摘要：Droughts in Africa cause severe problems, such as crop failure, foodshortages, famine, epidemics and even mass migration. To minimize theeffects of drought on water and food security on Africa, a high-resolutiondrought dataset is essential to establish robust drought hazardprobabilities and to assess drought vulnerability considering a multi- andcross-sectional perspective that includes crops, hydrological systems,rangeland and environmental systems. Such assessments are essential forpolicymakers, their advisors and other stakeholders to respond to thepressing humanitarian issues caused by these environmental hazards. In thisstudy, a high spatial resolution StandardizedPrecipitation-Evapotranspiration Index (SPEI) drought dataset is presentedto support these assessments. We compute historical SPEI data based onClimate Hazards group InfraRed Precipitation with Station data (CHIRPS)precipitation estimates and Global Land Evaporation Amsterdam Model (GLEAM)potential evaporation estimates. The high-resolution SPEI dataset (SPEI-HR)presented here spans from 1981 to 2016 (36 years) with 5 km spatialresolution over the whole of Africa. To facilitate the diagnosis of droughts ofdifferent durations, accumulation periods from 1 to 48 months are provided.The quality of the resulting dataset was compared with coarse-resolutionSPEI based on Climatic Research Unit (CRU) Time Series (TS) datasets,Normalized Difference Vegetation Index (NDVI) calculated from the GlobalInventory Monitoring and Modeling System (GIMMS) project androot zone soil moisture modelled by GLEAM. Agreement found between coarse-resolution SPEI from CRU TS (SPEI-CRU) and the developed SPEI-HR providesconfidence in the estimation of temporal and spatial variability of droughtsin Africa with SPEI-HR. In addition, agreement of SPEI-HR versus NDVI androot zone soil moisture – with an average correlation coefficient (R) of 0.54and 0.77, respectively – further implies that SPEI-HR can provide valuableinformation for the study of drought-related processes and societal impacts atsub-basin and district scales in Africa. The dataset is archived in Centrefor Environmental Data Analysis (CEDA) via the following link: https://doi.org/10.5285/bbdfd09a04304158b366777eba0d2aeb(Peng et al., 2019a).
