Summer drought predictability in the Euro-Mediterranean region in seasonal forecasts

In the Euro-Mediterranean region, summer droughts present significant challenges for various socio-economic sectors, raising the need for reliable seasonal drought forecasts to support proactive water resource management. This study evaluates the skill of the latest seasonal forecast systems from the Copernicus Climate Change Service in predicting summer droughts, using the Standardized Precipitation Evapotranspiration Index (SPEI) to characterize drought events. Using a systematic multi-metric evaluation framework that includes both deterministic and probabilistic scores, we benchmark individual systems and their multi-model ensemble (MME) to identify patterns of predictive skill across regions and lead times. The findings reveal that when SPEI forecasts are initiated at the onset of the summer season, all models exhibit on average positive correlations with observed dry conditions, reflecting also good quality in terms of accuracy, reliability, and discrimination skills, though with local variability. The added value of dynamical models compared to climatology-based heuristic prediction methods declines significantly for forecasts initialized one month earlier. At all lead times performance is better for all models in Southern Mediterranean areas, indicating higher predictability of SPEI in that region compared to Northern Europe. By highlighting the grid points where SPEI seasonal forecasts hold significant predictive value, this study provides actionable insights for leveraging these products in decision-making processes. When a non-locally tailored analysis is needed, the MME offers the most robust drought forecasting solution, always demonstrating more widespread significant skill with respect to single models up to a 1-month lead time, covering much of the Mediterranean region. Beyond this horizon, significant skill becomes limited, resulting in forecasts that are neutral compared to the heuristic approaches. Notably, individual models demonstrate localized lead time-dependent strengths that may make them preferable to the MME in specific cases where tailored predictions are required.