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

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.