Microphysical Studies of Melting Hail Using In Situ Aircraft Measurements, Cloud Modeling, and Polarimetric Radar Data

Abstract

Hail is a highly destructive severe weather hazard, causing over $10 billion USD in insured losses annually. Beyond impacts to personal and commercial property, industries such as agriculture and aviation are also highly vulnerable to the damaging nature of hail. Advanced polarimetric weather radars provide the primary means for remotely detecting hail, estimating its size, and issuing timely warnings. However, existing methodologies for quantifying and forecasting large hail remain limited, particularly due to uncertainties in relating radar signatures to hail microphysics and storm dynamics. This research leverages unique in situ observations from the armored T-28 aircraft, which has sampled hail-bearing storms across multiple field campaigns, to better constrain these relationships. Throughout this work, I investigate the sensitivity of polarimetric radar variables to hail size aloft and the role of downdraft dynamics in shaping radar signatures in hail-producing storms. Using a one-dimensional downdraft model with spectral bin microphysics initialized from T-28 aircraft observations, I examine how different definitions of maximum hail size (Dmax) influence simulated vertical profiles of reflectivity (ZH), differential reflectivity (ZDR), and specific differential phase (KDP). The model framework enables controlled exploration of how microphysical assumptions and environmental conditions influence both radar presentation and downdraft evolution. By linking in situ measurements, modeling, and radar observations, this work aims to improve understanding of hail microphysics and support the development of more optimized radar-based hail detection and prediction methodologies. The results demonstrate that uncertainty in the assumed maximum hail size propagates directly into simulated polarimetric radar signatures. While the inclusion of modeled downdrafts produced measurable reductions in hydrometeor concentration and corresponding decreases in radar variables, these effects were secondary to the influence of the particle size distribution and environmental thermodynamic structure. Comparison with S-Pol observations from the 29 June 2000 STEPS field campaign showed that the model successfully reproduced the primary characteristics of the observed vertical profiles of ZH, ZDR, and KDP, providing confidence that the coupled aircraft-model-radar framework captures the dominant physical processes governing melting hail. These findings improve understanding of how particle size distribution uncertainty and vertical transport influence polarimetric radar observations and provide guidance for the continued development of radar-based hail detection and quantitative precipitation estimation algorithms.