Impact of Configurations of Rapid Intermittent Assimilation of Wsr-88d Radar Data for the 8 May 2003 Oklahoma City Tornadic Thunderstorm Case
نویسندگان
چکیده
The operational WSR-88D Doppler radar network of the United States (Crum and Alberty 1993) has dramatically improved the ability of severe weather warning in routine operations (Serafin and Wilson 2000); it is also playing an important role in storm-scale data assimilation and model initialization, because it is the only observational network that can resolve convective storms. However, the analysis of radar data to arrive at a complete set of initial conditions for a numerical weather prediction (NWP) model is challenging, because radars only observe a very limited set of parameters, mainly, the radial velocity and reflectivity. Further, their spatial coverage is usually incomplete. To build up suitable dynamically balanced storms in a model from radar observations, retrieval or assimilation methods that take advantage of the high data frequency is usually necessary. Four-dimensional variational (4DVAR) data assimilation method is considered ideal for this purpose and some encouraging results with both simulated and real radar data have been obtained (Sun et al. 1991; Sun and Crook 1997,1998). However, the difficulty of getting the adjoint code and the high cost of computation are limiting its use in research and operation. Another relatively new technique is the ensemble Kalman filter (EnKF) data assimilation, which can produce the similar quality assimilation of thunderstorms with single-Doppler radar data as the 4DVAR (Snyder and Zhang 2003; Zhang et al. 2004; Tong and Xue 2005). While also expensive in computation, EnKF method is easier to implement and more flexible.
منابع مشابه
Analysis of a Tornadic Meoscale Convective Vortex Based on Ensemble Kalman Filter Assimilation of CASA X-band and WSR-88D Radar Data
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