Horizontal-Velocity and Variance Measurements in the Stable Boundary Layer Using Doppler Lidar: Sensitivity to Averaging Procedures

• Published in: Journal of atmospheric and oceanic technology 2008-08, Vol.25 (8), p.1307-1327
• Main Authors: Pichugina, Yelena L, Tucker, Sara C, Banta, Robert M, Brewer, WAlan, Kelley, Neil D, Jonkman, Bonnie J, Newsom, Rob K
• Format: Article
• Language: English
• Subjects: Agreements; Anemometers; Atmospherics; Boundary layer; Boundary layers; Correlation coefficient; Data processing; Doppler; Doppler effect; Kinetic energy; Lidar; Marine; Meteorology; Regression analysis; Remote sensing; Standard deviation; Turbulence; Variance; Wind speed
• ISSN: 0739-0572; 1520-0426
• DOI: 10.1175/2008JTECHA988.1

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 σ2u were computed from HRDL measurements of the line-of-sight (LOS) velocity using a method described by Banta 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−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 σ2u. 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 (τ) were estimated for the four high-wind nights. Time series of τ through each night indicated erratic behavior consistent with the nonstationarity. Histograms of τ showed a mode at 4–5 s, but frequent occurrences of larger τ values, mostly between 10 and 100 s.