The current state of regional climate and climate change modelling using GCMs is reviewed for southern Africa, and several approaches to regional climate change prediction which have been applied to southern Africa are assessed. Confidence in projected regional changes is based on the ability of a range of models to simulate present regional climate, and is greatest where intermodel consensus in terms of the nature of projected changes is highest. Both equilibrium and transient climate change projections for southern Africa are considered. Warming projected over southern Africa is within the range of globally averaged estimates. Uncertainties associated with the parameterization of convection ensure that projected changes in rainfall at GCM grid scales remain unreliable. However, empirical downscaling approaches produce rainfall changes consistent with synoptic-scale circulation. Both downscaling and grid-scale approaches indicate a 10-15% decrease in summer rainfall over the central interior which may have important implications for surface hydrology. Climate change may be manifested as a change in variability, and not in mean climate. Over southern Africa, increases in the variability and intensity of daily rainfall events are indicated.

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A general circulation model simulation is used to investigate possible changes in rainfall over southern Africa resulting from a doubling of atmospheric carbon dioxide. Simulated increases in rainfall intensity are found to be a spatially coherent and an apparently less regionally dependent signal of climatic change than changes in annual means or number of rain-days. Accordingly, increases in both the frequency and intensity of extreme daily rainfall events are simulated throughout most of the subcontinent. Simulated increases in the intensity of the lowest frequency floods are shown to be particularly severe, suggesting that greenhouse-related climatic change may be most detectable through an increase in extreme flood events rather than changes in long-term means. Similar results are evident when changes in the frequency and intensity of prolonged rainfall events, measured over a period of five consecutive days, are analysed. All results are qualitatively similar to those for the Australian region, except that the model's sensitivity to sharp changes in topography over southern Africa is highlighted.

The southern African region is susceptible to climatic extremes and particularly to extended dry periods. Possible changes in the probability of dry years under doubled‐CO2 conditions are examined using output from the CSIRO nine‐level general circulation model. Changes in annual mean rainfall are not expected to be significant. However, the model simulates an increase in the probability of dry years in the tropics, to the south‐west of the subcontinent, as well as over the western and eastern parts of South Africa and southern Mozambique, where large percentage increases in the most intense dry spells are indicated. A decrease in the frequency of dry years is simulated over much of the interior of the subcontinent south of 10°S. In regions where the frequency of dry years decreases, the most severe events occur less often. The CSIRO nine‐level model indicates a shift in the frequency distribution of daily rainfall events under doubled‐CO2 conditions. A small change in the frequency distribution of daily rainfall events may have further implications for the frequency of mid‐summer droughts during the peak summer rainfall period of December–February. Increases in the frequency of mid‐summer droughts are simulated over the eastern part of the subcontinent south of 20°S.

Abstract. The Commonwealth Scientific and Industrial Research Organisation (CSIRO)Division of Atmospheric Research limited area model (DARLAM) is used to simulate midsummer (January) climate over southern Africa. Using a one-way nesting procedure, lateral boundary and initial conditions are supplied by the CSIRO nine-level Mark 2 general circulation model (GCM), CSIRO9. In general, the DARLAM results are improved in comparison with those from CSIRO9, although certain deficiencies in the GCM climatology over southern Africa are also present in the nested model results. DARLAM captures the spatial pattern of observed rainfall and interannual rainfall variability over the region as a whole more accurately than CSIRO9. Over most parts of the subcontinent, interannual rainfall variability simulated by DARLAM is not significantly different from observations. Over the steep escarpment region of south-east South Africa, DARLAM simulates more rainfall than CSIRO9 and significantly more rainfall than observed. Over Madagascar, DARLAM simulates more rainfall than CSIRO9, but less than observed, and interannual variability is also significantly less than the observed variability.