Investigating the Role of Evolving Ice and Snow Geometric Aspect Ratio in Thunderstorm Electrification

The goal of this study is to understand how the consideration of ice and snow growing habits (shape) affects other microphysical processes and electrification. Idealized and real simulations of a May 20^th 2011 squall line in Oklahoma are conducted in WRF using a variety of traditional (NSSL two moment (N2M), Morrison two moment (M2M)) and novel (Adaptive Habit Model, hereafter AHM) microphysical schemes. The highlight in AHM is that it dynamically evolves ice and snow aspect ratio according to environmental temperature and supersaturation. This additional information on ice and snow is then used to more realistically represent particle characteristics, and related processes like deposition/sublimation, melting, aggregation, sedimentation. An electrification scheme previously available only in N2M has been implemented into M2M and AHM. There are 5 members of simulations: N2M, M2M, AHM without shape-aware calculation (AHM_sphere), AHM with shape-aware ice only (AHM_ice), AHM with shape-aware ice and snow (AHM_ice_snow). Results are analyzed in terms of hydrometeor mass and number, characteristic size and fall speed, microphysical process rates, charging rates, lightning rates. The real simulation results are compared against observation from NEXRAD radar gridded by GridRad, Oklahoma Lightning Mapping Array, and National Lightning Detection Network. Results show that aggregation plays a very important role in lightning generation, and that a sufficient graupel fall speed is crucial during non-inductive charging to generate electric field strong enough to initiate lightning a breakdown.