Abstract:
Aspects of forecast skill in predicting seasonal characteristics using global climate models (GCMs) are assessed over South Africa. The GCMs output is configured to predict number of rainfall days at South African Weather Service stations exceeding pre-defined threshold values for the austral summer seasons and to predict the rainfall totals of the onset months of the rainy seasons for eight homogeneous rainfall regions of South Africa. Using canonical correlation analysis (CCA) as statistical downscaling technique through model output statistics, the forecast skill levels of coupled ocean–atmosphere and uncoupled atmospheric models are determined through retro-actively generated hindcasts. Both downscaled models have skill in predicting low and high number of rainfall days exceeding pre-defined thresholds for the austral summer seasons as well as rainfall totals of onset months. In addition to the forecast verification results, CCA pattern is performed to determine the dominating atmospheric circulation systems predicted to be controlling rainfall variations for the seasons and months of interest. CCA patterns for both the GCMs indicate that usually when there are anomalously negative (positive) predicted 850 hPa geopotential heights over South Africa, there are anomalously wet (dry) conditions over most parts of South Africa. The work has paved the way for the operational production of seasonal rainfall characteristics over South Africa in real time.
