Doppler Lidar Measurements of Turbulent Structure Function over an Urban Area

Davies, F.; Collier, C. G.; Pearson, Guy N.; Bozier, K. E.

doi:10.1175/1520-0426(2004)021<0753:dlmots>2.0.co;2

Cited by 47 publications

(45 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…One method involves velocity structure functions, which can be calculated longitudinally along the beam or transversely across azimuths in sector plan position indicator (PPI) scans (e.g. Eberhard et al, 1989;Frehlich and Cornman, 2002;Krishnamurthy et al, 2011;Davies et al, 2004). Values of the horizontal wind variance (σ 2 u and σ 2 v ) can be calculated from range height indicator scans, by first separating the measured velocity into height bins and calculating the variance in velocity at each height (e.g.…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2016

View full text Add to dashboard Cite

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.

show abstract

Section: Introductionmentioning

confidence: 99%

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

et al. 2016

View full text Add to dashboard Cite

show abstract

“…Using the VAD technique Bozier et al (2004) compared the average horizontal wind velocity difference and average standard deviation between a CO 2 Doppler lidar and tethered balloon borne turbulence probe measurements at a site in Eastern England as shown in Table 3. The in situ sensor captures a higher frequency turbulence component in the wind velocity data due to the higher measurement rate, 4 Hz, compared to the lidar data sampling rate of 0.1 Hz.…”

Section: Single Instrument Measurementsmentioning

confidence: 99%

Synergy Between Doppler Radar and Lidar for Atmospheric Boundary Layer Research

Collier¹

2012

Doppler Radar Observations - Weather Radar, Wind Profiler, Ionospheric Radar, and Other Advanced Applications

View full text Add to dashboard Cite

“…A spectrum of the velocity time series can then determine how much energy is contained in the turbulent eddies at different temporal and spatial scales. The LiDAR data are ideal for spectral analysis as it has high resolution in both time and space (Davies et al, 2004). A spectrum of energy against frequency is shown in Figure 9.…”

Section: Turbulent Eddies and Tropical Convectionmentioning

confidence: 99%