Wave-by-wave forecasts in directional seas using nonlinear dispersion corrections

TL;DR

This paper introduces a nonlinear frequency correction method for deterministic forecasting of directional ocean waves, which improves accuracy over linear models without extra computational cost.

Contribution

The paper presents a novel nonlinear dispersion correction approach for wave forecasting that leverages measured spectra, enhancing prediction accuracy in complex sea states.

Findings

Outperforms linear forecasts in highly nonlinear seas

No additional computational cost compared to linear theory

Effective across various sea steepness and directional spreading conditions

Abstract

We develop a new methodology for the deterministic forecasting of directional ocean surface waves, based on nonlinear frequency corrections. These frequency corrections can be pre-computed based on measured energy density spectra, and therefore come at no additional computational cost compared to linear theory. The nonlinear forecasting methodology is tested on highly-nonlinear, synthetically generated seas with a variety of values of average steepness and directional spreading, and shown to consistently outperform a linear forecast.