Simulation of Flow Fields in Complex Terrain with WRF-LES: Sensitivity Assessment of Different PBL Treatments

A multiscale modeling study of a real case has been conducted to explore the capability of WRF-LES over the Xiaohaituo Mountain (a game zone for the 24th Beijing-2022-Winter-Olympic-Games). Comparing WRF-LES results with observations collected during the MOUNTAOM (MOUNtain Terrain Atmospheric Observations and Modeling) field campaign, it is found that at 37 m resolution with LES settings, the model can reasonably capture both large-scale events and microscale atmospheric circulation characteristics. Employing SRTM1 (≈30 m) high resolution topographic dataset instead of traditional USGS_30s (≈900 m) dataset effectively improves the model capability for reproducing fluctuations and turbulent features of surface winds. Five sensitivity experiments are conducted to investigate the impact of different PBL treatments, including YSU and SH PBL schemes and LES with 1.5TKE, SMAG and NBA subgrid-scale (SGS) stress models. In this case, at gray zone scales, differences between YSU and SH are negligible. LES outperform two PBL schemes which generate smaller turbulence kinetic energy, and increase the model errors for mean wind speed, energy spectra and probability density function of velocity. Another key finding is that wind field features in the boundary layer over complex terrain are more sensitive to the choice of SGS models than above the boundary layer. With the increase of model resolution, the effects of SGS model become more significant, especially for the statistical characteristics of turbulence. Among these three SGS models, NBA has the best performance compared to observation. Overall, this study demonstrates that WRF-LES is a promising tool for simulating real weather flows over complex terrain.