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Discussion papers
https://doi.org/10.5194/essd-2019-138
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-2019-138
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: data description paper 07 Oct 2019

Submitted as: data description paper | 07 Oct 2019

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Earth System Science Data (ESSD).

A pan-African high-resolution drought index dataset

Jian Peng1,2, Simon Dadson1, Feyera Hirpa1, Ellen Dyer1, Thomas Lees1, Diego G. Miralles3, Sergio M. Vicente-Serrano4, and Chris Funk5,6 Jian Peng et al.
  • 1School of Geography and the Environment, University of Oxford, OX1 3QY Oxford, UK
  • 2Max Planck Institute for Meteorology, Hamburg, Germany
  • 3Laboratory of Hydrology and Water Management, Ghent University, Ghent, Belgium
  • 4Instituto Pirenaico de Ecología, Consejo Superior de Investigaciones Científicas (IPE-CSIC) Zaragoza, Spain
  • 5U.S. Geological Survey, Earth Resources Observation and Science Center, Sioux Falls, South Dakota, USA
  • 6Santa Barbara Climate Hazards Center, University of California, USA

Abstract. Droughts in Africa cause severe problems such as crop failure, food shortages, famine, epidemics and even mass migration. To minimize the effects of drought on water and food security over Africa, a high-resolution drought dataset is essential to establish robust drought hazard probabilities and to assess drought vulnerability considering a multi- and cross-sectorial perspective that includes crops, hydrological systems, rangeland, and environmental systems. Such assessments are essential for policy makers, their advisors, and other stakeholders to respond to the pressing humanitarian issues caused by these environmental hazards. In this study, a high spatial resolution Standardized Precipitation-Evapotranspiration Index (SPEI) drought dataset is presented to support these assessments. We compute historical SPEI data based on Climate 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 spatial resolution over the whole Africa. To facilitate the diagnosis of droughts of different durations, accumulation periods from 1 to 48 months are provided. The quality of the resulting dataset was compared with coarse-resolution SPEI based on Climatic Research Unit (CRU) Time-Series (TS) datasets, and Normalized Difference Vegetation Index (NDVI) calculated from the Global Inventory Monitoring and Modeling System (GIMMS) project, as well as with root zone soil moisture modelled by GLEAM. Agreement found between coarse resolution SPEI from CRU TS (SPEI-CRU) and the developed SPEI-HR provides confidence in the estimation of temporal and spatial variability of droughts in Africa with SPEI-HR. In addition, agreement of SPEI-HR versus NDVI and root zone soil moisture – with average correlation coefficient (R) of 0.54 and 0.77, respectively – further implies that SPEI-HR can provide valuable information to study drought-related processes and societal impacts at sub-basin and district scales in Africa. The dataset is archived in Centre for Environmental Data Analysis (CEDA) with link: https://doi.org/10.5285/bbdfd09a04304158b366777eba0d2aeb (Peng et al., 2019a)

Jian Peng et al.
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Jian Peng et al.
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High resolution Standardized Precipitation Evapotranspiration Index (SPEI) dataset for Africa J. Peng, S. Dadson, F. Hirpa, E. Dyer, T. Lees, D. G. Miralles, S. M. V.-S. Vicente-Serrano, and C. Funk https://doi.org/10.5285/bbdfd09a04304158b366777eba0d2aeb

Jian Peng et al.
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Short summary
Africa has been severely influenced by intense drought events, which has led to crop failure, food shortages, famine, epidemics and even mass migration. The current study developed a high spatial resolution drought dataset entirely from satellite-based products. The dataset has been comprehensively inter-compared with other drought indicators and may contribute to an improved characterization of drought risk and vulnerability, and minimize its impact on water and food security over Africa.
Africa has been severely influenced by intense drought events, which has led to crop failure,...
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