Boundary-Layer Meteorology

, Volume 149, Issue 2, pp 165–178 | Cite as

Sonic Anemometer as a Small Acoustic Tomography Array

  • Sergey N. Vecherin
  • Vladimir E. Ostashev
  • Christopher W. Fairall
  • D. Keith Wilson
  • Ludovic Bariteau


The spatial resolution of a sonic anemometer is limited by the distance between its transducers, and for studies of small-scale turbulence and theories of turbulence, it is desirable to increase this spatial resolution. We here consider resolution improvements obtainable by treating the sonic anemometer as a small tomography array, with application of appropriate inverse algorithms for the reconstruction of temperature and velocity. A particular modification of the sonic anemometer is considered when the number of its transducers is doubled and the time-dependent stochastic inversion algorithm is used for reconstruction. Numerical simulations of the sonic anemometer and its suggested modification are implemented with the temperature and velocity fields modelled as discrete eddies moving through the sonic’s volume. The tomographic approach is shown to provide better reconstructions of the temperature and velocity fields, with spatial resolution increased by as much as a factor of ten. The spatial resolution depends on the inverse algorithm and also improves by increasing the number of transducers.


Acoustic tomography Small-scale turbulence Sonic anemometer 



This material is based upon work supported in part by the U. S. Army Research Laboratory and the U. S. Army Research Office under contract/grant number W911NF1010415 to Dr. Ostashev. Permission to publish was granted by Director, Cold Regions Research and Engineering Laboratory. We would like to thank two anonymous reviewers whose comments allowed us to improve the paper.


  1. Angelou N, Mann J, Sjoholm M, Courtney M (2012) Direct measurement of the spectral transfer function of a laser based anemometer. Rev Sci Instrum 83:033111, 7 ppGoogle Scholar
  2. Chamecki M, Dias NL (2004) The local isotropy hypothesis and the turbulent kinetic energy dissipation rate in the atmospheric surface layer. Q J R Meteorol Soc 130:2733–2752CrossRefGoogle Scholar
  3. CSAT3 (1998) Three dimensional sonic anemometer instruction manual. Campbell Scientific Inc., Logan, 14 ppGoogle Scholar
  4. Fairall CW, Bradley EF, Hare JE, Grachev AA, Edson JB (2003) Bulk parametrization of air–sea fluxes: updates and verification of the COARE algorithm. J Clim 16:571–591CrossRefGoogle Scholar
  5. Horst TW, Oncley SP (2006) Corrections to inertial-range power spectra measured by CSAT3 and solent sonic anemometers, 1. Path-averaging errors. Boundary-Layer Meteorol 119:375–395CrossRefGoogle Scholar
  6. Kaimal JC, Finnigan JJ (1994) Atmospheric boundary layerflows: their structure and measurement. Oxford University Press, Oxford, 304 ppGoogle Scholar
  7. Ostashev VE (1997) Acoustics in moving inhomogeneous media. E & FN SPON, London 259 ppGoogle Scholar
  8. Ostashev VE, Vecherin SN, Wilson DK, Ziemann A, Goedecke GH (2009) Recent progress in acoustic travel-time tomography of the atmospheric surface layer. Meteorol Zeitschrift 18:125–133CrossRefGoogle Scholar
  9. Sullivan PP, McWilliams JC, Moeng C-H (1994) A subgrid-scale model for large-eddy simulation of planetary boundary-layer flows. Boundary-Layer Meteorol 71:247–276CrossRefGoogle Scholar
  10. Vecherin SN, Ostashev VE, Goedecke GH, Wilson DK, Voronovich AG (2006) Time-dependent stochastic inversion in acoustic travel-time tomography of the atmosphere. J Acoust Soc Am 119:2579–2588CrossRefGoogle Scholar
  11. Vecherin SN, Ostashev VE, Wilson DK, Ziemann A (2008) Time-dependent stochastic inversion in acoustic tomography of the atmosphere with reciprocal transmission. Meas Sci Technol 19:125501–125512Google Scholar
  12. Wilson DK, Thomson DW (1994) Acoustic tomographic monitoring of the atmospheric surface layer. J Atmos Ocean Technol 11:751–769CrossRefGoogle Scholar
  13. Wilson DK, Ostashev VE, Goedecke GH (2009) Quasi-wavelet formulations of turbulence and other random fields with correlated properties. Probab Eng Mech 24:343–357CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  • Sergey N. Vecherin
    • 1
  • Vladimir E. Ostashev
    • 2
  • Christopher W. Fairall
    • 3
  • D. Keith Wilson
    • 1
  • Ludovic Bariteau
    • 2
  1. 1.U.S. Army Engineer Research and Development CenterHanoverUSA
  2. 2.Cooperative Institute for Research in Environmental SciencesUniversity of Colorado at BoulderBoulderUSA
  3. 3.NOAA/Earth System Research LaboratoryBoulderUSA

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