The current GSI (Gridpoint Statistical Interpolation) is a three-dimensional variational (3DVar) data assimilation system, using static (climatology) background error covariance. In reality the background error covariances are flow-dependent. As an upgrade of the 3DVar data assimilation, hybrid ensemble-variational data assimilation improves the background error covariances by incorporating the flow-dependent information from the ensembles and has been proved to have superior performance to the pure 3DVar data assimilation and costs less computing resources than EnKF. At DTC, testing and evaluation of the hybrid ensemble-variational data assimilation systems is being conducted in collaboration with code developers. In this work, GSI based hybrid variational-ensemble (Hybrid-GSI) data assimilation system is tested with HWRF (WRF for Hurricanes) as part of the efforts of HFIP (Hurricane Forecast Improvement Program) in improving the accuracy of the hurricane forecasting. Retrospective cases will be run and preliminary results will be presented.