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Observations of Breaking Surface Wave Statistics

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  • 1 Department of Electrical and Computer Engineering, University of Victoria, Victoria, and Institute of Ocean Sciences, Sidney, British Columbia Canada
  • | 2 Institute of Ocean Sciences. Sidney, British Columbia, Canada
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Abstract

Breaking surface waves were observed during the Surface Wave Process Program with a novel acoustical instrument that makes use of underwater ambient sound to track individual breaking events. The spatial and temporal statistics of braking waves such as duration, velocity, spacing and breaking probability were determined under various wind and wave conditions. Statistical models are developed to assess and when appropriate, correct for any bias resulting from limitations of the measurement approach. Empirical relations of these statistics with wind speed are obtained. Comparison of the observed distributions with simultaneously measured directional wave spectra suggests that wave breaking occurs at multiple scales and that the mean scale of breaking is substantially smaller than the associated with the dominant wind wave component. Preliminary analysis indicates that the dependence of breaking probability on the fourth moment of the wave spectrum is consistent with a linear statistical model.

Abstract

Breaking surface waves were observed during the Surface Wave Process Program with a novel acoustical instrument that makes use of underwater ambient sound to track individual breaking events. The spatial and temporal statistics of braking waves such as duration, velocity, spacing and breaking probability were determined under various wind and wave conditions. Statistical models are developed to assess and when appropriate, correct for any bias resulting from limitations of the measurement approach. Empirical relations of these statistics with wind speed are obtained. Comparison of the observed distributions with simultaneously measured directional wave spectra suggests that wave breaking occurs at multiple scales and that the mean scale of breaking is substantially smaller than the associated with the dominant wind wave component. Preliminary analysis indicates that the dependence of breaking probability on the fourth moment of the wave spectrum is consistent with a linear statistical model.

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