276 Assimilation of Polarimetric Radar Data to Improve the Microphysical State of Tornadic Supercells Using the Ensemble Kalman Filter

Thursday, 17 September 2015
Oklahoma F (Embassy Suites Hotel and Conference Center )
Bryan J. Putnam, CAPS/ARRC/Univ. of Oklahoma, Norman, OK; and M. Xue, Y. Jung, N. Snook, D. J. Bodine, and G. Zhang

Polarimetric radar data are assimilated using the ensemble Kalman Filter (EnKF) and an advanced double-moment (DM) microphysics (MP) scheme to improve the analyzed and forecast microphysical state of tornadic supercells on 10 May 2010 in Oklahoma. The polarimetric variables provide important information on the particle size distributions (PSDs) of hydrometeors including size and liquid water content. They also increase the amount of observed information distributed among the MP scheme state variables compared to assimilating reflectivity (ZH) and radial velocity (Vr) alone, which is more significantly under-constrained when using a DM MP scheme. Experiments that assimilate ZH and Vr from the S-band WSR-88D radar KTLX and different combinations of differential reflectivity (ZDR) and specific differential phase (KDP) from the National Severe Storm Laboratory's (NSSL) polarimetric S-band WSR-88D radar KOUN are considered to evaluate the impact each variable has on the model microphysical state. The results are evaluated using simulated polarimetric radar data to compare to KOUN and to the Advanced Radar Research Center's (ARRC) polarimetric C-band radar OU-PRIME, which provides an additional source for independent verification. Particular attention is paid to the replication of known polarimetric signatures such as the ZDR arc.
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