ISSN 1000-0526
CN 11-2282/P
CN 11-2282/P
Archive > Volume 48 Issue 4 > 2022,48(4):393-405. DOI:10.7519/j.issn.1000-0526.2022.011901 Prev Next
Multi-Model Ensemble Forecasts of Wind over East China by Using Augmented Complex Extended Kalman Filter
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Abstract:
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.
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