Characterization of Surface-Layer Turbulence Using Scanning Lidar Data at the WFIP-2 Site

Turbulent structures in the lower part of the atmosphere play a major role in the exchange of heat and momentum in the atmospheric boundary layer. It is often challenging to characterize their nature using limited data from traditional measuring instruments. A numerically simulated flow field provides spatially resolved flow; however, it may not accurately capture the real turbulence structures that vary with atmospheric stability and surface and lateral forcings of the boundary layer. Herein, we used radial velocity data from scanning lidar and heat flux measurements from a meteorological station collected over a five-month period in 2016 during the Wind Forecasting and Improvement 2 (WFIP2) field campaign in the Columbia Gorge, Oregon. These large datasets were used to characterize the turbulence at that location under unstable and stable conditions using an ensemble approach. To compare the lidar data under the unstable condition, the flow field for a fair-weather day was also simulated using WRF-LES. Proper orthogonal decomposition (POD) analysis was employed to detect the coherent structures present in the scanning lidar data, whereas the second order moment of the measured velocity was used to analyze the turbulence scale in the surface layer. The results showed that the size and shape of turbulent structures vary with the stability of the atmosphere as well as the mean wind speed. There are more coherent and turbulent energy in the unstable condition compared to the stable condition. The flow field from both scanning lidar and simulated flow showed streak-like structures orienting along the mean wind near the surface, indicating that the simulation can capture the real flow structures near the surface that that occur under daytime, moderate wind conditions.