Based on EC, GFS, CMA-MESO and CMA-GFS, the 0-72 h ensemble forecasts of daily surface and high-altitude zonal wind and meridional wind from January to April 2020 from the four models for East China and surrounding areas (20°-40°N，110°-130°E) are evaluated with the augmented complex extended Kalman filter (ACEKF) method. The results show that the ACEKF method outperforms the bias-removed ensemble mean, super-ensemble forecast and single-mode forecasts, and can further reduce the wind speed forecast errors. ACEKF can improve the upper-air wind speed forecasts better than those at ground level. In complex terrain areas the improved wind speed forecast is much better. These results are also reflected in the root-mean-square error and anomaly correlation coefficient for all forecast times.