We use the Hilbert-Huang Transform (HHT) for the spectral analysis of waves during a storm in the North Sea that took place in 1999. We look at the contribution of the different Intrinsic Mode Functions (IMF) obtained by the Empirical Mode Decomposition algorithm and also compare the Hilbert Marginal Spectra and the classical Fourier spectra for the data set and for the corresponding IMFs.
The Hilbert-Huang Transform (HHT) was proposed by Huang et al. (1998, 1999, 2003), as an adequate method for the spectral analysis of non-stationary, nonlinear processes. Since then it has been used by several authors for the analysis of sea waves under different conditions (Schlumann, 2000, Veltcheva and Guedes Soares, 2004, Veltcheva, 2005, among others). In this work we study a storm in the North Sea using the HHT. The wave data was decomposed into Intrinsic Mode Functions and their characteristics are studied and compared to those of the original record. We consider both the Hilbert and Fourier Spectra for comparison. HHT We give a brief description of the Hilbert Huang Transform. A detailed presentation can be found in the original articles of Huang et al. (1998, 1999) as well as in Huang (2005a, b). The Hilbert Huang Transform is based on an empirical algorithm called the Empirical Mode Decomposition (EMD), used to decompose a time series into individual characteristic oscillations known as the intrinsic mode functions (IMF). This technique is based on the assumption that any signal consists of different modes of oscillation based on different time scales, so that each IMF represents one of these embedded oscillatory modes. Each IMF has to satisfy two criteria:
The number of local extreme points and of zero-crossings must either be equal or differ at most by one,
