The predictor SST data for the current forecast are then projected onto the preferred relationships derived from the past years, and a forecast for the 1996 target season is developed. Here the lead time is 1 month, as the latest predictor data used are those of August 1996, preceding the beginning of the target period by 1 month. A rainfall data set consisting of individual stations has also been tested, with results shown in Thiao et al. The gridded data used here tend to show slightly higher skill in parts of Africa having sparser data, such as eastern Africa. This may be because the gridded data are developed using stations that have major gaps during some periods, while the station data set completely excludes such stations.
Highest skills tend to occur in southern Sudan.
A cross-validation design is used in obtaining these skill estimates, where each year is held out of the developmental data set in turn, and then used as the forecast target. The forecast provides the estimated deviation from these long-term probabilities for the period being forecast. For example, if a 0.07 probability anomaly for below normal rainfall is forecast, then the probabilities of the below, near and above normal categories to occur would be 0.403, 0.333 and 0.263 instead of the climatological probabilities of 0.333, 0.333, 0.333. In some cases the probability of the near normal category may be elevated at the expense of the two outer categories. Expressing the forecasts in terms of probability anomalies enables uncertainty to be incorporated into the forecasts.