Impact of Assimilating the FY-3E Ocean Surface Wind Vector Product in GSI on NWP Analyses and Forecasts

The Fengyun-3E (FY-3E) satellite, operating in an early morning orbit, provides critical Ocean Surface Wind Vector (OSWV) observations to complement the global observing system. This study evaluates the impact of assimilating FY-3E Wind Field Measuring Radar (WindRAD) OSWV data into numerical weather prediction (NWP) using a dedicated module developed within the Gridpoint Statistical Interpolation (GSI) system based on the hybrid four-dimensional ensemble-variational (Hybrid-4DEnVar) scheme. Cycling assimilation experiments conducted for September 2024 demonstrate that FY-3E OSWV data are effectively integrated, evidenced by a significant reduction in observation-minus-analysis (OMA) statistics compared to observation-minus-background (OMB). The assimilation yields substantial improvements in global wind field analysis, particularly in the lower troposphere below 700 hPa. At 1000 hPa, root-mean-square errors (RMSEs) for zonal and meridional winds decrease by over 2%, an improvement statistically significant at the 95% confidence level. These wind analysis enhancements indirectly improve the representation of geopotential height, temperature, and specific humidity. Forecast evaluations confirm that these optimized initial conditions propagate robustly into downstream predictions. Specifically, wind forecast RMSEs for lead times up to 144 h show consistent reductions (up to 0.13 m s⁻¹), accompanied by an increase in the anomaly correlation coefficient (ACC) of approximately 0.01. Concurrently, short-to-medium-range forecasts of geopotential height, temperature, and specific humidity exhibit sustained skill improvements. In conclusion, assimilation of FY-3E OSWV data consistently enhances multivariate analysis accuracy and forecast skill across the troposphere, highlighting its significant value for operational global NWP.