Prediction of Fort worth Tornadic Thunderstorms Using 3dvar and Cloud Analysis with Wsr-88d Level-ii Data

The development of high-resolution nonhydrostatic models and the rapid increase of computer power are making the explicit prediction of thunderstorms a reality (Droegemeier 1990; Lilly 1990; Droegemeier 1997; Xue et al. 2003, X03 hereafter). Data assimilation plays an important role in providing an accurate initial condition for the model forecast. The operational US WSR88D Doppler radar network (Crum and Alberty 1993) is a key source of data for initializing stormscale numerical weather prediction (NWP) models as it the only operational platform capable of providing observations of spatial and temporal resolutions sufficient for resolving convective storms. The analysis of radar data to arrive at a complete set of initial conditions for a NWP model is challenging, because radars only observe a very limited set of parameters, the most important being the radial velocity and reflectivity. Their spatial coverage is often incomplete. To determine atmospheric state variables that are not directly observed, certain retrieval or assimilation techniques have to be used. Four-dimensional variational (4DVAR) data assimilation, which obtains a full set of model initial conditions that provides the best fit between the model solution and radar observations within a time (assimilation) window, is considered ideal for this purpose. Some encouraging 4DVAR results with both simulated and real radar data have been obtained by, for example, Sun et al. (1991; 1997; 1998). On the other hand, the complexity of developing and maintaining the adjoint code needed by a 4DVAR system and the high computational cost of 4DVAR technique for highresolution applications are limiting its use in re-