Accuracy of supercell cold pools in multiparameter WRF/DART EnKF simulations

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Thursday, 6 February 2014: 4:15 PM
Room C203 (The Georgia World Congress Center )
Anthony E. Reinhart, Texas Tech University, Lubbock, TX; and C. C. Weiss, D. C. Dowell, and H. Morrison

An ongoing study is considering the ability of numerical weather prediction microphysical parameterizations to properly simulate supercell cold pools. Inaccuracies in these parameterizations have led typically to an overestimation of high-level clouds, precipitation amounts, and magnitude of evaporative cooling, which impact the evolution and strength of the supercell cold pool. Two-moment microphysics schemes address several issues with particle size distributions, but new challenges remain. For example, the method of raindrop breakup used in schemes can lead to a large difference in cold pool magnitude and evolution.

This study investigates two cases from the Verification of the Origins of Rotation in Tornadoes Experiment 2 (VORTEX2) using different microphysical parameterizations to determine the role of environmental heterogeneity and effect of different drop breakup schemes and efficiencies on the supercell cold pool. Simulations are conducted, initialized from soundings obtained by VORTEX2 rawinsonde platforms and using WRF/DART to assimilate WSR-88D and mobile radar radial velocity data onto a 1 km domain. The EnKF technique is used in order to minimize the initial condition error and otherwise best produce the observed atmospheric state, allowing for a focus on errors attributed to bulk microphysical parameterizations. Each ensemble member has one of three different drop breakup schemes, different mean drop sizes for breakup to begin occurring, and varying falls speeds for large frozen particles; leading to a broad range of possible cold pool magnitudes and orientations while maintaining spread. Results will show that, using StickNet measurements as verification, varying the drop breakup parameter leads towards a more accurate cold pool in the ensemble mean or a subset of the ensemble.