Evaluating vector winds over eastern China in 2022 predicted by the CMA-MESO model and ECMWF forecast

Abstract

Vector winds play a crucial role in weather and climate, as well as the effective utilization of wind energy resources. However, limited research has been conducted on treating the wind field as a vector field in the evaluation of numerical weather prediction models. In this study, the authors treat vector winds as a whole by employing a vector field evaluation method, and evaluate the mesoscale model of the China Meteorological Administration (CMA-MESO) and ECMWF forecast, with reference to ERA5 reanalysis, in terms of multiple aspects of vector winds over eastern China in 2022. The results show that the ECMWF forecast is superior to CMA-MESO in predicting the spatial distribution and intensity of 10-m vector winds. Both models overestimate the wind speed in East China, and CMA-MESO overestimates the wind speed to a greater extent. The forecasting skill of the vector wind field in both models decreases with increasing lead time. The forecasting skill of CMA-MESO fluctuates more and decreases faster than that of the ECMWF forecast. There is a significant negative correlation between the model vector wind forecasting skill and terrain height. This study provides a scientific evaluation of the local application of vector wind forecasts of the CMA-MESO model and ECMWF forecast.

摘要

本文利用矢量场评估VFE方法, 从矢量场角度系统性评估CMA-MESO模式与ECMWF模式对2022年华东地区10 m高度矢量风场的预报技巧. 结果表明, ECMWF模式对矢量风场空间分布与风场强度的预报均优于CMA-MESO模式. CMA-MESO模式明显高估了矢量风场的强度. 模式预报技巧随着预报时效的延长而下降, 其中以CMA-MESO模式的预报技巧波动更大, 衰减更迅速. 本研究将为CMA-MESO模式与ECMWF模式风场预报产品的本地化应用, 提供一个科学的评估依据.