Impact of Spectral Nudging Technique Driven with ECMWF Data on the Fine Numerical Prediction of Super Typhoon Lekima (2019) in Zhejiang Province

In order to improve the performance of high-resolution regional numerical modeling, the impact from spectral nudging (SN) technique driven with the ECMWF data on the fine prediction of super typhoon Lekima (2019) in Zhejiang Province is investigated with the Weather Research and Forecasting (WRF) model, based on both the advantages of high accuracy forecasting data from European Centre for Medium-range Weather Forecasts (ECMWF) and SN technique. The results show that: (1) The improvement by using SN to track Lekima is obvious. For instance, the maximum hourly track error can be reduced by 80 km. Overall the improvement is the most significant for the track and intensity of Lekima (2019) when nudging is adopted above 800 hPa. (2) In Zhejiang Province, the fine predictions of gale and heavy rainfall induced by Lekima (2019) are largely improved through SN technique. Compared to the control experiment, the increased percentage of ETS (Equitable Threat Score) score for the wind stronger than 17.2 m s⁻¹ is about 8% in mean and 20.8% in maximum. At the same time, the increased rates of TS (Threat Score) scores for the rainfall heavier than 50 mm (24 h)⁻¹ and 100 mm (24 h)⁻¹ reach 11.8% and 26.2%, respectively. (3) Further diagnosis illustrates that wind field spectral nudging can amend effectively the west deviation of typhoon track, the over-prediction of strong wind, and the heavy rainfall in southwest of Zhejiang Province, which all are related to the improvements in the atmospheric elements in troposphere, steering flow of Lekima, low-level wind field, and the resulted rainfall enhancement effect by the local topography.