In this study, we examine the hail-fall in 20 supercell storms obtained from the 5-yr field research campaign, a Hail Spatial and Temporal Observing Network Effort (HailSTONE). Approximately 2000 instantaneous hail observations were recorded from these events, providing unprecedented spatiotemporal insight into the hail-fall character of each storm. These observations collected during active hail-fall helps mitigate diameter loss from melting effects of stones lying on the ground for unknown periods of time; and more importantly, these datasets provide a unique look at diameters plotted versus time, allowing for a thorough investigation of size sorting in each storm.
This project explores the size sorting in supercells and how these physical measurements at the ground compare with previous modeling results, hodograph characteristics, and the traditional conceptual model of spatial exponential hail-fall in organized storms. It also takes an initial look at the validation of low-level S-band polarimetric radar variables to specific maximum diameter hail sizes, and the related implications of current and future hail size algorithms. Improved identification of storm-relative regions most favorable for large hail will afford for more specific NWS Impact-based Decision Support Services, benefit future algorithm and modeling efforts, and support the proposed next-generation severe weather warning framework associated with Forecasting a Continuum of Environmental Threats (FACETs).