In this study spectral and cross-spectral analysis are conducted using the complex Morlet wavelet transformation to investigate wind–wave interaction during wave growth. The wavelet power spectrum of the individual time series of wind speed and wave height shows that the energy content of these time series varies considerably with time for different scales. The cross-spectrum shows that the energetic events in the wind and wave time series occur at the same scale and time. Therefore, the use of wavelet analysis gives the ability to analyze features that could not be analyzed through the use of the classical Fourier analysis because of the nonstationarity feature of the wind speed and wave height signals. The computed cross-spectrum shows that the regions of high values correspond to the occurrence of a sudden increase in wind speed or wave height.