Automated detection of crossing seas from simulated wave spectra

Abstract

The presence of crossing seas in the nearshore may lead to a drastic amplification of local wave heights or to a substantial change in the orientation of the highest parts of the wave crest owing to nonlinear interactions of waves in shallow water. The location and strength of the related effects can be roughly forecast based on the properties of crossing wave systems in the framework of the Kadomtsev-Petviashvili equation. We introduce a method of the identification of crossing seas and singling out the properties of interacting wave systems from numerically simulated two-dimensional wave energy spectra of selected locations in the Baltic Sea obtained within a multi-decadal (1956-1997) wave hindcast using the WAM model. Each spectrum spans across 24 evenly spaced directions and 40 frequencies starting from 0.042 Hz (23.8 s) to about 1.718 Hz (0.58 s). The numerically replicated spectra usually contain a certain level of noise, which may lead to the detection of false maxima and is filtered out using a Gaussian-type convolution filter. We then test each sample of the resulting anti-aliased distribution with a pyramid shaped stencil in order to find the spectral density, frequency and direction of all relative maxima. Their frequency and direction is then mapped back onto the initial spectra to evaluate the heights of the single wave systems. The average reduction of maxima detection from unfiltered to filtered data is 9.2%.