Towards using overshooting tops in improving probabilistic risk models of (very) large hail across Europe

Large hail events produced by severe convective storms (SCSs) have emerged as a critical concern for the insurance sector, driven by a significant rise in insured losses from severe hail events across densely populated regions of Europe in recent years. Further complicating the relationship between losses and hail events is shifts to the underlying probability of SCSs occurrence and severity due to anthropogenic climate change. Record-breaking hail events, such as those observed in France and Italy in recent years, underscore the evolving risk that hail poses currently in Europe and may further pose in the future under changing climatic conditions. 

As part of an overarching goal of improving probabilistic models for convective hazard occurrence (especially across data-sparse regions), in the present work, we seek to better understand the relationship between remotely-sensed convective signatures, like overshooting tops (OTs), with large hail occurrences in SCSs. Specifically, OTs retrieved from satellite data provide a uniquely consistent view, spanning multiple decades, of the most intense convective updrafts across Europe. By employing a recently developed 21-year dataset of convective storms and overshooting tops over Europe derived from MSG SEVIRI infrared imagery (developed by NASA), we will compare OT occurrence and intensity across Europe with ground-based severe hail reports from the European Severe Weather Database (ESWD). OT events are first assigned into clusters based on spatiotemporal constraints. The frequency of these clusters will then be compared to modeled, multi-decadal trends in (very) large hail from the Additive Regression Convective Hazard Models (AR-CHaMo) in order to gain a first-order understanding of the potential predictive skill of OTs for large hail. We will also provide preliminary results of using OTs as an input predictor of hail occurrence in the AR-CHaMo models of hail risk across Europe. Finally, near-storm environmental characteristics, derived from ERA5 reanalysis, will be used to compare attributes of the thermodynamic and kinematic vertical profiles that may, or may not, differentiate between OT clusters, including a cluster’s orientation, length, width, and the severity of hail (or the lack thereof) assigned to each cluster.