In many regions of Africa, droughts can have adverse impacts on crop production which may result in food scarcity, famine, and even widespread infectious disease in some cases. Particularly in areas where food security is already jeopardized due to poverty, lack of resources, or other extreme environmental occurrences, droughts can be extremely detrimental to agricultural management. Because of this, there is a need for a high-resolution drought dataset that can inform drought hazard probability and analyze drought-vulnerable regions.
In order to create this essential dataset, our partners and colleagues at the Santa Barbara Climate Hazards Center teamed up with researchers across the world including: the School of Geography and the Environment at the University of Oxford, the Max Planck Institute for Meteorology in Germany, the Hydro-Climatic Extremes Lab in Belgium, Instituto Pirenaico de Ecología, Consejo Superior de Investigaciones Científicas in Spain, and the U.S. Geological Survey Earth Resources Observation and Science Center. A high spatial resolution Standardized Precipitation-Evapotranspiration Index (SPEI) drought dataset is used by the researchers to support the resulting dataset which was computed based on the Climate Hazards group InfraRed Precipitation with Station data (CHIRPS) precipitation estimates and Global Land Evaporation Amsterdam Model (GLEAM) potential evaporation estimates.
The team of experts aimed to produce a set of drought data that would ultimately be used in Africa to reduce the negative effects of drought on water and food availability. The dataset is particularly useful for policy makers who are tasked with preventative planning and drought response because it provides an “assessment of drought vulnerability considering a multi- and cross-sectional perspective that includes crops, hydrological systems, rangeland and environmental systems.” By taking all of these variables into account and estimating regional drought likelihood, the dataset is a well-rounded source of information for decision-makers to reference in order to save time and money when droughts occur.
Read the full publication in the Earth System Science Data Journal to learn more about the dataset production method and view the dataset in the Centre for Environmental Data Analysis archives.