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Two regression-based methods that recalibrate the ECHAM4. 5 general circulation model (GCM) output during austral summer have been developed for southern Africa, and their performance assessed over a 12-year retroactive period 1989/90–2000/01. A linear statistical model linking near-global sea-surface temperatures (SSTs) to regional rainfall has also been developed. The recalibration technique is model output statistics (MOS) using principal components regression (PCR) and canonical correlation analysis (CCA) to statistically link archived records of the GCM to regional rainfall over much of Africa, south of the equator. The predictability of anomalously dry and wet conditions over each rainfall region during December–February (DJF) using the linear statistical model and MOS models has been quantitatively evaluated. The MOS technique outperforms the raw-GCM ensembles and the linear statistical model. Neither the PCR-MOS nor the CCA-MOS models show clear superiority over the other, probably because the two methods are closely related. The need to recalibrate GCM predictions at regional scales to improve their skill at smaller spatial scales is further demonstrated in this paper. Copyright© 2006 Royal Meteorological Society.