Climate model ensembles reveal increasing future extreme precipitation in Northern Italy

Abstract. Assessing future changes in extreme precipitation remains a critical challenge for climate adaptation and flood risk mitigation. While growing observational evidence indicates an intensification of short-duration extreme precipitation, robust quantification of these changes and how it will change in the future remains uncertain. Using one of the longest continuous daily precipitation records available, dating back to 1 January 1813 in Bologna, we evaluate the ability of 22 bias-corrected CMIP6 climate models to reproduce historical extreme precipitation characteristics based on four standardized extreme precipitation indices. Building on this evaluation, we develop a comprehensive assessment framework that combines bias correction, independent validation and multi-model ensemble (MME) schemes. We present a comparison of Bayesian Model Averaging (BMA) with Simple Model Averaging (SMA) and individual model simulations, and apply both MME schemes to project 21st-century changes in extreme precipitation under different emission scenarios. The results show that MME schemes provide a more stable and robust representation of extreme precipitation than most individual models. Among the projected changes, the intensity indices show robust increasing signals across most scenarios and periods, with more pronounced enhancement under high-emission conditions in the far future. By contrast, the frequency-related indices show more complex responses: the annual count of days where precipitation is greater than or equal to 20mm and 10mm (R20mm and R10mm) exhibits a weak increasing tendency and no sustained increasing signal, respectively, with R10mm projected to decline under SSP5-8.5. This study provides a robust framework for assessing future changes in station-scale extreme precipitation and for better characterizing the associated projection uncertainties.