Validating precision estimates in horizontal wind measurements from a Doppler lidar

Abstract

Abstract. Results from a recent field campaign are used to assess the accuracy of wind speed and direction precision estimates produced by a Doppler lidar wind retrieval algorithm. The algorithm, which is based on the traditional velocityazimuth-display (VAD) technique, estimates the wind speed and direction measurement precision using standard error propagation techniques, assuming the input data (i.e., radial velocities) to be contaminated by random, zero-mean, errors. For this study, the lidar was configured to execute an 8-beam plan-position-indicator (PPI) scan once every 12 min during the 6-week deployment period. Several wind retrieval trials were conducted using different schemes for estimating the precision in the radial velocity measurements. The resulting wind speed and direction precision estimates were compared to differences in wind speed and direction between the VAD algorithm and sonic anemometer measurements taken on a nearby 300 m tower.All trials produced qualitatively similar wind fields with negligible bias but substantially different wind speed and direction precision fields. The most accurate wind speed and direction precisions were obtained when the radial velocity precision was determined by direct calculation of radial velocity standard deviation along each pointing direction and range gate of the PPI scan. By contrast, when the instrumental measurement precision is assumed to be the only contribution to the radial velocity precision, the retrievals resulted in wind speed and direction precisions that were biased far too low and were poor indicators of data quality.

Atmospheric Boundary Layer Classification With Doppler Lidar

“…Horizontal winds are required to estimate the length scales L and L 1 , and these may be provided by the instrument itself, if scanning capable, or by supplementary sources such as radiosonde, wind profiler, or weather forecast models (O'Connor et al, ). Low SNR or highly turbulent conditions can impact the Doppler lidar wind retrievals (Newsom et al, ; Päschke et al, ), in which case, when Halo lidar horizontal winds are not available, horizontal winds provided by, for example, the Global Data Assimilation System, GDAS (GDAS, ) can be used instead.…”

LiDAR measurements for an onshore wind farm: Wake variability for different incoming wind speeds and atmospheric stability regimes

“…For each cluster of the LiDAR data, ensemble statistics are calculated with the Barnes scheme . Grid characteristics for applications of the Barnes scheme should be defined as a trade‐off between spatial resolution of the available LiDAR data and spatial variability of the wake velocity field.…”

“…Sections and report in detail the procedure for the post‐processing and clustering, respectively, of single‐wake LiDAR scans. In Section , ensemble statistics of plan position indicator (PPI) scans belonging to the same cluster are retrieved through the Barnes scheme . In Section , average and standard deviation of the wake velocity field are investigated for different hub‐height wind speed and atmospheric stability regimes.…”

Response of the Land‐Atmosphere System Over North‐Central Oklahoma During the 2017 Eclipse

“…Note that the relative accuracy of the two types of measurement systems is within 20% for most conditions (Fritschen et al, ). Scanning Doppler lidars (DLIDs) at all three sites are used to measure horizontal winds (every 15 min at E32 and E39) using a velocity‐azimuth display method (Newsom et al, ) and vertical motions at 1 s resolution otherwise. The vertical motion data sets were processed to provide profiles of their variance and skewness (Berg, Newsom, & Turner, ), thereby providing a description of the turbulent motions in the PBL.…”