NOAA's Rapid Refresh forecast system (RAP) is an hourly-updated regional data-assimilation and forecasting system that uses the Weather Research and Forecasting (WRF-ARW) model with 13-km horizontal grid spacing and the Gridpoint Statistical Interpolation (GSI) analysis package. The RAP version 2 has been running operationally at NCEP since February 2013 with enhancements including a 3DVAR-Ensemble hybrid assimilation procedure within GSI with the GFS EnKF global ensemble forecasts. 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 2015, we 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. This talk will introduce the progress of our efforts of building RAP ensembles and report the initial test results comparing the RAP GSI hybrid with global ensemble and regional ensembles
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