A novel technique in analyzing non-linear wave-wave interaction

During wave growth non-linear wave–wave interactions cause transfer of some wave energy from lower to higher wave periods as the spectrum grows. Wavelet bicoherence, which is a new technique in the analysis of wind–wave and wave–wave interactions, is used to analyze non-linear wave–wave interactions. A selected record of wind wave that contains the maximum wave height observed during 6 h of wave generation is divided into five segments and wavelet bicoherence is computed for the whole record, and for all divided segments. The study shows that the non-linear wave–wave interaction occurs at different bicoherence levels and these levels are different from one segment to another due to the non-stationarity feature of the examined data set.     

Wavelet bicoherence analysis of wind–wave interaction

A new technique in the analysis of wind–wave interaction, wavelet bicoherence, will be applied in this article. Wavelet bicohence has the ability to detect phase coupling and nonlinear interactions of the quadratic order with time resolution. It is used in this study to analyze wind–wave interaction during wave growth in a Mistral event. A selected record of simultaneously measured wind and wave data during Mistral is divided into five segments and the computations of the wavelet bicoherence are conducted for the whole record and for all divided segments. The results show that the phase coupling occurs between wind speed and wave height over a certain range of frequencies and that the range is different from one segment to another due to the non-stationary feature of the time series.