TY - JOUR
T1 - Simulation of flow fields in complex terrain with WRF-LES
T2 - Sensitivity assessment of different PBL treatments
AU - Liu, Yujue
AU - Liu, Yubao
AU - Muñoz-Esparza, Domingo
AU - Hu, Fei
AU - Yan, Chao
AU - Miao, Shiguang
N1 - Publisher Copyright:
© 2020 American Meteorological Society.
PY - 2020/9
Y1 - 2020/9
N2 - A multiscale modeling study of a real case has been conducted to explore the capability of the large-eddy simulation version of the Weather Research and Forecasting Model (WRF-LES) over Xiaohaituo Mountain (a game zone for the Beijing, China, 2022 Winter Olympic Games). In comparing WRF-LES results with observations collected during the Mountain Terrain Atmospheric Observations and Modeling (MOUNTAOM) 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 the Shuttle Radar Topography Mission 1 arc s dataset (SRTM1; ~30 m) high-resolution topographic dataset instead of the 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/Shin and Hong (SH) PBL schemes and LES with 1.5-order turbulence kinetic energy closure model (1.5TKE), Smagorinsky (SMAG), and nonlinear backscatter and anisotropy (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 that generate smaller turbulence kinetic energy and increase the model errors for mean wind speed, energy spectra, and probability density functions 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 the SGS model become more significant, especially for the statistical characteristics of turbulence. Among these three SGS models, NBA has the best performance. Overall, this study dem-onstrates that WRF-LES is a promising tool for simulating real weather flows over complex terrain.
AB - A multiscale modeling study of a real case has been conducted to explore the capability of the large-eddy simulation version of the Weather Research and Forecasting Model (WRF-LES) over Xiaohaituo Mountain (a game zone for the Beijing, China, 2022 Winter Olympic Games). In comparing WRF-LES results with observations collected during the Mountain Terrain Atmospheric Observations and Modeling (MOUNTAOM) 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 the Shuttle Radar Topography Mission 1 arc s dataset (SRTM1; ~30 m) high-resolution topographic dataset instead of the 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/Shin and Hong (SH) PBL schemes and LES with 1.5-order turbulence kinetic energy closure model (1.5TKE), Smagorinsky (SMAG), and nonlinear backscatter and anisotropy (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 that generate smaller turbulence kinetic energy and increase the model errors for mean wind speed, energy spectra, and probability density functions 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 the SGS model become more significant, especially for the statistical characteristics of turbulence. Among these three SGS models, NBA has the best performance. Overall, this study dem-onstrates that WRF-LES is a promising tool for simulating real weather flows over complex terrain.
KW - Atmosphere
KW - Mesoscale models
KW - Mountain meteorology
KW - Turbulence
KW - Valley/mountain flows
UR - https://www.scopus.com/pages/publications/85091962025
U2 - 10.1175/JAMC-D-19-0304.1
DO - 10.1175/JAMC-D-19-0304.1
M3 - Article
AN - SCOPUS:85091962025
SN - 1558-8424
VL - 59
SP - 1481
EP - 1501
JO - Journal of Applied Meteorology and Climatology
JF - Journal of Applied Meteorology and Climatology
IS - 9
ER -