Seasonal predictability of tropical rainfall: probabilistic formulation and validation

Two idealized seasonal forecast experiments are performed by prescribing mo nthly observed SSTs to atmospheric GCMs. The first one uses 3 different mod els, each with 9 individual forecasts (PROVOST experiment). The second one uses an improved version of one of the 3 models and larger ensembles consis ting of 120 members. Both experiments show that forecast scores are maximum in the tropics during winter and during summer. The relatively high correl ations in the tropics (0.4 to 0.7) imply. however. that the forecasts expla in less than 50% of the variance of the observations. The raw probabilistic forecasts obtained by the empirical probability distribution of the foreca st members exhibit very little skill. when evaluated by a euclidian distanc e versus the climatological forecast. The lack of reliability can be partly corrected by a simple statistical adaptation. Moreover. when the skill is evaluated by an economical value in a cost loss approach. the model forecas ts are more efficient than the climatological forecast. A more realistic ev aluation of the probabilistic skill is obtained by replacing observed by st atistically predicted SSTs. A simple but efficient method is used. which le ts each member of the ensemble develop its own SST anomalies. Although lowe r. skill is significant in the tropics.