This paper suggests a probabilistic framework for predicting when the rainy season will start over the Greater Horn of Africa. It uses bias-corrected, long-range, multi-model ensemble precipitation forecasts to do this.

When you look closely at how the different forecast systems affect the overall multi-model skill, you can see that the larger ensemble size is a big reason for the improvement over the best-performing single model.

An alternative way of increasing ensemble size by blending a single-model ensemble with climatology is explored and demonstrated to yield better probabilistic forecasts than the multi-model ensemble. Both the reliability and skill of the probabilistic forecasts are better for OND onset than for MAM and JJAS onset, where forecasts are found to be late-biased and have only minimal skill relative to climatology.

The insights gained in this study will help enhance operational subseasonal-to-seasonal forecasting in the GHA region.