Evaluation of the FSU synthetic superensemble performance for seasonal forecasts over the Euro-Mediterranean region

This paper deals with seasonal climate forecasting using as many as 13 coupled ocean–atmosphere models. An analysis of the individual model, multimodel ensemble, and FSU synthetic superensemble (FSUSSE) climate forecasts was performed for monthly and seasonal forecasts of precipitation, sea surface temperature (SST) and surface air temperature over the Euro-Mediterranean region including the land areas of Europe, North Africa and the Near East, during the period 1989–2001. In the FSUSSE methodology, forecasts are obtained by a weighted combination of the individual coupled ocean–atmosphere model forecasts based on a training period. The set of 13 individual climate forecast models utilized in this research is comprised of the seven models in the European suite of DEMETER models, a suite of four Florida State University models, the Australian POAMA model and the NCAR CCM3 model. The FSUSSE forecasts of seasonal precipitation anomalies were found to have the lowest root mean square (RMS) errors in comparison to the models in the multimodel ensemble, and their ensemble mean. However, the anomaly correlation (AC) coefficient results for seasonal precipitation anomaly forecasts by the FSUSSE were less impressive. The equitable threat scores for the FSUSSE forecasts of seasonal precipitation were found to be better than the various models in the multimodel ensemble, but those scores for the forecasts of positive seasonal anomalies were found to be worse than most of the models in the multimodel ensemble. The FSUSSE seasonal forecasts for SST and surface air temperature for the season considered (winter) were found to be excellent for both AC coefficients and RMS errors in the forecast anomalies.