Characterizing hail-prone environments using convection-permitting reanalysis and overshooting top detections over south-central Europe

Among severe weather events related to deep moist convection, hail represents one of the most hazardous perils for terrestrial ecosystems and human-related activities such as agriculture and building and insurance sectors. Furthermore, the severity and frequency of high-impact hailstorms is increasing throughout Europe, with the highest potential to worsen expected over northern Italy. However, multiple limitations hinder a comprehensive understanding of where and when severe hail can occur. Indeed, the scarcity and incompleteness of information provided by the available observations, and the approximate representations possible with numerical simulations limit a thorough assessment of hail occurrence. These challenges call for new approaches that combine information from different available sources, such as remote sensing instruments, observations, or numerical modeling.

In this work, a proxy for hail frequency is developed by combining overshooting cloud top (OT) detections from the Meteosat Second Generation (MSG) weather satellite with convection-permitting SPHERA reanalysis predictors describing hail-favorable environmental conditions. Atmospheric properties associated with ground-based reports from the European Severe Weather Database (ESWD) are considered to define specific criteria for data selection. Five convection-related parameters from reanalysis data quantifying key ingredients for hailstorm occurrence enter the filter built to sub-sample the OTs, namely: most unstable convective available potential energy (CAPE), K index, surface lifted index, deep-layer shear, and freezing level height. A hail frequency estimate over the extended summer season (April-October) in south-central Europe is presented for a test period of 5 years (2016-2020). OT-derived hail frequency peaks at around 15 UTC in June-July over Italian pre-Alpine regions and the northern Adriatic sea. The hail proxy statistically matches with ∼63% of confirmed ESWD reports, which is roughly 23% more than the previous estimate over Europe obtained by coupling deterministic satellite detections with coarser global reanalysis ambient conditions. The separation of hail events according to their severity highlights enhanced appropriateness of the method for large-hail-producing hailstorms (with hailstones diameters ≥ 3 cm). Further, signatures for small-hail missed occurrences are identified, which are characterized by lower instability and organization, and warmer cloud-top temperatures.