In an attempt to improve the forecast skill of the austral summer precipitation over South Africa, an
ensemble of 1-month-lead seasonal hindcasts generated by the Scale Interaction Experiment–Frontier Research
Center for Global Change (SINTEX-F2v) coupled global circulation model is downscaled using the
Weather Research and Forecasting (WRF) Model. The WRF Model with two-way interacting domains at
horizontal resolutions of 27 and 9 km is used in the study. Evaluation of the deterministic skill score using the
anomaly correlation coefficients shows that SINTEX-F2v has significant skill in precipitation forecasts confined
to western regions of South Africa. Dynamical downscaling of SINTEX-F2v forecasts using the WRF
Model is found to further improve the skill scores over South Africa. However, larger improvements in the
skill scores are achieved when the WRF Model is forced by a form of bias-corrected SINTEX-F2v forecasts.
The systematic biases in the original fields of the SITNEX-F2v forecasts are removed by superimposing the
SINTEX-F2v 6-hourly anomalies over the ERA-Interim 6-hourly climatological fields. The WRF Model
forced by the bias-corrected SINTEX-F2v shows significant skill in the forecast anomalies of precipitation
over most parts of South Africa. Interestingly, the WRF Model runs with the bias correction did not help to
improve the SINTEX-F2v forecast of 2-m air temperatures. Perhaps this is because of the large biases in the
precipitation forecast by the WRF Model driven by the bias-corrected SINTEX-F2v. These results are important
for potentially improving seasonal forecasts over South Africa.