Coherent CO2 lidars for measuring wind velocity and atmospheric turbulence

1994 ◽  
Vol 33 (10) ◽  
pp. 3206 ◽  
Author(s):  
Anatoly A. Kormakov
Keyword(s):  
Atmospheric Turbulence ◽  
Wind Velocity

Boundary Layer Wind Characteristics over Urban Area

2014 ◽  
Vol 501-504 ◽  
pp. 2297-2300
Author(s):  
Lun Hai Zhi
Keyword(s):  
Boundary Layer ◽  
Wind Speed ◽  
Urban Area ◽  
Atmospheric Turbulence ◽  
Wind Velocity ◽  
Three Dimensional ◽  
Tall Buildings ◽  
Gust Factor ◽  
Mean Wind Speed ◽  
Wind Characteristics

This paper presents statistical analysis results of wind speed and atmospheric turbulence data measured from a meteorological station in Beijing and is primarily intended to provide useful information on boundary layer wind characteristics for wind-resistant design of tall buildings and high-rise structures. Wind velocity data in longitudinal, lateral and vertical directions, which were recorded from an ultrasonic anemometer during windstorms, are analyzed and discussed. Atmospheric turbulence information such as turbulence intensity, gust factor, turbulence integral length scale and power spectral densities of the three-dimensional fluctuating wind velocity are presented and used to evaluate the adequacy of existing theoretical and empirical models. The objective of this study is to investigate the profiles of mean wind speed and atmospheric turbulence characteristics over a typical urban area.

scholarly journals Using Doppler lidar systems to detect atmospheric turbulence in Iceland

2019 ◽  
Author(s):  
Shu Yang ◽  
Guðrún Nína Petersen ◽  
Sibylle von Löwis ◽  
Jana Preißler ◽  
David Christian Finger
Keyword(s):  
Atmospheric Turbulence ◽  
Wind Velocity ◽  
Turbulence Intensity ◽  
Weather Conditions ◽  
Wind Fields ◽  
Air Traffic Controllers ◽  
Noise Filter ◽  
Filter Methods ◽  
Kolmogorov Theory ◽  
Lidar Observations

Abstract. The temporal and spatial scale of atmospheric turbulence is very dynamic, requiring an adequate method to detect and monitor turbulence with high resolution. Doppler Light Detection and Ranging (lidar) systems have been used widely to observe and monitor wind velocity and atmospheric turbulence profiles. Lidar systems can provide continuous information about wind fields using the Doppler effect from emitted light signals. In this study, we use a Leosphere Windcube 200S lidar system stationed in Reykjavik, Iceland, to evaluate turbulence intensity by estimating eddy dissipation rate (EDR). For this purpose, we retrieved radial wind velocity observations from velocity azimuth display (VAD) scans to compute EDR based on the Kolmogorov theory. We compared different noise filter methods, scan strategies and calculation approaches during different selected weather conditions to assess the accuracy of our EDR estimations. The results reveal that the lidar observations can detect and quantify atmospheric turbulence with high spatial and temporal resolution, our algorithm can retrieve EDR and indicate the turbulence intensity. These results suggest that lidar observation can be of high importance for potential end-user, e.g. air traffic controllers at the local airport. The work is an important step towards enhanced aviation safety in a subpolar climate characterized by severe wind turbulence.

Flow distortion investigation of wind velocity perturbations for two ocean meteorological platforms

2012 ◽  
Author(s):  
Marc Emond ◽  
Doug Vandemark ◽  
James Forsythe ◽  
Albert J. Plueddemann ◽  
J. Thomas Farrar
Keyword(s):  
Wind Velocity ◽  
Flow Distortion

Prediction of Atmospheric Turbulence Characteristics for Surface Boundary Layer using Empirical Spectral Methods

2020 ◽  
Author(s):  
Yagya Dutta Dwivedi ◽  
Vasishta Bhargava Nukala ◽  
Satya Prasad Maddula ◽  
Kiran Nair
Keyword(s):  
Boundary Layer ◽  
Time Series ◽  
Surface Roughness ◽  
Wind Speed ◽  
Atmospheric Turbulence ◽  
Surface Boundary ◽  
Low Frequencies ◽  
Surface Boundary Layer ◽  
Power Spectral ◽  
Mean Wind Speed

Abstract Atmospheric turbulence is an unsteady phenomenon found in nature and plays significance role in predicting natural events and life prediction of structures. In this work, turbulence in surface boundary layer has been studied through empirical methods. Computer simulation of Von Karman, Kaimal methods were evaluated for different surface roughness and for low (1%), medium (10%) and high (50%) turbulence intensities. Instantaneous values of one minute time series for longitudinal turbulent wind at mean wind speed of 12 m/s using both spectra showed strong correlation in validation trends. Influence of integral length scales on turbulence kinetic energy production at different heights is illustrated. Time series for mean wind speed of 12 m/s with surface roughness value of 0.05 m have shown that variance for longitudinal, lateral and vertical velocity components were different and found to be anisotropic. Wind speed power spectral density from Davenport and Simiu profiles have also been calculated at surface roughness of 0.05 m and compared with k−1 and k−3 slopes for Kolmogorov k−5/3 law in inertial sub-range and k−7 in viscous dissipation range. At high frequencies, logarithmic slope of Kolmogorov −5/3rd law agreed well with Davenport, Harris, Simiu and Solari spectra than at low frequencies.

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