Multi-model forecast skill for mid-summer rainfall over southern Africa


  • Willem A. Landman,

    Corresponding author
    1. Council for Scientific and Industrial Research, Natural Resources and the Environment, Pretoria, South Africa
    2. Department of Geography, Geoinformatics and Meteorology, University of Pretoria, South Africa
    • Council for Scientific and Industrial Research, Pretoria, 0001, South Africa.
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  • Asmerom Beraki

    1. South African Weather Service, Pretoria, South Africa
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Southern African December-January-February (DJF) probabilistic rainfall forecast skill is assessed over a 22-year retroactive test period (1980/1981 to 2001/2002) by considering multi-model ensembles consisting of downscaled forecasts from three of the DEMETER models, the ECMWF, Météo-France and UKMO coupled ocean-atmosphere general circulation models. These models are initialized in such a way that DJF forecasts are produced at an approximate 1-month lead time, i.e. forecasts made in early November. Multi-model forecasts are obtained by: i) downscaling each model's 850 hPa geopotential height field forecast using canonical correlation analysis (CCA) and then simply averaging the rainfall forecasts; and ii) by combining the three models' 850 hPa forecasts, and then downscaling them using CCA. Downscaling is performed onto the 0.5° × 0.5° resolution of the CRU rainfall data set south of 10° south over Africa. Forecast verification is performed using the relative operating characteristic (ROC) and the reliability diagram. The performance of the two multi-model combinations approaches are compared with the single-model downscaled forecasts and also with each other. It is shown that the multi-model forecasts outperform the single model forecasts, that the two multi-model schemes produce about equally skilful forecasts, and that the forecasts perform better during El Niño and La Niña seasons than during neutral years. Copyright © 2010 Royal Meteorological Society