Describing hail-prone convective environments with high-resolution reanalysis and overshooting top detections
Authors: Giordani Antonio , Kunz Michael , Bedka Kristopher M. , Punge Heinz Jürgen , Paccagnella Tiziana , Di Sabatino Silvana 
Published: February 2023

&lt;p&gt;Hail is one of the most dangerous hazards for agriculture, infrastructures, and buildings of all severe-weather phenomena linked to deep moist convection. Due to global warming, the frequency and severity of hailstorms are expected to increase throughout Europe. It is, therefore, increasingly urgent to improve our understanding of hail hazard and risk. However, the intrinsic difficulties in systematically observing and simulating hail are still a major hurdle. While direct hail observations are heterogeneous, temporally-limited, and scarce, numerical simulations lack sufficient detail to represent the localized and rapidly-evolving hailstorm dynamics. A possible way to indirectly assess hail likelihood is through remote-sensing detections combined with numerical dynamical and thermodynamical characteristics of convective environments prone to hailstorm formation. Indeed, multiple data sources are necessary as, to date, more than a singular proxy is required to characterize hail.&lt;/p&gt;
&lt;p&gt;The new high-resolution reanalysis dataset SPHERA (High rEsolution ReAnalysis over Italy), developed at ARPAE, is considered for investigating hail-favoring environments over Italy and nearby countries. SPHERA is dynamically downscaled from ERA5, driven by the convection-permitting model COSMO (at 2.2 km grid spacing), providing meteorological data at hourly frequency. A set of parameters is extracted from SPHERA and combined with Overshooting cloud Top (OT) satellite detections, constituting a reliable proxy for hail. A probabilistic algorithm recently developed at NASA automatically detects OTs from geostationary Meteosat Second Generation SEVIRI infrared images. However, not all OTs are associated with hail formation in the storm. Hence, a filter is developed to retain only those occurrences linked to potential hailstorm formation based on the surrounding environmental conditions. To do so, ESWD (European Severe Weather Database) crowdsourced reports, representing the most reliable hail observational dataset in Europe, are coupled with SPHERA proxies to investigate convective environments nearby hailstorm events.&lt;/p&gt;
&lt;p&gt;The procedure is applied over five years (2016-2020). Hence, the primary purpose is to present the methodology rather than a sound hail frequency estimate. The resulting hailstorm characterization reveals a non-hailing OTs removal exceeding a quarter, mainly over the Mediterranean sea and complex-topography areas. The maximum hail likelihood is observed over pre-Alpine regions and the northern Adriatic sea around 15 UTC in June-July, in agreement with recent European hail climatologies. The validation against ESWD reports provides a hit rate exceeding 60%, roughly 20% more than the previous&amp;#160;non-probabilistic OT detections coupling with ERA-Interim over Europe. Separating hit/miss reports and small/large hail reveals different characteristics of hail-prone environments. Most hit reports pertain to large hailstones (diameters &amp;#8805; 3 cm), suggesting an inclination of the method to perform better in cases of severe hail occurrences. Investigating the interrelations among SPHERA parameters quantifying the main mechanisms needed for hail formation (i.e., atmospheric instability, freezing level height, and storm organization), the leading role of thermal and thermodynamical factors over the kinetics of the storm emerges.&lt;/p&gt;
&lt;p&gt;These results suggest promising opportunities to enhance hail dynamics comprehension owing to the advancements in remote-sensing techniques and the development of convection-permitting numerical simulations. In addition, further extension of the analysis should shed more light on the climatology of hailstorms.&lt;/p&gt;