Anomalous statistics and large deviations of turbulent water waves past a step

A computational strategy based on large deviation theory (LDT) is used to study the anomalous statistical features of turbulent surface waves propagating past an abrupt depth change created via a step in the bottom topography. The dynamics of the outgoing waves past the step are modeled using the truncated Korteweg-de Vries equation with random initial conditions at the step drawn from the system's Gibbs invariant measure of the incoming waves. Within the LDT framework, the probability distributions of the wave height can be obtained via the solution of a deterministic optimization problem. Detailed numerical tests show that this approach accurately captures the non-Gaussian features of the wave height distributions, in particular their asymmetric tails leading to high skewness. These calculations also give the spatiotemporal pattern of the anomalous waves most responsible for these non-Gaussian features. The strategy shows potential for a general class of nonlinear Hamiltonian systems with highly non-Gaussian statistics. (c) 2022 Author(s).

Automated summary

A computational strategy based on large deviation theory is used to study the anomalous statistical features of turbulent surface waves propagating past an abrupt depth change. The strategy accurately captures the non-Gaussian features of the wave height distributions, particularly their asymmetric tails and high skewness. This approach shows potential for a general class of nonlinear Hamiltonian systems with highly non-Gaussian statistics.