From ENSO prediction to regional climate services: The scientific evolution of seasonal forecasting in southern Africa within a US–South Africa collaborative framework

Abstract

Seasonal climate forecasting in southern Africa has evolved over three decades from statistical rainfall outlooks to an integrated system combining coupled ocean–atmosphere models, statistical recalibration, probabilistic verification, and sector-specific climate services. This paper documents that development within a sustained collaborative framework linking South African institutions with U.S. modelling centres, highlighting contributions from ENSO prediction, the North American Multi-Model Ensemble, and the IRI Climate Predictability Tool. We demonstrate continuity of archived real-time Niño3.4 sea-surface temperature anomaly forecasts since 2015, their extension to full-field global SST anomaly prediction, and probabilistic verification of seasonal rainfall forecasts across the Southern African Development Community. Archived real-time rainfall forecasts demonstrate measurable probabilistic skill relative to climatology, with useful discrimination of extreme categories. Applications at farm scale and within a provincial malaria early warning system illustrate how calibrated probabilistic guidance is translated into agricultural and public-health decision contexts. The collaboration has been reciprocal: U.S. coupled model systems underpin regional rainfall forecasting, while South African ENSO forecasts contribute to international multi-model assessment efforts. Southern Africa’s seasonally varying and spatially heterogeneous predictability provides a structured environment for evaluating global seasonal prediction systems. Sustained bilateral engagement has contributed to advances in both regional climate services and the broader science of seasonal forecasting.