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  • Antoniou, I., Jørgensen H. E. , von Hünerbein S. , Bradley S. G. , Kindler D. , Warmbier G. , and de Noord M. , 2004: The Profiler Intercomparison Experiment (PIE). Proc. European Wind Energy Conf. and Exhibition, London, United Kingdom, EWEA, CD-ROM.

  • Behrens, P., Bradley S. , and Wiens T. , 2010: A multisodar approach to wind profiling. J. Atmos. Oceanic Technol., 27, 1165–1174.

  • Behrens, P., O'Sullivan J. , Archer R. , and Bradley S. , 2012: Underestimation of mono-static sodar measurements in complex terrain. Bound.-Layer Meteor., 143, 97–106.

    • Search Google Scholar
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  • Bingol, F., Mann J. , and Foussekis D. , 2009: Conically scanning lidar error in complex terrain. Meteor. Z., 18, 189–195.

  • Blanc-Benon, P., Juvé D. , and Comte-Bellot G. , 1991: Occurrence of caustics for high-frequency acoustic waves propagating through turbulent fields. Theor. Comput. Fluid Dyn., 2, 271–278.

    • Search Google Scholar
    • Export Citation

  • Bradley, S. G., 2007: Atmospheric Acoustic Remote Sensing. CRC Press/Taylor and Francis Group, 328 pp.

  • Bradley, S. G., 2012: A simple model for correcting sodar and lidar errors in complex terrain. J. Atmos. Oceanic Technol., 29, 1717–1722.

    • Search Google Scholar
    • Export Citation

  • Bradley, S. G., Perrott Y. , and Oldroyd A. , 2012: Corrections for wind-speed errors from sodar and lidar in complex terrain. Bound.-Layer Meteor., 143, 37–48.

    • Search Google Scholar
    • Export Citation

  • Careta, A., Sagues F. , and Sancho J. M. , 1993: Stochastic generation of homogeneous isotropic turbulence with well-defined spectra. Phys. Rev., 48E, 2279–2287.

    • Search Google Scholar
    • Export Citation

  • Chu, C. R., Parlange M. B. , Katul G. G. , and Albertson J. D. , 1996: Probability density functions of turbulent velocity and temperature in the atmospheric surface layer. Water Resour. Res., 32, 1681–1688.

    • Search Google Scholar
    • Export Citation

  • Contini, D., Mastrantonio G. , Viola A. , and Argentini S. , 2004: Mean vertical motions in the PBL measured by Doppler sodar: Accuracy, ambiguities, possible improvements. J. Atmos. Oceanic Technol., 21, 1532–1544.

    • Search Google Scholar
    • Export Citation

  • Contini, D., Donateo A. , and Belosi F. , 2006: Accuracy of measurements of turbulent phenomena in the surface layer with an ultrasonic anemometer. J. Atmos. Oceanic Technol., 23, 785–801.

    • Search Google Scholar
    • Export Citation

  • Contini, D., Grasso F. M. , Mastrantonio G. , Viola A. P. , and Martano P. , 2007: Performances of a modular PC-based multi-tone sodar system in measuring vertical wind velocity. Meteor. Z., 16, 357–365.

    • Search Google Scholar
    • Export Citation

  • Ewert, R., 2008: Broadband slat noise prediction based on CAA and stochastic: Sound sources from a fast random particle-mesh (RPM) method. Comput. Fluids, 37, 369–387.

    • Search Google Scholar
    • Export Citation

  • Kristensen, K., 1999: The perennial cup anemometer. Wind Energy, 2, 59–75.

  • Mastrantonio, G., and Fiocco G. , 1982: Accuracy of wind velocity determinations with Doppler sodar. J. Appl. Meteor., 21, 820–830.

    • Search Google Scholar
    • Export Citation

  • Mikkelsen, T., and Bradley S. G. , 2011: Lidar remote sensing. Int. Sustainable Energy Rev., 5, 19–23.

  • Moore, K. E., and Bailey B. H. , 2006: Maximizing the accuracy of sodar measurements for wind resource assessment. AWS Truewind Research Note 2, 10 pp. [Available online at http://www.awstruepower.com/2006/08/maximizing-the-accuracy-of-sodar-measurements-for-wind-resource-assessment/.]

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Editorial Type:
Article
Article Type:
Research Article

Aspects of the Correlation between Sodar and Mast Instrument Winds

Stuart Bradley1
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  • 1 Physics Department, University of Auckland, Auckland, New Zealand
Print Publication:
01 Oct 2013
Collections:
16th International Symposium for the Advancement of Boundary-Layer Remote Sensing (ISARS 2012)
DOI:
https://doi.org/10.1175/JTECH-D-12-00256.1
Page(s):
2241–2247
Restricted access

Abstract

On a uniform terrain site, differences between a sodar and a mast-mounted cup anemometer will arise because of turbulent fluctuations and wind components being measured in different spaces, and because of the inherent difference between scalar and vector averaging. This paper develops theories for turbulence-related random fluctuations resulting from finite sampling rates and sampling from spatially distributed volumes. Coefficients of determination (R2) are predicted comparable to those obtained in practice. It is shown that more than two-thirds of the reduction in R2 arises from differences in the winds measured by mast instruments and by sodars, rather than by sodar errors: both instruments are measuring accurately, but just not in the same place or at the same time. The result is that sodars being used operationally should be able to measure winds to a root-mean-square accuracy of around 2%.

Corresponding author address: Stuart Bradley, Physics Department, University of Auckland, Private Bag 92019, Auckland, New Zealand. E-mail: s.bradley@auckland.ac.nz

This article is included in the ISARS 2012 special collection.

Abstract

On a uniform terrain site, differences between a sodar and a mast-mounted cup anemometer will arise because of turbulent fluctuations and wind components being measured in different spaces, and because of the inherent difference between scalar and vector averaging. This paper develops theories for turbulence-related random fluctuations resulting from finite sampling rates and sampling from spatially distributed volumes. Coefficients of determination (R2) are predicted comparable to those obtained in practice. It is shown that more than two-thirds of the reduction in R2 arises from differences in the winds measured by mast instruments and by sodars, rather than by sodar errors: both instruments are measuring accurately, but just not in the same place or at the same time. The result is that sodars being used operationally should be able to measure winds to a root-mean-square accuracy of around 2%.

Corresponding author address: Stuart Bradley, Physics Department, University of Auckland, Private Bag 92019, Auckland, New Zealand. E-mail: s.bradley@auckland.ac.nz

This article is included in the ISARS 2012 special collection.

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