scholarly journals A six-beam method to measure turbulence statistics using ground-based wind lidars

2015 ◽  
Vol 8 (2) ◽  
pp. 729-740 ◽  
Author(s):  
A. Sathe ◽  
J. Mann ◽  
N. Vasiljevic ◽  
G. Lea
Keyword(s):  
Radial Velocity ◽  
Wind Field ◽  
Atmospheric Stability ◽  
Random Errors ◽  
Turbulence Statistics ◽  
Beam Method ◽  
Vertical Beam ◽  
Wind Lidar ◽  
Velocity Variances ◽  
Cup Anemometer

Abstract. A so-called six-beam method is proposed to measure atmospheric turbulence using a ground-based wind lidar. This method requires measurement of the radial velocity variances at five equally spaced azimuth angles on the base of a scanning cone and one measurement at the centre of the scanning circle, i.e.using a vertical beam at the same height. The scanning configuration is optimized to minimize the sum of the random errors in the measurement of the second-order moments of the components (u,v, w) of the wind field. We present this method as an alternative to the so-called velocity azimuth display (VAD) method that is routinely used in commercial wind lidars, and which usually results in significant averaging effects of measured turbulence. In the VAD method, the high frequency radial velocity measurements are used instead of their variances. The measurements are performed using a pulsed lidar (WindScanner), and the derived turbulence statistics (using both methods) such as the u and v variances are compared with those obtained from a reference cup anemometer and a wind vane at 89 m height under different atmospheric stabilities. The measurements show that in comparison to the reference cup anemometer, depending on the atmospheric stability and the wind field component, the six-beam method measures between 85 and 101% of the reference turbulence, whereas the VAD method measures between 66 and 87% of the reference turbulence.

scholarly journals A six-beam method to measure turbulence statistics using ground-based wind lidars

2014 ◽  
Vol 7 (10) ◽  
pp. 10327-10359 ◽  
Author(s):  
A. Sathe ◽  
J. Mann ◽  
N. Vasiljevic ◽  
G. Lea
Keyword(s):  
Radial Velocity ◽  
Wind Field ◽  
Atmospheric Stability ◽  
Random Errors ◽  
Turbulence Statistics ◽  
Beam Method ◽  
Vertical Beam ◽  
Wind Lidar ◽  
Velocity Variances ◽  
Cup Anemometer

Abstract. A so-called six-beam method is proposed to measure atmospheric turbulence using a ground-based wind lidar. This method requires measurement of the radial velocity variances at five equally spaced azimuth angles on the base of a scanning cone and one measurement at the center of the scanning circle, i.e.using a vertical beam at the same height. The scanning configuration is optimized to minimize the sum of the random errors in the measurement of the second-order moments of the components (u,v, w) of the wind field. We present this method as an alternative to the so-called velocity azimuth display (VAD) method that is routinely used in commercial wind lidars, and which usually results in significant averaging effects of measured turbulence. In the VAD method, the high frequency radial velocity measurements are used instead of their variances. The measurements are performed using a pulsed lidar (WindScanner), and the derived turbulence statistics (using both methods) such as the u and v variances are compared with those obtained from a reference cup anemometer and a wind vane at 89 m height under different atmospheric stabilities. The measurements show that in comparison to the reference cup anemometer, depending on the atmospheric stability and the wind field component, the six-beam method measures between 85–101% of the reference turbulence, whereas the VAD method measures between 66–87% of the reference turbulence.

scholarly journals Errors in radial velocity variance from Doppler wind lidar

2016 ◽  
Vol 9 (8) ◽  
pp. 4123-4139 ◽  
Author(s):  
H. Wang ◽  
R. J. Barthelmie ◽  
P. Doubrawa ◽  
S. C. Pryor
Keyword(s):  
Radial Velocity ◽  
Autocorrelation Function ◽  
Sampling Rate ◽  
Random Errors ◽  
Turbulence Measurement ◽  
Atmospheric Flows ◽  
Velocity Variance ◽  
Wind Lidar ◽  
Systematic And Random Errors ◽  
Sampling Duration

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. Using both statistically simulated and observed data, this 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. 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 %.

scholarly journals Errors in radial velocity variance from Doppler wind lidar

2016 ◽  
Author(s):  
Hui Wang ◽  
Rebecca J. Barthelmie ◽  
Paula Doubrawa ◽  
Sara C. Pryor
Keyword(s):  
Radial Velocity ◽  
Autocorrelation Function ◽  
Sampling Rate ◽  
Random Errors ◽  
Turbulence Measurement ◽  
Atmospheric Flows ◽  
Velocity Variance ◽  
Wind Lidar ◽  
Systematic And Random Errors ◽  
Sampling Duration

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. Using both statistically simulated and observed data, this 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. For current generation scanning lidars and sampling durations of about 30 minutes and longer during which the stationarity assumption is valid for atmospheric flows the systematic error is negligible but the random error exceeds about 10 %.

Performance Improvement of Rayleigh Wind Lidar and Wind Field Observation in Middle and Upper Atmosphere

2016 ◽  
Vol 43 (7) ◽  
pp. 0710004
Author(s):  
唐磊 Tang Lei ◽  
蒋杉 Jiang Shan ◽  
李梓霂 Li Zimu ◽  
郑俊 Zheng Jun ◽  
赵若灿 Zhao Ruocan ◽  
...  
Keyword(s):  
Performance Improvement ◽  
Field Observation ◽  
Wind Field ◽  
Upper Atmosphere ◽  
Wind Lidar

scholarly journals Better turbulence spectra from velocity–azimuth display scanning wind lidar

2019 ◽  
Vol 12 (3) ◽  
pp. 1871-1888 ◽  
Author(s):  
Felix Kelberlau ◽  
Jakob Mann
Keyword(s):  
Data Processing ◽  
Resonance Effect ◽  
Measurement Data ◽  
Cross Contamination ◽  
Raw Data ◽  
Combined Use ◽  
Beam Method ◽  
Wind Lidar ◽  
Velocity Spectra ◽  
Methods Numerical

Abstract. Turbulent velocity spectra derived from velocity–azimuth display (VAD) scanning wind lidars deviate from spectra derived from one-point measurements due to averaging effects and cross-contamination among the velocity components. This work presents two novel methods for minimizing these effects through advanced raw data processing. The squeezing method is based on the assumption of frozen turbulence and introduces a time delay into the raw data processing in order to reduce cross-contamination. The two-beam method uses only certain laser beams in the reconstruction of wind vector components to overcome averaging along the measurement circle. Models are developed for conventional VAD scanning and for both new data processing methods to predict the spectra and identify systematic differences between the methods. Numerical modeling and comparison with measurement data were both used to assess the performance of the methods. We found that the squeezing method reduces cross-contamination by eliminating the resonance effect caused by the longitudinal separation of measurement points and also considerably reduces the averaging along the measurement circle. The two-beam method eliminates this averaging effect completely. The combined use of the squeezing and two-beam methods substantially improves the ability of VAD scanning wind lidars to measure in-wind (u) and vertical (w) fluctuations.

scholarly journals Cloud-Resolving 4D-Var Assimilation of Doppler Wind Lidar Data on a Meso-Gamma-Scale Convective System

2014 ◽  
Vol 142 (12) ◽  
pp. 4484-4498 ◽  
Author(s):  
Takuya Kawabata ◽  
Hironori Iwai ◽  
Hiromu Seko ◽  
Yoshinori Shoji ◽  
Kazuo Saito ◽  
...  
Keyword(s):  
Water Vapor ◽  
Radial Velocity ◽  
Inversion Layer ◽  
Rainfall Event ◽  
Japan Meteorological Agency ◽  
Heavy Rainfall Event ◽  
Convective System ◽  
Vapor Flux ◽  
Wind Lidar ◽  
Doppler Wind Lidar

Abstract The authors evaluated the effects of assimilating three-dimensional Doppler wind lidar (DWL) data on the forecast of the heavy rainfall event of 5 July 2010 in Japan, produced by an isolated mesoscale convective system (MCS) at a meso-gamma scale in a system consisting of only warm rain clouds. Several impact experiments using the nonhydrostatic four-dimensional variational data assimilation system (NHM-4DVAR) and the Japan Meteorological Agency nonhydrostatic model with a 2-km horizontal grid spacing were conducted in which 1) no observations were assimilated (NODA), 2) radar reflectivity and radial velocity determined by Doppler radar and precipitable water vapor determined by GPS satellite observations were assimilated (CTL), and 3) radial velocity determined by DWL were added to the CTL experiment (LDR) and five data denial and two observational error sensitivity experiments. Although both NODA and CTL simulated an MCS, only LDR captured the intensity, location, and horizontal scale of the observed MCS. Assimilating DWL data improved the wind direction and speed of low-level airflows, thus improving the accuracy of the simulated water vapor flux. The examination of the impacts of specific assimilations and assigned observation errors showed that assimilation of all data types is important for forecasting intense MCSs. The investigation of the MCS structure showed that large amounts of water vapor were supplied to the rainfall event by southerly flow. A midlevel inversion layer led to the production of exclusively liquid water particles in the MCS, and in combination with the humid airflow into the MCS, this inversion layer may be another important factor in its development.

scholarly journals Wind Turbulence Statistics of the Atmospheric Inertial Sublayer under Near-Neutral Conditions

Atmosphere ◽  
2020 ◽  
Vol 11 (10) ◽  
pp. 1087
Author(s):  
Eslam Reda Lotfy ◽  
Zambri Harun
Keyword(s):  
Boundary Layer ◽  
Atmospheric Stability ◽  
Turbulent Velocity ◽  
Stability Conditions ◽  
Mean Velocity ◽  
Law Of The Wall ◽  
Turbulent Statistics ◽  
The Mean ◽  
The Law ◽  
Velocity Variances

The inertial sublayer comprises a considerable and critical portion of the turbulent atmospheric boundary layer. The mean windward velocity profile is described comprehensively by the Monin–Obukhov similarity theory, which is equivalent to the logarithmic law of the wall in the wind tunnel boundary layer. Similar logarithmic relations have been recently proposed to correlate turbulent velocity variances with height based on Townsend’s attached-eddy theory. The theory is particularly valid for high Reynolds-number flows, for example, atmospheric flow. However, the correlations have not been thoroughly examined, and a well-established model cannot be reached for all turbulent variances similar to the law of the wall of the mean-velocity. Moreover, the effect of atmospheric thermal condition on Townsend’s model has not been determined. In this research, we examined a dataset of free wind flow under a near-neutral range of atmospheric stability conditions. The results of the mean velocity reproduce the law of the wall with a slope of 2.45 and intercept of −13.5. The turbulent velocity variances were fitted by logarithmic profiles consistent with those in the literature. The windward and crosswind velocity variances obtained the average slopes of −1.3 and −1.7, respectively. The slopes and intercepts generally increased away from the neutral state. Meanwhile, the vertical velocity and temperature variances reached the ground-level values of 1.6 and 7.8, respectively, under the neutral condition. The authors expect this article to be a groundwork for a general model on the vertical profiles of turbulent statistics under all atmospheric stability conditions.

scholarly journals Surface layer similarity in the nocturnal boundary layer: the application of Hilbert-Huang transform

2010 ◽  
Vol 7 (4) ◽  
pp. 1271-1278 ◽  
Author(s):  
J. Hong ◽  
J. Kim ◽  
H. Ishikawa ◽  
Y. Ma
Keyword(s):  
Boundary Layer ◽  
Surface Layer ◽  
Turbulent Flows ◽  
Atmospheric Stability ◽  
Complex Environments ◽  
Mathematical Technique ◽  
Turbulence Statistics ◽  
Hilbert Huang Transform ◽  
Stable Surface Layer ◽  
Energy And Momentum

Abstract. Turbulence statistics such as flux-variance relationship are critical information in measuring and modeling ecosystem exchanges of carbon, water, energy, and momentum at the biosphere-atmosphere interface. Using a recently proposed mathematical technique, the Hilbert-Huang transform (HHT), this study highlights its possibility to quantify impacts of non-turbulent flows on turbulence statistics in the stable surface layer. The HHT is suitable for the analysis of non-stationary and intermittent data and thus very useful for better understanding the interplay of the surface layer similarity with complex nocturnal environment. Our analysis showed that the HHT can successfully sift non-turbulent components and be used as a tool to estimate the relationships between turbulence statistics and atmospheric stability in complex environments such as nocturnal stable boundary layer.

The Change of Aerodynamic Parameters over Beijing Urban Area during 1991-2018

2020 ◽  
Author(s):  
Xiaoman Liu
Keyword(s):  
Wind Speed ◽  
Urban Area ◽  
Wind Direction ◽  
Wind Field ◽  
Atmospheric Stability ◽  
Meteorological Condition ◽  
Field Structure ◽  
Average Height ◽  
Growth Trend ◽  
Aerodynamic Parameters

<p>       Higher and denser building groups are the most concentrated reflection of urbanization on the underlying surface reconstruction. With the continuous city expanding, urban wind field structure was changed, also the aerodynamic parameters dependent on. Based on observational data (slow-response) collected at 15 levels on Beijing 325m meteorological tower from 1991-2018, time and vertical trends of atmospheric stability, wind direction, wind speed, aerodynamic parameters were analyzed. Through Sen's slope, Mann-Kendall trend test and mutation analysis, we believe that urbanization has made a significant influence on local meteorological condition, and all the above variables mutated around the year of 1999. Before 1999, the proportion of neutral and unstable conditions declined with a trend of -0.63% and -2.0% per year respectively, and increased with a trend of +0.08% and +0.06% per year after 1999. As for wind direction, the dominant wind direction below 47m turned from southwest/northwest before 1999 to southeast after 1999, while above 47m remain unchanged as southeast, reflecting that the action range of urban impact is clearly distinguished from that of atmospheric background field. In terms of wind speed, the annual mean value trended to decrease at -0.0019m/s per year, and vertical wind speed trended to increased with height (per meter) at m/s per year, which reflected the continuous enhancement of attenuation effect of complex underlying on the near-ground wind speed. Furthermore, we found that although there was indeed a weaken tendency for wind speed in Beijing urban areas, but near neutral wind speed maintained a growth trend under 140m during 1999-2018. It was possible the deal with urban wake effect, wind field structure mutation or turbulence effect. Aerodynamic parameters  and d have undergone significant changes during the peak stage of urbanization, and tended to develop steadily with a 7-years fluctuations trend after that. In the past 28 years, d has increased from 1.34m in 1991 to 26.19m in 2018, while  has decreased from 2.75m to 1.02m. This is due to the fact that the increase of buildings average height is the result of roughness superposition. If the 7-year fluctuations trend continues, d of Beijing urban area will soon enter the next uplift period, during which the wind speed may increase slightly under nearly neutral conditions, and the cleaning effect on the pollution may be gradually enhanced.</p><p> </p>

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