11.2 Recent Development and Research of GSI-Based Hybrid Ensemble-Variational Data Assimilation for Convective-Scale Predictions

Thursday, 11 January 2018: 10:45 AM
Room 14 (ACC) (Austin, Texas)
Xuguang Wang, Univ. of Oklahoma, Norman, OK; and Y. Wang, J. D. Duda, J. Carley, and D. C. Dowell

GSI based EnKF /hybrid DA system is further developed and implemented to the US NWS convection allowing prediction systems HRRR and NAM CONUS nest. Different from current operational systems which use the coarse resolution GFS ensemble covariance, the new system uses convective scale model’s own EnKF ensemble. Also different from the current systems which use cloud analysis and diabatic digital filter to indirectly assimilate radar reflectivity, the new system adopts a method proposed by Wang and Wang (2017) to directly assimilate reflectivity in GSI based EnVar. Experiments with multiple retrospective cases for the full CONUS domain have found that the newly extended GSI hybrid DA system with direct reflectivity assimilation outperforms the cloud analysis/DFI, measured by various traditional, neighborhood and object based verification metrics. The impact of the radar observations and the optimal DA configurations are dependent on whether the underlying convective systems are strongly or weakly forced. Additional results regarding the best DA configuration will also be discussed in the conference.
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