Articles | Volume 19, issue 6
Hydrol. Earth Syst. Sci., 19, 2577–2586, 2015

Special issue: Drought forecasting and warning

Hydrol. Earth Syst. Sci., 19, 2577–2586, 2015

Research article 02 Jun 2015

Research article | 02 Jun 2015

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

F. Wetterhall1, H. C. Winsemius2, E. Dutra1, M. Werner2,3, and E. Pappenberger1,4 F. Wetterhall et al.
  • 1European Centre for Medium Range Weather Forecasts, Reading, UK
  • 2Deltares, P.O. Box 177, 2600MH, Delft, the Netherlands
  • 3UNESCO-IHE, P.O. Box 3015, 2601DA, Delft, the Netherlands
  • 4School of Geographical Sciences, University of Bristol, Bristol, UK

Abstract. 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.

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Short summary
Dry spells can have a devastating impact on agricuture in areas where irrigation is not available. Forecasting these dry spells could enhance preparedness in sensitive regions and avoid economic loss due to harvest failure. In this study, ECMWF seasonal forecasts are applied in the Limpopo basin in southeastern Africa to forecast dry spells in the seasonal rains. The results indicate skill in the forecast which is further improved by post-processing of the precipitation forecasts.