Correction for Spatial Averaging on Pulsed Doppler Wind LiDAR Measurements

Abstract:

In the last decades, pulsed wind LiDAR technology has been used for turbulence studies in the atmospheric surface layer by means of several scanning strategies. Yet, when a pulsed wind LiDAR is used to characterize the standard deviation of the streamwise velocity in the inertial sublayer, a remarkable underestimation of the energy content may arise due to the underestimated energy content of eddies whose size is comparable or smaller than the probe length. This feature is evident observing the departure of the turbulent energy spectrum from the Kolmogorov -5/3 law. In this study, we propose a data-driven procedure to correct the second-order statistics of LiDAR measurements for spatial averaging. In particular, the blunt model is calibrated over the low-wavenumber portion of the velocity spectrum (which is considered to be unaffected by the smoothing process) and used to quantify the ratio of missing energy over the whole spectral bandwidth. A low-pass filter is tuned on the energy ratio and used to retrieve the spectral scaling in the inertial sub-range. This procedure has been successfully assessed against sonic anemometer data and then used to retrieve the wall-normal distribution of turbulence intensity for two different experimental campaigns. Therefore, the effect of the low-pass filter parameters (order and cutoff wavenumber) has been simulated for flow conditions differing in terms of wind speed, turbulence intensity and height from the ground. As expected, a larger underestimation of the velocity standard deviation has been found increasing the probe length, as well as decreasing the wind speed and wall-normal distance.