scholarly journals Characteristics of atmospheric turbulence in terms of background atmospheric parameters inferred using MST radar at Gadanki (13.5°N, 79.2°E)

Radio Science ◽  
2010 ◽  
Vol 45 (4) ◽  
pp. n/a-n/a ◽  
Author(s):  
Siddarth Shankar Das ◽  
A. K. Ghosh ◽  
K. Satheesan ◽  
A. R. Jain ◽  
K. N. Uma
Keyword(s):  
Atmospheric Turbulence ◽  
Atmospheric Parameters ◽  
Mst Radar

scholarly journals Measurements of atmospheric turbulence with the dual-beamwidth method using the MST radar at Gadanki, India

2004 ◽  
Vol 22 (9) ◽  
pp. 3291-3297 ◽  
Author(s):  
G. D. Nastrom ◽  
P. B. Rao ◽  
V. Sivakumar
Keyword(s):  
Kinetic Energy ◽  
Atmospheric Turbulence ◽  
Traditional Method ◽  
Spectral Width ◽  
Effective Width ◽  
Prevailing Wind ◽  
Diurnal Range ◽  
Mst Radar ◽  
Diurnal Period ◽  
Beam Broadening

Abstract. A brief experiment was conducted during 24-29 April and 9-10 May 2002, using the MST radar at Gadanki, India, to test the dual-beamwidth method of estimating the turbulence kinetic energy (TKE). Because the beamwidth can be modified on only one polarization at a time at Gadanki, an elliptical beam was used with a modified dual-beamwidth analysis. Estimates of the TKE from the dual-beamwidth method and the traditional method are very similar in regions of light winds (<~10ms-1). In regions of stronger wind (>~15ms-1) the traditional method often gives TKE<0 because the beam-broadening correction is greater than the observed spectral width. It is suggested that some of the problems with the traditional method are due to the uncertainty in the effective width of the radar beam. In all regions the modified dual-beamwidth method gives TKE>0 on the beam parallel to the prevailing wind; on this beam the estimates depend only on the ratio of the beamwidths, which is presumably well-known, and the observed spectral widths. The values of TKE from the dual-beamwidth method are approximately constant with height at 0.2m2s-2 from about 5 to 7.5km during the afternoon during both April and May (all April observations were made between 9:00 and 17:00 local time), and then decrease rapidly to about 0.02m2s-2 by about 9km. The data from May extend over one full diurnal period and the diurnal range of TKE during this period is found to be about 5dB below about 12km and from about 15 to 19km, near the tropopause, with maximum values during local afternoon.

scholarly journals Turbulent diffusivity in the free atmosphere inferred from MST radar measurements: a review

2004 ◽  
Vol 22 (11) ◽  
pp. 3869-3887 ◽  
Author(s):  
R. Wilson
Keyword(s):  
Atmospheric Turbulence ◽  
Small Scale ◽  
Doppler Width ◽  
Free Atmosphere ◽  
Statistical Parameters ◽  
Actual Impact ◽  
Dissipation Rates ◽  
Mst Radar ◽  
Radar Measurements ◽  
Scale Turbulence

Abstract. The actual impact on vertical transport of small-scale turbulence in the free atmosphere is still a debated issue. Numerous estimates of an eddy diffusivity exist, clearly showing a lack of consensus. MST radars were, and continue to be, very useful for studying atmospheric turbulence, as radar measurements allow one to estimate the dissipation rates of energy (kinetic and potential) associated with turbulent events. The two commonly used methods for estimating the dissipation rates, from the backscattered power and from the Doppler width, are discussed. The inference methods of a local diffusivity (local meaning here "within" the turbulent patch) by using the dissipation rates are reviewed, with some of the uncertainty causes being stressed. Climatological results of turbulence diffusivity inferred from radar measurements are reviewed and compared. As revealed by high resolution MST radar measurements, atmospheric turbulence is intermittent in space and time. Recent theoretical works suggest that the effective diffusivity of such a patchy turbulence is related to statistical parameters describing the morphology of turbulent events: filling factor, lifetime and height of the patches. It thus appears that a statistical description of the turbulent patches' characteristics is required in order to evaluate and parameterize the actual impact of small-scale turbulence on transport of energy and materials. Clearly, MST radars could be an essential tool in that matter.

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.

Estimating Atmospheric Turbulence Parameters from the Envelopes of Radio Acoustic Signals

2001 ◽  
Vol 55 (8) ◽  
pp. 5
Author(s):  
V. M. Kartashov ◽  
V. A. Petrov ◽  
Ye. G. Proshkin ◽  
G. I. Sidorov
Keyword(s):  
Atmospheric Turbulence ◽  
Acoustic Signals ◽  
Turbulence Parameters

Numerical study of wake vortex decay and descent in homogeneous atmospheric turbulence

AIAA Journal ◽  
2000 ◽  
Vol 38 ◽  
pp. 643-656 ◽  
Author(s):  
Jongil Han ◽  
Yuh-Lang Lin ◽  
S. P. Arya ◽  
Fred H. Proctor
Keyword(s):  
Atmospheric Turbulence ◽  
Numerical Study ◽  
Wake Vortex
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