Assimilating of Reflectivity and Radial Velocity in a Unified Convective-Scale 3DVAR Framework: Idealized Thunderstorm Case

The WSR-88D Doppler radar network allows meteorologists to track severe weather events and provide better warning information to the public, ultimately saving lives and reducing property damage. However, the assimilation of such data into NWP models to provide physically consistent three-dimensional analyses and short-term forecasts has not been fully explored. The effective assimilation of Doppler radar data into operational convection-allowing models is of increasing importance in our quest to extend warning lead times. Among the existing data assimilation techniques, the 3DVAR method is a very efficient approach that can use radar data in real-time mode and in very high resolution both spatially and temporally. In this study, the impact of assimilating reflectivity data in addition to radial velocity data with intermittent 3DVAR cycles is examined using an idealized thunderstorm case. The goal of this work is to assimilate reflectivity data into a storm-scale NWP model in a more quantitative approach compared to the currently available cloud analysis. First, a forward operator for reflectivity (Smith et al. 1975) is modified to include a background field from an NWP model forecast as guidance for the automatic classification of hydrometeor types. Previous research on the classification of hydrometeor types is only based on radar observation itself (Zrnic et al. 2001). Three experiments are performed. One uses radial velocity only, the second uses both radial velocity and reflectivity with the original operator from Smith et al. (1975) and the final one uses both radial velocity and the new reflectivity operator with hydrometeor classification. It is found that by assimilating only radial velocity data, the model can reconstruct the supercell thunderstorm after several cycles, but spin-up problems delay the development of precipitation. The spin-up problem is lessened when assimilating reflectivity with the original reflectivity form. But the spin-up time is much reduced with the new reflectivity formulation with hydrometeor classification. The cold pool is also developed early with the new formulation. Smith, P. L., Jr., C. G. Myers, and H. D. Orville, 1975: Radar reflectivity factor calculations in numerical cloud models using bulk parameterization of precipitation processes. J. Appl. Meteor., 14, 1156–1165. Zrnic S. D., A. Ryzhkov, J. Straka, Y. Liu and J. Vivekanandan 2001: Testing a procedure for automatic classification of hydrometeor types, J. Tech., 18, 892-912.