Our paper, “Sub selection of seasonal ensemble precipitation predictions for East Africa” by Claudio Heinrich-Mertsching, has been published. The research brings a new dimension towards improving seasonal rainfall forecasts over the Greater Horn of Africa by employing sub-selecting ensemble members from seasonal prediction systems.
The results from the study show that informed sub-selection leads to systematically higher skill than random sub-selection. More specifically, informed sub-selection nearly consistently outperforms random sub-selection for small subsample sizes.
Similarly, sub-selecting based on well-known teleconnections benefits those seasons in which such pathways are active, such as OND and JJAS, and k-means sub-selection outperforms random selection for small ensemble sizes throughout all seasons.
This new research is a significant milestone expected to improve seasonal forecasting in the region, including the MAM season, which is continuously becoming challenging to forecast using the currently available techniques.
Read the full paper in the Quarterly Journal of the Royal Meteorological Society