AbstractPrevious observational work suggests that when sea‐surface temperature (SST) is warm (cool) in the southwest Indian Ocean and cool (warm) in the southeast Indian Ocean, increased (decreased) summer rains may occur over large areas of southeastern Africa. In this study, an atmospheric general circulation model is used to investigate the sensitivity of the regional circulation and rainfall over southern Africa to these dipole SST anomalies in the subtropical south Indian Ocean. When the model is forced with positive SST anomalies in the west and negative SST anomalies in the east, increased rainfall occurs over southeastern Africa as a result of the enhanced convergence of moister than average air over the region. Enhanced evaporation occurs over the warm pole in the southwest Indian Ocean and this moist air is advected towards southeastern Africa as a result of the low‐pressure anomaly generated over this pole, which strengthens the onshore flow. Increased and more intense extra‐tropical cyclones occur to the southeast of South Africa, favourable for tropical–temperate trough formation. When the SST poles are reversed in sign, decreased precipitation occurs over southeastern Africa as a result of increased low‐level divergence of low‐level flow and this flow being drier than average. Weaker and fewer extra‐tropical cyclones occur southeast of South Africa in this case.The model results are sensitive to the proximity of the southwest Indian Ocean pole to southeastern Africa. There is also sensitivity in the model low‐level wind changes and precipitation anomaly over low‐latitude southern Africa (but not over South Africa to any significant extent) to the presence or absence of the SST pole over the southeast Indian Ocean. Although the model resolution does not capture the details of the local SST and topographic gradients as well as one would like, the changes in model circulation and precipitation in the experiments with different SST anomalies are consistent with previous observational and theoretical work, hence increasing confidence in the robustness of the results. Copyright © 2002 Royal Meteorological Society
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