Assessing the Skill of Precipitation and Temperature Seasonal Forecasts in Spain: Windows of Opportunity Related to ENSO Events

Abstract

The skill of state-of-the-art operational seasonal forecast models in extratropical latitudes is assessed using a multimodel ensemble from the Development of a European Multimodel Ensemble System for Seasonal-to-Interannual Prediction (DEMETER) project. In particular, probabilistic forecasts of surface precipitation and maximum temperature in Spain are analyzed using a high-resolution observation gridded dataset (Spain02). To this aim, a simple statistical test based on the observed and predicted tercile anomalies is used. First, the whole period 1960?2000 is considered and it is shown that the only significant skill is found for dry events in autumn. Then, the influence of ENSO events as a potential source of conditional predictability is studied and the validation to strong La Niña or El Niño periods is restricted. Skillful seasonal predictions are found in partial agreement with the observed teleconnections derived from the historical records. On the one hand, predictability is found in spring related to El Niño events for dry events over the south and the Mediterranean coast and for hot events in the southeast areas. In contrast, La Niña drives predictability in winter for dry events over the western part and for hot events in summer over the south and the Mediterranean coast. This study considers both the direct model outputs and the postprocessed predictions obtained using a statistical downscaling method based on analogs. In general, the use of the downscaling method outperforms the direct output for precipitation, whereas in the case of the temperature no improvement is obtained.