Application of WRF-LES on the Simulation of Seasonal Characteristics of Atmospheric Boundary Layer Structure in Taklamakan Desert

Abstract

The lack of observational data in Taklamakan Desert makes it very difficult to study its unique boundary layer structure. As a common means of supplementing observational data, the mesoscale boundary layer parameterization scheme in the numerical model method is difficult to capture small-scale turbulent processes, which may lead to large deviations in simulation. In order to obtain more accurate simulation data of desert atmospheric boundary layer, nested LES into WRF (WRF-LES) was configured to simulate the seasonal variations in Taklamakan Desert. By comparing LES with the conventional boundary layer parameterization scheme, the error characteristics between the two schemes are analyzed. The results show that LES exhibits superior performance in solving key atmospheric features such as small-scale processes and low-level jet streams. The simulation results in winter and summer have great uncertainty due to the boundary condition errors, respectively. LES also shows the maximum and minimum optimization degree in summer and winter, respectively, while the simulation results in spring and autumn are relatively stable. In the analysis of turbulence parameters, there are clear seasonal differences in turbulence characteristics, and the intensity of turbulence in summer is significantly higher than that in other seasons. When turbulent activity is strong, the difference in potential temperature and horizontal wind speed simulated between the two schemes is closely related to intense turbulent kinetic energy in LES. More accurate turbulence reproduced in LES leads to the better potential temperature and horizontal wind speed simulations in summer. In addition, large-scale cloud systems can lead to considerable simulation bias. Neither scheme can accurately simulate the cloud emergence process, and large differences between the two schemes occur at this point.