Future changes in the occurrence of large hail events in the Mediterranean region

Hail-proxy indices have been developed over the past years to overcome shortages in hail parameterization in meteorological and climate models. They are mainly focused on reconstructing hail climatology or the frequency of occurrence of hail events during the present or past climate (Prein and Holland 2018, Torralba et al, 2023). Because of their sensitivity to spatio-temporal resolution, they are, however, not specifically designed to simulate long-term changes in the occurrence of large hail events under future climate scenarios.

In this study, we present a novel methodology tailored for CMIP6 climate models under various SSPs scenarios, and in synergy with higher resolution ERA5 reanalysis. Our approach is based on 34 commonly employed hail predictors: their probability distribution functions (pdf) are compared to the hail-conditioned pdf during observed large hail events (hail diameter >2 cm), in order to identify all 3-hourly intervals during the hail season (April to November) in which hailstones might form. These intervals are then combined with coarser GCM trends (individually for each quantile of the pdf) to project future changes in the frequency of hailstorms. The proposed technique provides a simple yet robust framework for assessing future changes in the occurrence of large hail events.

Such a trend-based scaling was rigorously validated using a multi-model ensemble of CMIP6 historical daily simulations and ERA5 reanalysis data. In order to assess the method over the Mediterranean basin and nearby lands, the newly released satellite dataset MASHA was exploited (Laviola et al, 2022). MASHA is the first large hail dataset derived from passive microwave observations; it offers a 3-hourly time resolution and a 1°×1° spatial resolution over the whole Mediterranean basin [5W-35E, 25N-50N] during 1999-2023.

Results of the assessment revealed a good agreement between the simulated and observed average monthly frequency of large hail events and their intradaily variability, highlighting the reliability of the index and its usefulness for climate change projections.