Semi-empirical dissipation source functions for ocean waves: Part I, definition, calibration and validation

TL;DR

This paper introduces new, observation-consistent parameterizations for wave spectrum dissipation, calibrated with data across diverse ocean conditions, improving wave modeling accuracy.

Contribution

It develops and calibrates novel dissipation source functions for ocean wave spectra that depend on wave and wind properties, enhancing wave model realism.

Findings

Accurate reproduction of directional wave spectra shapes.

Validated wave height and period predictions across various conditions.

Improved overall wave energy balance modeling.

Abstract

New parameterizations for the spectra dissipation of wind-generated waves are proposed. The rates of dissipation have no predetermined spectral shapes and are functions of the wave spectrum and wind speed and direction, in a way consistent with observation of wave breaking and swell dissipation properties. Namely, the swell dissipation is nonlinear and proportional to the swell steepness, and dissipation due to wave breaking is non-zero only when a non-dimensional spectrum exceeds the threshold at which waves are observed to start breaking. An additional source of short wave dissipation due to long wave breaking is introduced to represent the dissipation of short waves due to longer breaking waves. Several degrees of freedom are introduced in the wave breaking and the wind-wave generation term of Janssen (J. Phys. Oceanogr. 1991). These parameterizations are combined and calibrated with the Discrete Interaction Approximation of Hasselmann et al. (J. Phys. Oceangr. 1985) for the nonlinear interactions. Parameters are adjusted to reproduce observed shapes of directional wave spectra, and the variability of spectral moments with wind speed and wave height. The wave energy balance is verified in a wide range of conditions and scales, from gentle swells to major hurricanes, from the global ocean to coastal settings. Wave height, peak and mean periods, and spectral data are validated using in situ and remote sensing data. Some systematic defects are still present, but the parameterizations yield the best overall results to date. Perspectives for further improvement are also given.