资源环境科技发展态势分析平台

The El Nino Southern Oscillation (ENSO) is a major driver of southern Africa drought, but the nonlinearity of ENSO variation inhibits accurate drought prediction. While studies have identified multiple sea surface temperature (SST) patterns associated with ENSO, most drought predictions over southern Africa are still based on only two patterns. This study examines the relationship between southern Africa droughts and eight ENSO SST patterns using SPEEDY. The capability of SPEEDY in reproducing southern Africa climate was evaluated by comparing historical simulations (1979-2008) with observation. To understand the influence of ENSO SST patterns on southern Africa drought, multi-ensemble simulations were forced with SSTs of each pattern, and the impacts on the Standardized Precipitation Evapotranspiration Index (SPEI) and the associated atmospheric dynamics were analysed. The results show that SPEEDY generally captures the temporal and spatial distribution of climate variables over southern Africa well, although with a warm and wet bias. However, the results are comparable with those from more complex atmospheric models. In agreement with previous studies, the results show that El Nino (La Nina) conditions weaken (strengthen) the Walker circulation, causing drier (wetter) conditions over parts of southern Africa. However, the results show that differences in the El Nino conditions alter the moisture flux circulation over southern Africa, thereby influencing the spatial pattern and intensity of drought over the region. The same is true of the La Nina conditions. Hence, this study shows that accounting for the differences in El Nino (or La Nina) conditions may improve drought predictions in southern Africa.