Reconstructing Global Severe Hail Environmental Climatology Using Multiple Reanalyses

Severe hailstorms pose significant threats to life, property, and various industries. Hail detection traditionally relies on both surface and remotely sensed observations. However, the limitations in spatial distribution and coverage of these methods, along with inherent deficiencies, hinder accurate global prediction and hail size estimation. Reanalysis data, frequently used in severe weather applications, serves as a surrogate for observed atmospheric data by providing historical environmental profiles derived through data assimilation.

This study aims to reproduce and compare environmental conditions conducive to severe hail frequency to construct a global hail climatology. Utilizing ERA5 and MERRA2 reanalysis datasets, we examine atmospheric parameters associated with hail occurrences, including unstable conditions, melting level height, vertical wind shear, and both dynamical and thermodynamical indices. By applying established relationships and indices for severe weather parameters and accounting for the geographical and climate regime differences across regions, we seek to provide a reliable and valid assessment of the varying importance of each parameter in different areas.

We evaluate the performance of these predictors against ground observations, and conduct a trend analysis to assess how these environmental conditions have evolved over time, considering variability, seasonal, and interannual cycles. Our findings aim to highlight the limitations of universal proxies, and illuminate hail frequency in regions with limited or nonexistent observational data, and ultimately enhance our ability to understand the various mechanisms involved in hail frequency around the globe.