TY - JOUR
T1 - Rogue waves and large deviations in deep sea
JF - Proceedings of the National Academy of Sciences
JO - Proc Natl Acad Sci USA
SP - 855
LP - 860
DO - 10.1073/pnas.1710670115
VL - 115
IS - 5
AU - Dematteis, Giovanni
AU - Grafke, Tobias
AU - Vanden-Eijnden, Eric
Y1 - 2018/01/30
UR - http://www.pnas.org/content/115/5/855.abstract
N2 - Quantifying the departure from Gaussianity of the wave-height distribution in the seas and thereby estimating the likelihood of appearance of rogue waves is a long-standing problem with important practical implications for boats and naval structures. Here, a procedure is introduced to identify ocean states that are precursors to rogue waves, which could permit their early detection. Our findings indicate that rogue waves obey a large deviation principle—i.e., they are dominated by single realizations—which our method calculates by solving an optimization problem. The method generalizes to estimate the probability of extreme events in other deterministic dynamical systems with random initial data and/or parameters, by using prior information about the nature of their statistics.The appearance of rogue waves in deep sea is investigated by using the modified nonlinear Schrödinger (MNLS) equation in one spatial dimension with random initial conditions that are assumed to be normally distributed, with a spectrum approximating realistic conditions of a unidirectional sea state. It is shown that one can use the incomplete information contained in this spectrum as prior and supplement this information with the MNLS dynamics to reliably estimate the probability distribution of the sea surface elevation far in the tail at later times. Our results indicate that rogue waves occur when the system hits unlikely pockets of wave configurations that trigger large disturbances of the surface height. The rogue wave precursors in these pockets are wave patterns of regular height, but with a very specific shape that is identified explicitly, thereby allowing for early detection. The method proposed here combines Monte Carlo sampling with tools from large deviations theory that reduce the calculation of the most likely rogue wave precursors to an optimization problem that can be solved efficiently. This approach is transferable to other problems in which the system’s governing equations contain random initial conditions and/or parameters.
ER -