Using wavelet spectrum analysis to resolve breaking events in the wind wave time series

This paper presents the development of a new approach, based on wavelet spectrum analysis, for the detection of breaking waves in a time series of surface wave fluctuations. The approach is shown to be capable of producing equivalent wave breaking statistics as field measurements based on detection of whitecaps at a fixed point of observation. This wavelet-based approach is applicable to both deep water and finite depth environments. Based on applications of this approach to the analysis of available field data, a novel classification of wave breaking processes that consists of incipient, developing, and subsiding phases is proposed.