Evaluation of a model ensemble appraoch to explore climate variability in Emilia-Romagna in the present and future scenarios

Understanding climate variability at a regional scale is crucial for evaluating climate change impacts and improving future projections. This study examines the application of a regional climate model (RCM) ensemble approach in reproducing past climate conditions and projecting future air temperature and precipitation trends in Emilia-Romagna, Italy. The analysis is based on monthly mean values of air temperature and precipitation derived from observational datasets (1961–2023) from ISPRA, available on a 1 km resolution grid, and EURO-CORDEX RCM simulations for the historical period (1961–2005). The simulation period of the ensemble was then extended to include the intervals 2006-2023 and 2041-2100, both modeled under the Representative Concentration Pathways scenarios RCP2.6 and RCP8.5 scenarios. To enhance comparability, a downscaling method was applied to refine the coarse-resolution of the climate model outputs to a 1 km spatial resolution, ensuring alignment with observational data. A dynamic weighting scheme was implemented to optimize the ensemble, improving its ability to capture the measured air temperature and precipitation monthly means. Results show that the ensemble significantly improves simulation accuracy, particularly for air temperature. Observations indicate a consistent warming trend, with more pronounced seasonal variations. Precipitation exhibits high interannual variability, a slight downward trend, and an increase in heavy rainfall events. Future projections suggest continued warming and possible changes in precipitation regimes, with more significant reductions under the high emission scenario. These findings highlight the value of a weighted ensemble approach for improving regional climate simulations and emphasize the importance of integrating multiple datasets from different sources to achieve a more comprehensive analysis of regional climate dynamics.