Low-Level Polarimetric Radar Signatures in EnKF Analyses and Forecasts of the May 8, 2003 Oklahoma City Tornadic Supercell: Impact of Multimoment Microphysics and Comparisons with Observation

The impact of increasing the number of predicted moments in a multimoment bulk microphysics scheme is investigated using ensemble Kalman filter analyses and forecasts of the May 8, 2003 Oklahoma City tornadic supercell storm and the analyses are validated using dual-polarization radar observations. The triple-moment version of the microphysics scheme exhibits the best performance, relative to the single- and double-moment versions, in reproducing the low- hail core and high- arc, as well as an improved probabilistic track forecast of the mesocyclone. A comparison of the impact of the improved microphysical scheme on probabilistic forecasts of the mesocyclone track with the observed tornado track is also discussed. 1. Introduction The assimilation of radar data into storm scale models using the Ensemble Kalman Filter (EnKF) [1] approach has proven to be an extremely useful tool for the analysis and prediction of convective storms in recent years. There have been many recent successful uses of this approach for both analyses [2–7] and short-range forecasts [8–10] based on these analyses. In general, these studies have focused on improving techniques for assimilation of radar data, on the design of the overall data assimilation system, or on the impact of initial and boundary conditions. High-resolution numerical weather prediction has progressed during the past decade such that prediction of the dynamics of individual convective storms is now routinely attempted. One substantial challenge is the improvement and validation of the microphysics parameterization and the associated impacts on storm structure and behavior (e.g., through the development of the cold pool). Errors from the model’s microphysical parameterization can significantly impact forecasts of these storms. Polarimetric radar observations offer a rich source of data to validate the output of such schemes within this context. Several storm-scale simulation studies have shown that the microphysics parameterization has a profound impact on simulated storm structure and behavior [11–17] and even on tornadic potential [18]. Here, we restrict our discussion to bulk microphysics schemes, which assume a priori a certain functional form for the underlying drop or particle size distribution (DSD/PSD) for several hydrometeor categories. Typically, one or more moments of the PSD for a given category are explicitly predicted within a scheme, with single-moment schemes that predict the mass mixing ratio (proportional to the third moment) being the most common. Double-moment schemes that typically predict