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Title: Errors in radial velocity variance from Doppler wind lidar

Abstract

A high-fidelity lidar turbulence measurement technique relies on accurate estimates of radial velocity variance that are subject to both systematic and random errors determined by the autocorrelation function of radial velocity, the sampling rate, and the sampling duration. Our paper quantifies the effect of the volumetric averaging in lidar radial velocity measurements on the autocorrelation function and the dependence of the systematic and random errors on the sampling duration, using both statistically simulated and observed data. For current-generation scanning lidars and sampling durations of about 30 min and longer, during which the stationarity assumption is valid for atmospheric flows, the systematic error is negligible but the random error exceeds about 10%.

Authors:
ORCiD logo [1]; ORCiD logo [1];  [1]; ORCiD logo [2]
  1. Cornell Univ., Ithaca, NY (United States). Sibley School of Mechanical and Aerospace Engineering
  2. Cornell Univ., Ithaca, NY (United States). Dept. of Earth and Atmospheric Sciences
Publication Date:
Research Org.:
Cornell Univ., Ithaca, NY (United States)
Sponsoring Org.:
USDOE Office of Science (SC)
OSTI Identifier:
1363864
Grant/Contract Number:
EE0005379
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Atmospheric Measurement Techniques (Online)
Additional Journal Information:
Journal Name: Atmospheric Measurement Techniques (Online); Journal Volume: 9; Journal Issue: 8; Journal ID: ISSN 1867-8548
Publisher:
European Geosciences Union
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES

Citation Formats

Wang, H., Barthelmie, R. J., Doubrawa, P., and Pryor, S. C.. Errors in radial velocity variance from Doppler wind lidar. United States: N. p., 2016. Web. doi:10.5194/amt-9-4123-2016.
Wang, H., Barthelmie, R. J., Doubrawa, P., & Pryor, S. C.. Errors in radial velocity variance from Doppler wind lidar. United States. doi:10.5194/amt-9-4123-2016.
Wang, H., Barthelmie, R. J., Doubrawa, P., and Pryor, S. C.. 2016. "Errors in radial velocity variance from Doppler wind lidar". United States. doi:10.5194/amt-9-4123-2016. https://www.osti.gov/servlets/purl/1363864.
@article{osti_1363864,
title = {Errors in radial velocity variance from Doppler wind lidar},
author = {Wang, H. and Barthelmie, R. J. and Doubrawa, P. and Pryor, S. C.},
abstractNote = {A high-fidelity lidar turbulence measurement technique relies on accurate estimates of radial velocity variance that are subject to both systematic and random errors determined by the autocorrelation function of radial velocity, the sampling rate, and the sampling duration. Our paper quantifies the effect of the volumetric averaging in lidar radial velocity measurements on the autocorrelation function and the dependence of the systematic and random errors on the sampling duration, using both statistically simulated and observed data. For current-generation scanning lidars and sampling durations of about 30 min and longer, during which the stationarity assumption is valid for atmospheric flows, the systematic error is negligible but the random error exceeds about 10%.},
doi = {10.5194/amt-9-4123-2016},
journal = {Atmospheric Measurement Techniques (Online)},
number = 8,
volume = 9,
place = {United States},
year = 2016,
month = 8
}

Journal Article:
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  • Quantitative data on turbulence variables aloft--above the region of the atmosphere conveniently measured from towers--have been an important but difficult measurement need for advancing understanding and modeling of the stable boundary layer (SBL). Vertical profiles of streamwise velocity variances obtained from NOAA's high-resolution Doppler lidar (HRDL), which have been shown to be approximately equal to turbulence kinetic energy (TKE) for stable conditions, are a measure of the turbulence in the SBL. In the present study, the mean horizontal wind component U and variance {sigma}2u were computed from HRDL measurements of the line-of-sight (LOS) velocity using a method described by Bantamore » et al., which uses an elevation (vertical slice) scanning technique. The method was tested on datasets obtained during the Lamar Low-Level Jet Project (LLLJP) carried out in early September 2003, near the town of Lamar in southeastern Colorado. This paper compares U with mean wind speed obtained from sodar and sonic anemometer measurements. The results for the mean U and mean wind speed measured by sodar and in situ instruments for all nights of LLLJP show high correlation (0.71-0.97), independent of sampling strategies and averaging procedures, and correlation coefficients consistently >0.9 for four high-wind nights, when the low-level jet speeds exceeded 15 m s{sup -1} at some time during the night. Comparison of estimates of variance, on the other hand, proved sensitive to both the spatial and temporal averaging parameters. Several series of averaging tests are described, to find the best correlation between TKE calculated from sonic anemometer data at several tower levels and lidar measurements of horizontal-velocity variance {sigma}{sup 2}{sub u}. Because of the nonstationarity of the SBL data, the best results were obtained when the velocity data were first averaged over intervals of 1 min, and then further averaged over 3-15 consecutive 1-min intervals, with best results for the 10- and 15-min averaging periods. For these cases, correlation coefficients exceeded 0.9. As a part of the analysis, Eulerian integral time scales ({tau}) were estimated for the four high-wind nights. Time series of {tau} through each night indicated erratic behavior consistent with the nonstationarity. Histograms of {tau} showed a mode at 4-5 s, but frequent occurrences of larger {tau} values, mostly between 10 and 100 s.« less
  • Quantitative data on turbulence variables aloft--above the region of the atmosphere conveniently measured from towers--has been an important but difficult measurement need for advancing understanding and modeling of the stable boundary layer (SBL). Vertical profiles of streamwise velocity variances obtained from NOAA’s High Resolution Doppler Lidar (HRDL), which have been shown to be numerically equivalent to turbulence kinetic energy (TKE) for stable conditions, are a measure of the turbulence in the SBL. In the present study, the mean horizontal wind component U and variance σu2 were computed from HRDL measurements of the line-of-sight (LOS) velocity using a technique described inmore » Banta, et al. (2002). The technique was tested on datasets obtained during the Lamar Low-Level Jet Project (LLLJP) carried out in early September 2003, near the town of Lamar in southeastern Colorado. This paper compares U with mean wind speed obtained from sodar and sonic anemometer measurements. It then describes several series of averaging tests that produced the best correlation between TKE calculated from sonic anemometer data at several tower levels and lidar measurements of horizontal velocity variance σu2. The results show high correlation (0.71-0.97) of the mean U and average wind speed measured by sodar and in-situ instruments, independent of sampling strategies and averaging procedures. Comparison of estimates of variance, on the other hand, proved sensitive to both the spatial and temporal averaging techniques.« less
  • When defining optimal scanning geometries for scanning lidars for wind energy applications, we found that it is still an active field of research. Our paper evaluates uncertainties associated with arc scan geometries and presents recommendations regarding optimal configurations in the atmospheric boundary layer. The analysis is based on arc scan data from a Doppler wind lidar with one elevation angle and seven azimuth angles spanning 30° and focuses on an estimation of 10-min mean wind speed and direction. When flow is horizontally uniform, this approach can provide accurate wind measurements required for wind resource assessments in part because of itsmore » high resampling rate. Retrieved wind velocities at a single range gate exhibit good correlation to data from a sonic anemometer on a nearby meteorological tower, and vertical profiles of horizontal wind speed, though derived from range gates located on a conical surface, match those measured by mast-mounted cup anemometers. Uncertainties in the retrieved wind velocity are related to high turbulent wind fluctuation and an inhomogeneous horizontal wind field. Moreover, the radial velocity variance is found to be a robust measure of the uncertainty of the retrieved wind speed because of its relationship to turbulence properties. It is further shown that the standard error of wind speed estimates can be minimized by increasing the azimuthal range beyond 30° and using five to seven azimuth angles.« less
  • One year of Coherent Doppler Lidar (CDL) data collected at the U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) site in Oklahoma is analyzed to provide profiles of vertical velocity variance, skewness, and kurtosis for cases of cloud-free convective boundary layers. The variance was scaled by the Deardorff convective velocity scale, which was successful when the boundary layer depth was stationary but failed in situations when the layer was changing rapidly. In this study the data are sorted according to time of day, season, wind direction, surface shear stress, degree of instability, and wind shear across the boundary-layer top. Themore » normalized variance was found to have its peak value near a normalized height of 0.25. The magnitude of the variance changes with season, shear stress, and degree of instability, but was not impacted by wind shear across the boundary-layer top. The skewness was largest in the top half of the boundary layer (with the exception of wintertime conditions). The skewness was found to be a function of the season, shear stress, wind shear across the boundary-layer top, with larger amounts of shear leading to smaller values. Like skewness, the vertical profile of kurtosis followed a consistent pattern, with peak values near the boundary-layer top (also with the exception of wintertime data). The altitude of the peak values of kurtosis was found to be lower when there was a large amount of wind shear at the boundary-layer top.« less