Research and Development of GSI-based Ensemble-Variational (EnVar) Data Assimilation for Convective Scale Weather Analysis and Forecasts

Xuguang Wang*
School of Meteorology, University of Oklahoma

GSI-based ensemble-variational data assimilation system is extended for direct assimilation of radar data for convective scale weather analysis and forecasts. Several aspects of research, system and methodology development are presented. The performance of the newly extended system are explored by conducting experiments with a few tornadic events. For example, for the 8 May 2003, Oklahoma City, tornadic supercell storm. The experiments were conducted with WRF ARW model at 3km convection allowing resolution. Radar observation including both reflectivity and radial velocity were assimilated every 5 minutes for a total of 1-hour period. The probabilistic forecast of a strong low-level vorticity derived from the ensemble followed well with the observed tornado track for both the location and longevity of the storm. The tornadic supercell maintained the strong updraft and vorticity during the entire 1 h forecast period. Detailed diagnostics revealed that the newly developed system was more correctly analyzed the hydrometeor fields such as the graupel and ice mixing ratio. Such an analysis of the hydrometeor fields led to constructive interaction of the cold pool, the surface gust front and updraft associated with the mid-level mesocyclone.

*Preference: Oral