Comparison of Measured and WRF-LES Turbulence Statistics in a Real Convective Boundary Layer over Complex Terrain

Resolving the finest turbulent scales present in the lower atmosphere using numerical simulations helps to study the processes that occur in the atmospheric boundary layer, such as the turbulent inflow condition to the wind plant and the generation of the wake behind wind turbines. This work employs several nested domains in the WRF-LES framework to simulate conditions in a convectively driven cloud free boundary layer at an instrumented field site in complex terrain. The innermost LES domain (30 m spatial resolution) receives the boundary forcing from two other coarser resolution LES outer domains, which in turn receive boundary conditions from two WRF-mesoscale domains. Wind and temperature records from sonic anemometers mounted at two vertical levels (30 m and 60 m) are compared with the LES results in term of first and second statistical moments as well as power spectra and distributions of wind velocity. For the two mostly used boundary layer parameterizations (MYNN and YSU) tested in the WRF mesoscale domains, the MYNN scheme shows slightly better agreement with the observations for some quantities, such as time averaged velocity and Turbulent Kinetic Energy (TKE). However, LES driven by WRF-mesoscale simulations using either parameterization have similar velocity spectra and distributions of velocity. For each component of the wind velocity, WRF-LES power spectra are found to be comparable to the spectra derived from the measured data (for the frequencies that are accurately represented by WRF-LES). Furthermore, the analysis of LES results shows a noticeable variability of the mean and variance even over small horizontal distances that would be considered sub-grid scale in mesoscale simulations. This observed statistical variability in space and time can be utilized to further analyze the turbulence quantities over a heterogeneous surface and to improve the turbulence parameterization in the mesoscale model.