Reduced-order prediction of rogue waves in two-dimensional deep-water waves
Mohammad Farazmand, Themistoklis P. Sapsis

TL;DR
This paper introduces a reduced-order prediction method for rogue waves in two-dimensional deep-water waves by decomposing the wave field into localized groups and precomputing their maximum elevations, enabling efficient large wave forecasting.
Contribution
It develops a novel wave field decomposition and precomputed elevation map approach for predicting rogue waves without direct simulation of the entire wave field.
Findings
The method accurately predicts rogue wave occurrence in various ocean spectra.
A critical wave group length scale associated with rogue wave probability is identified.
The approach reduces computational complexity while maintaining prediction accuracy.
Abstract
We consider the problem of large wave prediction in two-dimensional water waves. Such waves form due to the synergistic effect of dispersive mixing of smaller wave groups and the action of localized nonlinear wave interactions that leads to focusing. Instead of a direct simulation approach, we rely on the decomposition of the wave field into a discrete set of localized wave groups with optimal length scales and amplitudes. Due to the short-term character of the prediction, these wave groups do not interact and therefore their dynamics can be characterized individually. Using direct numerical simulations of the governing envelope equations we precompute the expected maximum elevation for each of those wave groups. The combination of the wave field decomposition algorithm, which provides information about the statistics of the system, and the precomputed map for the expected wave group…
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