Statistics of weakly nonlinear waves on currents with strong vertical shear

Autor: Zibo Zheng, Yan Li, Simen Å. Ellingsen
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: Physical Review Fluids
Popis: We investigate how the presence of a vertically sheared current affects wave statistics, including the probability of rogue waves, and apply it to a real-world case using measured spectral and shear current data from the mouth of the Columbia River. A theory for weakly nonlinear waves valid to second order in wave steepness is derived and used to analyze statistical properties of surface waves; the theory extends the classic theory by Longuet-Higgins [J. Fluid Mech. 12, 321 (1962)] to allow for an arbitrary depth-dependent background flow, U ( z ) , with U the horizontal velocity along the main direction of wave propagation and z the vertical axis. Numerical statistics are collected from a large number of realizations of random, irregular sea-states following a JONSWAP spectrum, on linear and exponential model currents of varying strengths. A number of statistical quantities are presented and compared to a range of theoretical expressions from the literature; in particular the distribution of wave surface elevation, surface maxima, and crest height; the exceedance probability including the probability of rogue waves; the maximum crest height among N s waves, and the skewness of the surface elevation distribution. We find that compared to no-shear conditions, opposing vertical shear [ U ′ ( z ) > 0 ] leads to increased wave height and increased skewness of the nonlinear-wave elevation distribution, while a following shear [ U ′ ( z ) < 0 ] has opposite effects. With the wave spectrum and velocity profile measured in the Columbia River estuary by Zippel and Thomson [J. Geophys. Res.: Oceans 122, 3311 (2017)] our second-order theory predicts that the probability of rogue waves is significantly reduced and enhanced during ebb and flood, respectively, adding support to the notion that shear currents need to be accounted for in wave modeling and prediction. publishedVersion
Databáze: OpenAIRE