Climate driven generative time-varying model for improved decadal storm power predictions in the Mediterranean

Decadal climate predictions are crucial for communities engaged in scenario planning under Sustainable Development Goals. However, uncertainties in future precipitation extremes hinder climate mitigation and adaptation efforts. Here we present a hybrid statistical climate-driven time-varying model to predict the Areal MEan Storm Erosivity Index, a key indicator of hydrological events, for the Mediterranean region. By integrating historical data (1884-2022) with large-scale (El Ni & ntilde;o-Southern Oscillation) and small-scale (precipitation variability) climate forcings, our model captures past storm behavior and projects future dynamics. The Hurst exponent (0.63) suggests a long-term positive memory in Areal MEan Storm Erosivity Index, enhancing prediction accuracy. Projections show an Index increase until 2040, then a decline until 2050, and a resurgence. While consistent with other regional models at the interdecadal scale, finer variations are less pronounced at the interannual scale. This approach offers valuable insights into hydroclimate variability, aiding climate resilience planning in the Mediterranean and beyond.