Improvement of vertical velocity statistics measured by a Doppler lidar through comparison with sonic anemometer observations

Abstract

Abstract. Since turbulence measurements from Doppler lidars are being increasingly used within wind energy and boundary-layer meteorology, it is important to assess and improve the accuracy of these observations. While turbulent quantities are measured by Doppler lidars in several different ways, the simplest and most frequently used statistic is vertical velocity variance (w 2 ) from zenith stares. However, the competing effects of signal noise and resolution volume limitations, which respectively increase and decrease w 2 , reduce the accuracy of these measurements. Herein, an established method that utilises the autocovariance of the signal to remove noise is evaluated and its skill in correcting for volume-averaging effects in the calculation of w 2 is also assessed. Additionally, this autocovariance technique is further refined by defining the amount of lag time to use for the most accurate estimates of w 2 . Through comparison of observations from two Doppler lidars and sonic anemometers on a 300 m tower, the autocovariance technique is shown to generally improve estimates of w 2 . After the autocovariance technique is applied, values of w 2 from the Doppler lidars are generally in close agreement (R 2 ≈ 0.95 − 0.98) with those calculated from sonic anemometer measurements.

Wind in Complex Terrain—Lidar Measurements for Evaluation of CFD Simulations

“…In their analysis, the availability was over 90%, which might be a reason for the favorable results. Bonin et al [6] reports that the deviations are apparent for frequencies higher than 0.1 Hz, but are able to obtain better estimates by applying the methods of Lenchow [5]. However, as the measurements in this study are performed in the presence of large-scale recirculation, isotropic turbulence cannot be expected.…”

“…An analysis was carried out to determine how the correlation of the Lidar and sonic anemometer data was affected by filtration of SNR values. Although recent studies [6,13] have shown that the spatial averaging effects of the Lidar can be corrected to some extent, none of these methods were applied. The aim of this study was to verify that the Lidar is sufficiently accurate to validate numerical models in complex terrain.…”

“…Several studies have investigated the ability of Lidar systems to provide accurate one-dimensional turbulence statistics, and methods such as the one described by Lenschow et al [5] can be applied to improve the accuracy of these estimates under the assumption of isotropic turbulence. Bonin et al [6] shows how measurement noise in Lidar data can be treated to improve the turbulence estimates. They investigated the performance of a StreamLine and WindCube Lidar compared to a sonic anemometer, and applied the methods of Lenschow to correct for white noise and limitations of spatiotemporal averaging of the measurements.…”

Characteristics of Water Vapor Turbulence Profiles in Convective Boundary Layers During the Dry and Wet Seasons Over Darwin

“…The authors compared the results with large‐eddy simulations (LESs) and found that atmospheric stability was a key factor for the observed variability in the vertical profiles of higher order moments from one case to another. Bonin et al () studied vertical velocity statistics using Doppler lidars and found the vertical velocity variance from Doppler lidars to be in good agreement with sonic anemometer measurements on a 300‐m tower. Berg, Newsom, and Turner () analyzed 1 year of Doppler lidar measurements of the vertical velocity in the cloud‐free CBL over the SGP site, evaluating how these profiles evolve from sunrise to sunset, the seasonal differences in the CBL evolution, and their sensitivity to wind direction, surface shear stress, degree of instability in the CBL, and wind shear across the top of the CBL.…”

Estudo do jato de baixos níveis em Iperó com a técnica lidar Doppler

“…ximo do vento é considerado a velocidade do JBN (V JBN ) e a altura correspondente é considerada a altura do JBN (H JBN ), conforme ilustra a gura 1. 3.4 Estimativa do perl vertical da turbulência Bonin et al (2016) apresentou as vantagens em usar a componente vertical do vento (w) e sua variância (σ 2 w ) para estimar informações da CLP. Em particular, a comparação de dados do Windcube v2 com dados de um anemômetro sônico apresentou bons resultados, embora, a magnitude da σ 2 w estimada pelo lidar seja inferior ao do anemômetro sônico.…”