8A.3 Diagnosing the Microphysical and Dynamical Effects of Mixed-Phase Hydrometeors in Convective Storms Using a Bin Microphysics Model

Tuesday, 8 November 2016: 5:00 PM
Pavilion Ballroom East (Hilton Portland )
Kevin Kacan, University of Wyoming, Laramie, WY; and Z. J. Lebo

Convective storms, especially organized linear convection, are largely controlled by near-surface cooling via both evaporation and melting of falling hydrometeors. The full effect of the former on storm system dynamics is currently an underdeveloped area of research within the scope of atmospheric science. In most numerical simulations, the melting of frozen hydrometeors (e.g., hail, graupel, snow, etc.) is computed within parameterized bulk microphysics schemes, which currently lack the ability to accurately represent mixed-phase hydrometeors (i.e., partially melted hail), which can effect hydrometeor sedimentation, subsequent melting, and evaporation of shed drops.

To better understand the microphysical and dynamical effects of melting in convective storms, a bin microphysics scheme was implemented in the Weather Research and Forecasting (WRF) model for two idealized cases: a supercell storm and a squall line. Ice was partitioned between pristine ice, snow, and a hybrid graupel/hail category, where a melt fraction parameter was added to prognose the amount of melting that occurs in each frozen hydrometeor bin below the freezing level; sensitivity simulations were run for each case to mimic melting in traditional bulk microphysics schemes. The results suggest that by modifying only the melt fraction, the amount and phase of precipitation that reaches the surface can vary greatly. Moreover, the cold pool characteristics also vary, which is likely tied to the differences in the size and number of shed drops in the different melting schemes, which ultimately affects evaporation rates. Perhaps most interesting, by modifying only the melt fraction parameter (i.e., continuous melting versus instantaneous melting), there appears to be a strong influence on the dynamical evolution of the storms. For example, a multi-cellular storm results at the end of the supercell simulation for the instantaneous melting case, while a supercellular storm develops for the opposite extreme, the continuous melting case.

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