6.4
Recent Improvements of GSI 3DVAR-Ensemble Hybrid Data Assimilation System for Rapid Refresh and High Resolution Rapid Refresh


The current application of GSI hybrid data assimilation within the RAPv2 has significantly improved mid- and upper-level wind and moisture forecasts, but we anticipate further improvement replacing GFS-ensemble forecasts with regional RAP ensemble forecasts within the GSI hybrid-ensemble assimilation. In 2014, we continue tuning and testing the configurations for GFS ensemble based GSI-Hybrid analysis but also invested significant effort to build RAP ensembles, which are initialized from GFS EnKF ensemble members, to feed into RAP GSI hybrid system with a goal of improving RAP forecasts of near-surface fields and localized weather phenomena including cloud/hydrometeor fields. In 2014, we also started to apply GSI hybrid analysis on HRRR system for real-time test. Radar reflectivity assimilation is applied in both RAP and HRRR as a key component of the RAP assimilation using specification of latent-heating within a forward-backward digital filter initialization at 13km and in forward mode only at 3km.