Abstract:In this study, to meet the fine meteorological service requirements proposed by the Organizing Committee for the Beijing Winter Olympic Games, a real-time forecasting system with 100 m horizontal grid spacing RMAPS-LES which was coupled with mesoscale meteorological model and large eddy simulation was especially built for the Yanqing and Zhangjiakou competition zones. Based on the observation data of Winter Olympics zones and the 3 km×3 km horizontal grid spacing from “CMA-BJ” mesoscale forecast system, the RMAPS-LES results of the competion months (February to March) from 2020 to 2022 are compared and verified at different space-time scales. The results show that the high-resolution microscale RMAPS-LES has a higher prediction in forecasting wind and temperature than the CMA-BJ mesoscale model. The mean absolute error (MAE) of average hourly 2 m temperature of all stations in the three years for the Winter Olympic Games is 1.85℃, which is 28% less than the CMA-BJ model, the MAE of the hourly average 10 m wind speed is 2.11 m·s-1, which is 23.6% less and the instantaneous wind direction MAE is 44.43°, 30.33% lower. Relative to the CMA-BJ model, RMAPS-LES has the advantage of obtaining high-frequency data that can describe the atmospheric microscale turbulent motion in detail. The verification results indicate that the probability density distribution of wind speed fluctuation is basically close to the normal distribution, nearing the observations. It is also found that when dynamic downscaling is used, the inflow turbulence generation method needs to be used for different-scale simulation to accelerate the rapid generation of atmospheric turbulence in the large eddy simulation region. The RMAPS-LES uses the turbulence generation scheme based on random disturbance of grid potential temperature, which can substantially reduce the transitional zone and achieve fully developed turbulence. The technical route of RMAPS-LES can also be widely used in the wind power generators selection， forest fires， outdoor activities， and other scenes that have high requirements for fine local meteorological forecasts.