Climate attribution of Italian cyclone-driven precipitation extremes using a regional large ensemble

Climate attribution science deals with understanding the role of climate change in impactful weather and climate events. It consists in comparing two sets of weather instances which are selected as analogues of the chosen event, one set in the ‘past climate’ and one in the ‘present climate’. The comparison allows to demonstrate the influence of climate change in the hazards produced by the present analogues against those by the past analogues (or future analogues against present analogues, if the interest is for the changes in future events). These analyses can lack in robustness because of the limited size of the datasets where the weather analogues are searched for – often the case in observation-derived datasets such as reanalyses, or because of the uniqueness of the event – e.g., when the small-scale details are important for the development of the hazards. In the Mediterranean region attribution of cyclone-driven hazards is made difficult by the fact that systems which are synoptically similar to each other may lead to a pletora of surface impacts. This is because the impacts depend on the small-scale interactions between the cyclone-driven circulation and the complex Mediterranean surface topography. Morover, the small scales are not always well captured by global atmospheric models such as those used to run reanalysis.

In this work we focus on a selection of high-impact, cyclone-driven precipitation extremes that have affected Italy during the recent climatological period. We search for analogues of these events in the regional large-ensemble climate projections run with CRCM5 model as part of the ClimEx project. The use of a large 50-member ensemble and the high spatial resolution (12 km) are crucial for addressing both sampling limitations and the representation of small-scale processes, which in the Mediterranean region contribute to precipitation extremes. The extensive ensemble size allows for a meaningful investigation of present and future changes in cyclone-driven extremes over Italy. Furthermore, the ensemble is sufficiently large to perform convergence tests, which help determine the minimum sample size required to obtain reliable attribution results for each selected case. By comparing these convergence behaviours across multiple extreme events, we explore the consistency and reliability of climate attribution statistics in the Mediterranean context. The results of this study therefore provide new insights into both the influence of anthropogenic climate change on severe precipitation events in Italy and the methodological soundness of attribution studies in complex regional settings like the Mediterranean.