Seasonal predictions of agro-meteorological drought indicators for the Limpopo basin

The rainfall in southern Africa has a large inter-annual variability, which can cause rain-fed agriculture to fail. The staple crop maize is especially sensitive to dry spells during the early growing season. An early prediction of the probability of dry spells and below normal precipitation can pot...

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Main Authors: F. Wetterhall, H. C. Winsemius, E. Dutra, M. Werner, E. Pappenberger
Format: Article
Language:English
Published: Copernicus Publications 2015-06-01
Series:Hydrology and Earth System Sciences
Online Access:http://www.hydrol-earth-syst-sci.net/19/2577/2015/hess-19-2577-2015.pdf
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spelling doaj-34e29523e58843a7a546ab37852a603c2020-11-24T21:58:53ZengCopernicus PublicationsHydrology and Earth System Sciences1027-56061607-79382015-06-011962577258610.5194/hess-19-2577-2015Seasonal predictions of agro-meteorological drought indicators for the Limpopo basinF. Wetterhall0H. C. Winsemius1E. Dutra2M. Werner3E. Pappenberger4European Centre for Medium Range Weather Forecasts, Reading, UKDeltares, P.O. Box 177, 2600MH, Delft, the NetherlandsEuropean Centre for Medium Range Weather Forecasts, Reading, UKDeltares, P.O. Box 177, 2600MH, Delft, the NetherlandsEuropean Centre for Medium Range Weather Forecasts, Reading, UKThe rainfall in southern Africa has a large inter-annual variability, which can cause rain-fed agriculture to fail. The staple crop maize is especially sensitive to dry spells during the early growing season. An early prediction of the probability of dry spells and below normal precipitation can potentially mitigate damages through water management. This paper investigates how well ECMWF's seasonal forecasts predict dry spells over the Limpopo basin during the rainy season December–February (DJF) with lead times from 0 to 4 months. The seasonal forecasts were evaluated against ERA-Interim reanalysis data, which in turn were corrected with GPCP (EGPCP) to match monthly precipitation totals. The seasonal forecasts were also bias-corrected with the EGPCP using quantile mapping as well as post-processed using a precipitation threshold to define a dry day. The results indicate that the forecasts show skill in predicting dry spells in comparison with a climatological ensemble based on previous years. Quantile mapping in combination with a precipitation threshold improved the skill of the forecast. The skill in prediction of dry spells was largest over the most drought-sensitive region. Seasonal forecasts have the potential to be used in a probabilistic forecast system for drought-sensitive crops, though these should be used with caution given the large uncertainties.http://www.hydrol-earth-syst-sci.net/19/2577/2015/hess-19-2577-2015.pdf
collection DOAJ
language English
format Article
sources DOAJ
author F. Wetterhall
H. C. Winsemius
E. Dutra
M. Werner
E. Pappenberger
spellingShingle F. Wetterhall
H. C. Winsemius
E. Dutra
M. Werner
E. Pappenberger
Seasonal predictions of agro-meteorological drought indicators for the Limpopo basin
Hydrology and Earth System Sciences
author_facet F. Wetterhall
H. C. Winsemius
E. Dutra
M. Werner
E. Pappenberger
author_sort F. Wetterhall
title Seasonal predictions of agro-meteorological drought indicators for the Limpopo basin
title_short Seasonal predictions of agro-meteorological drought indicators for the Limpopo basin
title_full Seasonal predictions of agro-meteorological drought indicators for the Limpopo basin
title_fullStr Seasonal predictions of agro-meteorological drought indicators for the Limpopo basin
title_full_unstemmed Seasonal predictions of agro-meteorological drought indicators for the Limpopo basin
title_sort seasonal predictions of agro-meteorological drought indicators for the limpopo basin
publisher Copernicus Publications
series Hydrology and Earth System Sciences
issn 1027-5606
1607-7938
publishDate 2015-06-01
description The rainfall in southern Africa has a large inter-annual variability, which can cause rain-fed agriculture to fail. The staple crop maize is especially sensitive to dry spells during the early growing season. An early prediction of the probability of dry spells and below normal precipitation can potentially mitigate damages through water management. This paper investigates how well ECMWF's seasonal forecasts predict dry spells over the Limpopo basin during the rainy season December–February (DJF) with lead times from 0 to 4 months. The seasonal forecasts were evaluated against ERA-Interim reanalysis data, which in turn were corrected with GPCP (EGPCP) to match monthly precipitation totals. The seasonal forecasts were also bias-corrected with the EGPCP using quantile mapping as well as post-processed using a precipitation threshold to define a dry day. The results indicate that the forecasts show skill in predicting dry spells in comparison with a climatological ensemble based on previous years. Quantile mapping in combination with a precipitation threshold improved the skill of the forecast. The skill in prediction of dry spells was largest over the most drought-sensitive region. Seasonal forecasts have the potential to be used in a probabilistic forecast system for drought-sensitive crops, though these should be used with caution given the large uncertainties.
url http://www.hydrol-earth-syst-sci.net/19/2577/2015/hess-19-2577-2015.pdf
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