Physical grounds for acoustic remote sensing of the atmospheric boundary layer

Kallistratova, M. A.

doi:10.1007/bfb0009558

Cited by 6 publications

(3 citation statements)

References 38 publications

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“…Reference textbooks on the topic may be found, e.g., Wheelon (2003). In terms of applications, the sound detection and ranging technology remotely senses the atmospheric turbulence on the basis of the large-angle scattering solutions of T61 (e.g., Kallistratova, 1997;Coulter, 1997).…”

Section: Introductionmentioning

confidence: 99%

Unified modeling of turbulence effects on sound propagation

Cheinet

Ehrhardt

Juvé

et al. 2012

The Journal of the Acoustical Society of America

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Many aspects of outdoor sound propagation depend on the scattering effects induced by atmospheric turbulence. Standard analytical and numerical assessments of these effects make an a priori distinction between the scattering effects at large versus small angles. The present study evaluates the ability of a numerical model in overcoming this distinction. The model solves a set of two coupled equations for the sound pressure and vector acoustic velocity, with the finite-difference time domain approach. It is first introduced and evaluated. The numerical predictions are compared to well-known analytical solutions in the case of two-dimensional plane wave propagation through turbulence. They are found to agree in the investigated scenarios. Hence, the finite-difference, time domain solution of the two coupled equations provides a unified, versatile numerical approach to investigating the effects of atmospheric turbulence on sound propagation. The comparison also provides original insights on the applicability and limitations of various methods used to investigate sound propagation through turbulence.

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Section: Introductionmentioning

confidence: 99%

Unified modeling of turbulence effects on sound propagation

Cheinet

Ehrhardt

Juvé

et al. 2012

The Journal of the Acoustical Society of America

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“…The speed of sound is far more sensitive to temperature variations than electromagnetic waves are; for the same temperature variations, the changes in refractive index are 1000 times greater for acoustic waves than for electromagnetic waves (Kallistratova 1997). The speed of sound is far more sensitive to temperature variations than electromagnetic waves are; for the same temperature variations, the changes in refractive index are 1000 times greater for acoustic waves than for electromagnetic waves (Kallistratova 1997).…”

Section: B Beam Locationsmentioning

confidence: 97%

A Time Series Sodar Simulator Based on Large-Eddy Simulation

Wainwright

Stepanian

Chilson

et al. 2014

Journal of Atmospheric and Oceanic Technology

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A sodar simulator capable of producing time series data emulating sodar signals has been developed and tested. The atmospheric fields used to populate the sodar simulator are taken from output of a large-eddy simulation code. The characteristics of the sodar (number and zenith angle of beams, beamwidth, transmit frequency, range resolution, etc.) are defined by the user to allow emulation of existing systems. The range of the reflected acoustic signal is calculated based upon a temperature-dependent speed of sound. Realistic acoustic background noise is simulated using filtered white noise. The raw acoustic time series data are processed using a Fourier transform to yield acoustic Doppler spectra, from which the radial velocities are calculated. The design of the simulator allows for the testing of and comparisons between various signalprocessing techniques and averaging periods. An example case of feeding the sodar simulator with large-eddy simulation data representative of a developing convective boundary layer is presented and discussed.

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“…Research concerning the state of the atmospheric boundary layer involving SODARs (Bradley, 2008;Kalistratova, 1997) has been conducted for over 25 years (Pyka, 1991) at the Department of Climatology and Atmosphere Protection, Wroclaw University. In order to evaluate spatial distributions of parameters describing the ABL, investigations have been carried out in the mobile measurement regime using Mini-SODAR 1DDS (Figure 1).…”

Section: Mobile Sodar Measurementsmentioning

confidence: 99%

Verification of SBL models by mobile SODAR measurements

Netzel

Slopek

Drzeniecka-Osiadacz

2012

IJEP

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Models of atmospheric pollutant transport need information about the structure of the atmospheric boundary layer (ABL). The most important characteristics for such applications are the parameterisation of the stable boundary layer (SBL) and the mixing layer height (MLH). Recently, many different schemes have been employed to calculate the SBL height, but there are many problems with applying these models in environmental studies. Remote sensing of the atmospheric boundary layer using an acoustic sounder provides an opportunity to assess the mixing height based on analysis of SODAR echo strength. During the night, with a steady state of the stable boundary layer, the mixing height is associated with the range of the inversion layer. In the present study, an attempt is made to assess the stable boundary layer height over an urban area based on seven different schemes. Furthermore, the relationship between the mixing height obtained from SODAR measurements and that obtained from models is examined. Data gathered during field experiments in Wroclaw and Cracow are employed for the evaluation of these models.

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Physical grounds for acoustic remote sensing of the atmospheric boundary layer

Cited by 6 publications

References 38 publications

Unified modeling of turbulence effects on sound propagation

Unified modeling of turbulence effects on sound propagation

A Time Series Sodar Simulator Based on Large-Eddy Simulation

Verification of SBL models by mobile SODAR measurements

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