Time-series analysis may appear to be the most straightforward approach to wave measurements, but two common limitations often prevent it from being applied successfully. The first is that time-series analysis can be technically demanding, and the second is that many wave-measuring instruments lack the capability to directly measure surface displacement and therefore cannot provide the data required. Instead, such instruments record wave-related properties such as pressure or velocity and infer the sea state from the spectra of these time series.
An alternative approach is spectral analysis, which relies on the application of Fourier transforms. Using a Fast Fourier Transform (FFT), a wave record can be converted into an energy density spectrum, showing how wave energy is distributed across different frequencies. From the spectrum, frequency-domain wave parameters can be derived. Because of its interpretability and its compatibility with the many instruments that measure only indirectly, spectral analysis has become the primary method for processing wave data. It not only provides a broader set of wave parameters but also enables directional wave analysis.
The parameters derived from spectral analysis include the peak period, peak wave direction, and the frequency-domain equivalents of the mean period and significant wave height, denoted as Tm02 and Hm0, respectively. The most comprehensive approach is therefore to combine both time-series and spectral analyses, ensuring a more complete characterization of the sea state.
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