References

HESS

Hydrology and Earth System Sciences

HESS

Hydrol. Earth Syst. Sci.

1607-7938

Copernicus Publications

Göttingen, Germany

10.5194/hess-19-2577-2015

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

Wetterhall

https://orcid.org/0000-0001-5331-9064

¹ Winsemius

H. C.

https://orcid.org/0000-0001-5471-172X

² Dutra

https://orcid.org/0000-0002-0643-2643

¹ Werner

² ³ Pappenberger

https://orcid.org/0000-0003-1766-2898

¹ ⁴

European Centre for Medium Range Weather Forecasts, Reading, UK

Deltares, P.O. Box 177, 2600MH, Delft, the Netherlands

UNESCO-IHE, P.O. Box 3015, 2601DA, Delft, the Netherlands

School of Geographical Sciences, University of Bristol, Bristol, UK

02 06 2015

19 6 2577 2586

2015

This work is licensed under the Creative Commons Attribution 3.0 Unported License. To view a copy of this licence, visit https://creativecommons.org/licenses/by/3.0/

This article is available from https://hess.copernicus.org/articles/19/2577/2015/hess-19-2577-2015.html

The full text article is available as a PDF file from https://hess.copernicus.org/articles/19/2577/2015/hess-19-2577-2015.pdf

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.

European Commission

DEWFORA - Improved Drought Early Warning and FORecasting to strengthen preparedness and adaptation to droughts in Africa (265454)

GLOWASIS - A collaborative project aimed at pre-validation of a GMES Global Water Scarcity Information Service (262255)

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