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Ocean Dynamics

, Volume 62, Issue 1, pp 105–121 | Cite as

Wind-speed inversion from HF radar first-order backscatter signal

  • Wei Shen
  • Klaus-Werner Gurgel
  • George Voulgaris
  • Thomas Schlick
  • Detlef Stammer
Article
Part of the following topical collections:
  1. Topical Collection on Maritime Rapid Environmental Assessment

Abstract

Land-based high-frequency (HF) radars have the unique capability of continuously monitoring ocean surface environments at ranges up to 200 km off the coast. They provide reliable data on ocean surface currents and under slightly stricter conditions can also give information on ocean waves. Although extraction of wind direction is possible, estimation of wind speed poses a challenge. Existing methods estimate wind speed indirectly from the radar derived ocean wave spectrum, which is estimated from the second-order sidebands of the radar Doppler spectrum. The latter is extracted at shorter ranges compared with the first-order signal, thus limiting the method to short distances. Given this limitation, we explore the possibility of deriving wind speed from radar first-order backscatter signal. Two new methods are developed and presented that explore the relationship between wind speed and wave generation at the Bragg frequency matching that of the radar. One of the methods utilizes the absolute energy level of the radar first-order peaks while the second method uses the directional spreading of the wind generated waves at the Bragg frequency. For both methods, artificial neural network analysis is performed to derive the interdependence of the relevant parameters with wind speed. The first method is suitable for application only at single locations where in situ data are available and the network has been trained for while the second method can also be used outside of the training location on any point within the radar coverage area. Both methods require two or more radar sites and information on the radio beam direction. The methods are verified with data collected in Fedje, Norway, and the Ligurian Sea, Italy using beam forming HF WEllen RAdar (WERA) systems operated at 27.68 and 12.5 MHz, respectively. The results show that application of either method requires wind speeds above a minimum value (lower limit). This limit is radar frequency dependent and is 2.5 and 4.0 m/s for 27.68 and 12.5 MHz, respectively. In addition, an upper limit is identified which is caused by wave energy saturation at the Bragg wave frequency. Estimation of this limit took place through an evaluation of a year long database of ocean spectra generated by a numerical model (third generation WAM). It was found to be at 9.0 and 11.0 m/s for 27.68 and 12.5 MHz, respectively. Above this saturation limit, conventional second-order methods have to be applied, which at this range of wind speed no longer suffer from low signal-to-noise ratios. For use in operational systems, a hybrid of first- and second-order methods is recommended.

Keywords

Coastal wind speed HF radar Neural network Wave generation 

Notes

Acknowledgments

The authors would like to thank Heinz Günther from the Helmholz–Zentrum Geesthacht (former GKSS Research Center) for providing the HIPOCAS WAM model data, the EuroROSE consortium for providing the Fedje experiment data set, and NURC for providing the Ligurian Sea experiment data set to Klaus-Werner Gurgel. The first author was supported by the China Scholarship Council while Deutscher Akademischer Austausch Dienst (DAAD) provided a research grant to George Voulgaris for his visit to the University of Hamburg. Finally, the authors would like to acknowledge the contribution of the two anonymous reviewers whose comments helped us improve this manuscript.

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Copyright information

© Springer-Verlag 2011

Authors and Affiliations

  • Wei Shen
    • 1
  • Klaus-Werner Gurgel
    • 1
  • George Voulgaris
    • 2
  • Thomas Schlick
    • 1
  • Detlef Stammer
    • 1
  1. 1.Institute of OceanographyUniversity of HamburgHamburgGermany
  2. 2.Department of Earth and Ocean SciencesUniversity of South CarolinaColumbiaUSA

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