Quasi-Wavelet Models for Atmospheric Turbulence

2002 ◽  
Author(s):  
George H. Goedecke ◽  
D. K. Wilson ◽  
Vladimir E. Ostashev ◽  
Harry J. Auvermann
Keyword(s):  
Atmospheric Turbulence

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

A striped pattern of snowfall and snow cover

1993 ◽  
Vol 18 ◽  
pp. 27-32
Author(s):  
Yasuaki Nohguchi ◽  
Takashi Ikarashi ◽  
Osamu Abe ◽  
Atsushi Sato
Keyword(s):  
Snow Cover ◽  
Atmospheric Turbulence ◽  
Layered Structure ◽  
Time Variation ◽  
Vertical Wall ◽  
Striped Pattern

A striped pattern can be seen by spraying ink on a vertical wall of a snow pit to observe the layered structure of a snow cover. This pattern is caused by variations of snowfall in time, particularly pauses in snowfall, and its structure is related to a kind of fractal. In this paper, we consider snowfall and snow cover from a viewpoint of fractals and show that the layered structure of snow cover is a record of fractals on atmospheric-turbulence phenomena through the time variation of snowfall.

A real-time atmospheric turbulence mitigation and super-resolution solution for infrared imaging systems

2012 ◽  
Author(s):  
Douglas R. Droege ◽  
Russell C. Hardie ◽  
Brian S. Allen ◽  
Alexander J. Dapore ◽  
Jon C. Blevins
Keyword(s):  
Real Time ◽  
Atmospheric Turbulence ◽  
Infrared Imaging ◽  
Super Resolution ◽  
Imaging Systems

Interferential seeing monitor, a seeing monitor for atmospheric turbulence studies: calibration with the differential image motion monitor

2020 ◽  
Vol 500 (2) ◽  
pp. 1884-1888
Author(s):  
Mohammed Sabil ◽  
A Habib ◽  
Z Benkhaldoun
Keyword(s):  
Structure Function ◽  
Atmospheric Turbulence ◽  
Wave Structure ◽  
Image Motion ◽  
Phase Fluctuations ◽  
Amplitude Fluctuations ◽  
Focus Plane ◽  
Cross Calibration ◽  
Double Slit ◽  
Good Agreement

ABSTRACT In this work, we aim to calibrate an interferential seeing monitor (ISM), which is a testing instument used at astronomical sites. Its method is based on the study of the diffraction pattern produced by a Young’s double-slit at the focus plane of a telescope. This method allows us to obtain the wave structure function by taking into account both phase and amplitude fluctuations of the light wavefront. A phase seeing εϕ was assigned to phase fluctuations and an amplitude seeing εχ was assigned to amplitude fluctuations (scintillation phenomenon), which allows us to obtain both phase and amplitude fluctuations. The feasibility of the ISM method was demonstrated by numerical simulations presented in a previous work. In this work, we have conducted a cross-calibration campaign of the ISM with a differential image motion monitor (DIMM) over 16 nights at the Oukaimeden and Atlas Golf Marrakech Observatories. The goal of this campaign was to study the reliability of this new method. In this paper, we present the calibration measurements and a comparison between the seeing measured by the ISM (εϕ, εχ) and that obtained by the DIMM (εdimm). These results show good agreement between the phase- eeing εϕ and εdimm.

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