Study On Statistical Properties Of Breaking Waves And Wave Groups

Breaking and grouping are two important phenomena of sea waves. The breaking probability and whitecap coverage are usually used to evaluate breaking, from which other features of breaking waves (i.e. intensity and duration of breaking waves), as well as distribution and concentration of spray and bubble clouds can be easily calculated, hence play important parts in upper ocean dynamics, air-sea interaction, remote sensing, ocean engineering and sea noise. Thus models of breaking probability and whitecap coverage deserve lucubrating. While wave groups have great influence on wave-structure interaction, marine disasters and design of offshore structures. It would be not only of major scientific interest but also of practical significance to study the statistical properties of wave group parameters.In this paper, the models of Xu et al.(2000) for breaking probability and whitecap coverage are developed into new forms. To avoid the complex estimation of dimensionless fetch, the new models are expressed in terms of average wave period and wind speed, which are relatively easy to measure in field. Considering that wave age has been widely used to parameterize spectral models of ocean waves and air-sea fluxes, the derived models are further developed into simple functions of wave age, respectively.The conventional distribution of wave group statistics is derived by taking records of the sea surface elevation as a random Gaussian process, which ignores the nonlinear effect of sea waves. Thus another aim of this paper is to derive a new distribution for statistical properties of wave groups based on the maximum entropy principle. Such a distribution is desirable, because its acquisition is under the maximum uncertainty, i.e., free of a Gaussian hypothesis. Comparisons of both the maximum entropy distribution and the distribution of Longuet-Higgins (1984) with the laboratory wind-wave data show that the former gives a better fit.To further test the validation of the above models, two measurements were conducted on Bohai Sea to provide real sea data of different conditions. Hydrophones and pressure sensor were adopted to record the wave breaking events and wave elevation, respectively. Instead of the acceleration criterion, the breaking criterion in terms of Sound Spectrum Level (SSL) is definitely employed to help detect wave breaking from the ambient sound signals. With the wave elevation and wind speed data observed, the wave age dependent model of wave breaking probability is reanalyzed. The result shows the new model is competent for breaking probability prediction. By use of the FFT filtering method proposed by Xu et al.(2004), the maximum entropy probability density function of wave records are plotted with comparison to the PDFs of Longuet-Higgins(1984). It has been shown that f_{n= 0.6}(G ), f_n=1 ( H), and f n= 0.5(l ) have rather good agreements with the field data. Furthermore, tentatively examination of correlations between wave groups and breaking suggests that breaking occurs most commonly in the center of a group, which accords with the earlier findings.