Hybrid EnKF-3DVAR Data Assimilation Improves Short-Term NWP Forecasts in Alaska

Satellite sounder data has been shown to improve short-term weather forecasts for Alaska when 3DVAR data assimilation is used [1]. A traditional 3DVAR uses a simple static covariance to estimate the analysis. The advanced Hybrid EnKF-3DVAR data assimilation scheme uses ensemble-based, flow-dependent estimate of background error covariance to calculate analysis increment in the variation framework. This study compares the performance of traditional 3DVAR and hybrid EnKF-3DVAR data assimilation schemes in assimilating the NUCAPS profile data for a regional WRF model over Alaska. The experiment runs WRF in three modes: WRF without data assimilation, WRF with 3DVAR, and WRF with hybrid EnKF-3DVAR. The MET tools are used to pair the upper atmospheric data from RAOB and WRF outputs. The statistical analysis for a monthly 24-hour forecast showed that including sounder profile data improves the short-term forecast, while the hybrid EnKF-3DVAR data assimilation scheme has better performance over traditional 3DVAR data assimilation.