Gaoyuan qixiang (Jun 2023)

Simulation of Near-Surface Wind over Mentougou with WRF-LES and Sensitivity Study of Planetary Boundary Layer Schemes

  • Yeqing LI,
  • Chunxiang SHI,
  • Runping SHEN,
  • Yun SU,
  • Dejie ZHANG,
  • Lingling GE

DOI
https://doi.org/10.7522/j.issn.1000-0534.2022.00084
Journal volume & issue
Vol. 42, no. 3
pp. 758 – 770

Abstract

Read online

Human life is affected by the intensity of near-surface wind fields, so obtaining high-precision wind field meteorological live products is essential. Precise and accurate wind field simulation can provide data support for real-time weather products. At present, the spatial-temporal resolution of the mesoscale model is low, which cannot meet the requirement of local fine-scale simulation. In this study, based on the large eddy simulation (LES) nested in the medium-scale Weather Research and Forecast Model (WRF), we simulated the near-surface wind field in the eastern part of the Mentougou region, which has five layers of two-way nesting. Meanwhile, combined with ground meteorological observation, we designed sensitivity experiments of boundary layer and Subgrid-Scale (SGS) models to compare the effects of YSU and LES boundary layer schemes on inner layer nesting at 1 km resolution, and examined and evaluated the applicability of different SGS models in the real atmosphere. The results show that the YSU boundary layer can perform better simulation than the LES boundary scheme when turned on at the mesoscale transition resolution of 1 km, with fewer errors and the ability to capture turbulence details. In the different SGS models sensitivity experiments (1.5TKE, SMAG, 1.5TKE_NBA and SMAG_NBA), there is little difference in the NBAs. SMAG had the slightest root-mean-square error and the highest correlation coefficient for statistical indicators. However, the wind speed simulation of four models still underestimates the high value and overestimates the low value.SMAG is closest to the observation in the wind vector distribution and probability density distribution of the wind. In the instantaneous spatial distribution of the wind field, SMAG_NBA shows a competitive advantage in capturing fine turbulence.

Keywords