A pan-African high-resolution drought index dataset
<p>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 on Africa, a high-resolution drought dataset is essential to establish robust drought hazard probabilities...
| Main Authors: | , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2020-03-01
|
| Series: | Earth System Science Data |
| Online Access: | https://www.earth-syst-sci-data.net/12/753/2020/essd-12-753-2020.pdf |
| _version_ | 1811218791362723840 |
|---|---|
| author | J. Peng J. Peng S. Dadson F. Hirpa E. Dyer T. Lees D. G. Miralles S. M. Vicente-Serrano C. Funk C. Funk |
| author_facet | J. Peng J. Peng S. Dadson F. Hirpa E. Dyer T. Lees D. G. Miralles S. M. Vicente-Serrano C. Funk C. Funk |
| author_sort | J. Peng |
| collection | DOAJ |
| description | <p>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 on Africa, a high-resolution
drought dataset is essential to establish robust drought hazard
probabilities and to assess drought vulnerability considering a multi- and
cross-sectional perspective that includes crops, hydrological systems,
rangeland and environmental systems. Such assessments are essential for
policymakers, 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 of 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,
Normalized Difference Vegetation Index (NDVI) calculated from the Global
Inventory Monitoring and Modeling System (GIMMS) project and
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 an average correlation coefficient (<span class="inline-formula"><i>R</i></span>) of 0.54
and 0.77, respectively – further implies that SPEI-HR can provide valuable
information for the study of 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) via the following link: <a href="https://doi.org/10.5285/bbdfd09a04304158b366777eba0d2aeb">https://doi.org/10.5285/bbdfd09a04304158b366777eba0d2aeb</a>
(Peng et al., 2019a).</p> |
| first_indexed | 2024-04-12T07:15:19Z |
| format | Article |
| id | doaj.art-c4a7f12f357149fe9b202c3586d72cc6 |
| institution | Directory Open Access Journal |
| issn | 1866-3508 1866-3516 |
| language | English |
| last_indexed | 2024-04-12T07:15:19Z |
| publishDate | 2020-03-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Earth System Science Data |
| spelling | doaj.art-c4a7f12f357149fe9b202c3586d72cc62022-12-22T03:42:30ZengCopernicus PublicationsEarth System Science Data1866-35081866-35162020-03-011275376910.5194/essd-12-753-2020A pan-African high-resolution drought index datasetJ. Peng0J. Peng1S. Dadson2F. Hirpa3E. Dyer4T. Lees5D. G. Miralles6S. M. Vicente-Serrano7C. Funk8C. Funk9School of Geography and the Environment, University of Oxford, OX1 3QY Oxford, UKMax Planck Institute for Meteorology, Hamburg, GermanySchool of Geography and the Environment, University of Oxford, OX1 3QY Oxford, UKSchool of Geography and the Environment, University of Oxford, OX1 3QY Oxford, UKSchool of Geography and the Environment, University of Oxford, OX1 3QY Oxford, UKSchool of Geography and the Environment, University of Oxford, OX1 3QY Oxford, UKHydro-Climatic Extremes Lab (H-CEL), Ghent University, Ghent, BelgiumInstituto Pirenaico de Ecología, Consejo Superior de Investigaciones Científicas (IPE-CSIC) Zaragoza, SpainU.S. Geological Survey, Earth Resources Observation and Science Center, Sioux Falls, South Dakota, USASanta Barbara Climate Hazards Center, University of California, Santa Barbara, USA<p>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 on Africa, a high-resolution drought dataset is essential to establish robust drought hazard probabilities and to assess drought vulnerability considering a multi- and cross-sectional perspective that includes crops, hydrological systems, rangeland and environmental systems. Such assessments are essential for policymakers, 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 of 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, Normalized Difference Vegetation Index (NDVI) calculated from the Global Inventory Monitoring and Modeling System (GIMMS) project and 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 an average correlation coefficient (<span class="inline-formula"><i>R</i></span>) of 0.54 and 0.77, respectively – further implies that SPEI-HR can provide valuable information for the study of 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) via the following link: <a href="https://doi.org/10.5285/bbdfd09a04304158b366777eba0d2aeb">https://doi.org/10.5285/bbdfd09a04304158b366777eba0d2aeb</a> (Peng et al., 2019a).</p>https://www.earth-syst-sci-data.net/12/753/2020/essd-12-753-2020.pdf |
| spellingShingle | J. Peng J. Peng S. Dadson F. Hirpa E. Dyer T. Lees D. G. Miralles S. M. Vicente-Serrano C. Funk C. Funk A pan-African high-resolution drought index dataset Earth System Science Data |
| title | A pan-African high-resolution drought index dataset |
| title_full | A pan-African high-resolution drought index dataset |
| title_fullStr | A pan-African high-resolution drought index dataset |
| title_full_unstemmed | A pan-African high-resolution drought index dataset |
| title_short | A pan-African high-resolution drought index dataset |
| title_sort | pan african high resolution drought index dataset |
| url | https://www.earth-syst-sci-data.net/12/753/2020/essd-12-753-2020.pdf |
| work_keys_str_mv | AT jpeng apanafricanhighresolutiondroughtindexdataset AT jpeng apanafricanhighresolutiondroughtindexdataset AT sdadson apanafricanhighresolutiondroughtindexdataset AT fhirpa apanafricanhighresolutiondroughtindexdataset AT edyer apanafricanhighresolutiondroughtindexdataset AT tlees apanafricanhighresolutiondroughtindexdataset AT dgmiralles apanafricanhighresolutiondroughtindexdataset AT smvicenteserrano apanafricanhighresolutiondroughtindexdataset AT cfunk apanafricanhighresolutiondroughtindexdataset AT cfunk apanafricanhighresolutiondroughtindexdataset AT jpeng panafricanhighresolutiondroughtindexdataset AT jpeng panafricanhighresolutiondroughtindexdataset AT sdadson panafricanhighresolutiondroughtindexdataset AT fhirpa panafricanhighresolutiondroughtindexdataset AT edyer panafricanhighresolutiondroughtindexdataset AT tlees panafricanhighresolutiondroughtindexdataset AT dgmiralles panafricanhighresolutiondroughtindexdataset AT smvicenteserrano panafricanhighresolutiondroughtindexdataset AT cfunk panafricanhighresolutiondroughtindexdataset AT cfunk panafricanhighresolutiondroughtindexdataset |