Assimilating FY4A AMV Winds with the Nudging－ Forced－3DVar Method for Promoting the Numerical Nowcasting of “7.20” Rainstorm over Zhengzhou

Geostationary atmospheric motion vectors (e.g., FY4A AMVs) are routine mid-upper atmospheric observations used in numerical weather prediction (NWP) models, yet their complex spatiotemporal errors and assimilation limitations, i.e., high-temporal/coarse-spatial data and large-scale-adjustment/direct-assimilation scheme, leave unclear impacts of AMVs assimilation on nowcasting forecasts. To this end, a Nudging-Forced-3DVar (NFV) scheme is designed within a multi-scale (i.e., 12-, 4-, and 1-km) regional NWP framework to exploit AMVs characteristics; ablation experiments for the Zhengzhou “7·20” rainstorm isolate Nudging and 3DVar impacts on assimilation and nowcasting. Results show: 1) large-scale Nudging and high-resolution 3DVar both improve mid-upper analyses, with the former ingesting more observations; 2) Nudging retains large-scale background updates but yields significant misses, whereas 3DVar intensifies rainfall extremes yet blurs fine structures; 3) NFV merges their strengths, modulating deep convection through upper-level systems and markedly improving rainfall spatiotemporal patterns. Therefore, NFV is recommended for the FY4A AMVs’ future numerical nowcasting, which provides useful guidance for regional application of geostationary 3D-winds.