPI) is the globally recommended standard for characterizing meteorological drought. It quantifies observed precipitation as a standardized deviation from the long-term probability distribution function for a specific location and time scale. This dataset typically includes multiple time-scales (e.g., 1-month, 3-month, 6-month, 12-month) to capture different types of drought impacts, from immediate soil moisture deficits to long-term hydrological stress. Because SPI is normalized, it allows for safe comparisons between different climatic zones—allowing a wet region and a dry region to be compared on the same scale of drought severity.

Seasonal rainfall accumulation anomaly for East Africa derived from CHIRPS data, showing deviation from the 1981-2010 historical average in millimetres. Use this layer for drought early warning, seasonal forecast validation, agricultural planning, and humanitarian response in the Horn of Africa.

The Global Precipitation Climatology Centre (GPCC) Monthly Precipitation dataset provides gridded gauge-analysis products focusing on land-surface precipitation. This dataset serves as a high-quality observational baseline for climate monitoring across Africa. It is constructed from quality-controlled data from thousands of rain gauges worldwide. At ACMAD, this data often serves as the "truth" or reference layer for calibrating satellite estimates and for calculating long-term indices like SPI. It is critical for retrospective analysis, model verification, and understanding the climatological context of current weather events.

The Combined Drought Indicator (CDI) dataset developed at ACMAD is designed as an operational drought-monitoring product that synthesizes multiple biophysical signals into a single, coherent assessment of drought conditions across Africa. Rather than relying on a single indicator, the ACMAD CDI combines information from rainfall-based drought indices and satellite-derived vegetation condition metrics, applying rule-based logic to identify areas where these independent indicators consistently point to drought stress. This convergence approach reduces the risk of false alarms that can arise from short-term rainfall variability or vegetation anomalies unrelated to drought. The data exist in two forms one based on GPCC while another based on Era5 precipitation. The dataset is particularly useful in the African context, where ground observations are sparse and climatic gradients are strong across regions. By using harmonized, gridded datasets, the CDI provides a comparable drought signal across national boundaries, supporting regional coordination and continental-scale analysis. Its categorical outputs are intentionally simple and policy-ready, making them suitable for drought bulletins, early-warning communications, and high-level decision support. Importantly, the CDI is not intended to replace detailed drought diagnostics or impact assessments. Instead, it serves as a convergence and confirmation tool that highlights areas requiring closer analysis and expert interpretation. In this role, the CDI acts as a bridge between complex climate data and practical drought-risk management, enabling timely, consistent, and defensible drought monitoring at regional and continental scales.

For every pixel, the number of rainy days in a month is reported. This dataset is created by using daily rainfall data from WaPOR precipitation data. **Data publication:** 2020-06-01 **Supplemental Information:** No data value: -9999 Unit: days/month **Contact points:** Metadata Contact: [Solomon Seyoum](mailto:s.seyoum@un-ihe.org) **Resource constraints:** Creative Commons Attribution 4.0 International (CC-BY-4.0) **Online resources:** Download the data from Google Cloud Storage

Number of rainy days calculated in the Nile basin area. For every pixel, the number of rainy days in a month is reported. This dataset is created by using daily rainfall data from WaPOR precipitation data. **Data publication:** 2020-06-01 **Supplemental Information:** No data value: -9999 Unit: mm **Citation:** FAO 2018. WaPOR Database Methodology: Level 3. Remote Sensing for Water Productivity Technical Report: Methodology Series. Rome, FAO. 72 pages. Licence: CC-BY-4.0 **Contact points:** Resource Contact: [WaPOR](mailto:wapor@fao.org) Metadata Contact: [Solomon Seyoum](mailto:s.seyoum@un-ihe.org) **Resource constraints:** Creative Commons Attribution 4.0 International (CC-BY-4.0) **Online resources:** Download the data from Google Cloud Storage

The NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) GEOLST4KHR version 2 swath product provides per-pixel Land Surface Temperature (LST) with a spatial resolution of 4,000 meters (m). The product is produced daily in hourly increments using data acquired from Geostationary Operational Environmental Satellite (GOES) 8 and 10 through 17 satellites for the years 2000 through 2023. The GEOLST4KHR product provides LST values for both North and South America. The GEOLST4KHR data product utilizes the Modern-Era Retrospective analysis for Research and Applications Version 2 / Radiative Transfer for TIROS Operational Vertical Sounder (MERRA-2/RTTOV) Single-Channel Emissivity-Combined ASTER and MODIS Emissivity over Land (CAMEL) algorithm. The GEOLST4KHR product provides layers for cloud mask, latitude, longitude, land surface temperature, and land surface temperature error. A low-resolution browse is also available showing land surface temperature as an RGB (red, green, blue) image in JPEG format.