Decadal prediction of the probability of extreme seasons

Abstract End-user products derived from decadal predictions are usually based on multi-year averages, however, users often demand information regarding shorter time-scales. We present an approach designed to assess the probability of extreme seasons within several years ahead. The approach is applied to a CMIP6 decadal prediction multi-model ensemble, to assess its ability to forecast extreme hot and extreme dry seasons. Over vast regions, the ensemble is skillful in predicting the observed probability of extreme hot seasons within the upcoming five years. For extreme dry summer seasons significant positive skill is limited to the Sahel region. Overall the results suggest that the proposed approach can be used to extract useful information on the probability of extreme seasons over a five year period from current decadal predictions. Hence, existing information based on multi-year averages can be complemented with this approach supporting users to make more informed decisions.