# Single-spectrum prediction of kurtosis of water waves in a non-conservative model

## TL;DR

This paper investigates the relationship between kurtosis, bandwidth, and other spectral properties of water waves under wind forcing, proposing a simple spectral measure to predict rogue wave likelihood in non-conservative models.

## Contribution

It introduces a robust quadratic relation between kurtosis and bandwidth, enabling single-spectrum assessment of rogue wave potential in water waves with wind forcing.

## Key findings

- Kurtosis and BFI are related quadratically but depend on forcing and damping.
- A simple quadratic relation exists between kurtosis and spectral bandwidth.
- The evolution of kurtosis can be predicted using bandwidth and damping coefficients.

## Abstract

We study statistical properties after a sudden episode of wind for water waves propagating in one direction. A wave with random initial conditions is propagated using a forced-damped higher order Nonlinear Schr\"odinger equation (NLS). During the wind episode, the wave action increases, the spectrum broadens, the spectral mean shifts up and the Benjamin-Feir index (BFI) and the kurtosis increase. Conversely, after the wind episode, the opposite occurs for each quantity. The kurtosis of the wave height distribution is considered the main parameter that can indicate whether rogue waves are likely to occur in a sea state, and the BFI is often mentioned as a means to predict the kurtosis. However, we find that while there is indeed a quadratic relation between these two, this relationship is dependent on the details of the forcing and damping. Instead, a simple and robust quadratic relation does exist between the kurtosis and the bandwidth. This could allow for a single-spectrum assessment of the likelihood of rogue waves in a given sea state. In addition, as the kurtosis depends strongly on the damping and forcing coefficients, by combining the bandwidth measurement with the damping coefficient, the evolution of the kurtosis after the wind episode can be predicted.