A Model Sensitivity Study of Ocean Surface Wave Modulation Induced by Internal Waves

Abstract

Nonlinear internal waves are an upper ocean phenomenon that drives horizontal surface current gradients, which in turn modulate ocean surface waves. Under certain conditions, this wave‐current interaction creates ocean surface roughness heterogeneity, in the form of alternating rough/smooth bands. In this study, we investigate the sensitivity of the modulation effect to internal wave properties and develop sea states using simulations of individual internal wave solitons. We utilize a phased‐resolved two‐layer fluid model to capture the evolution of surface waves deterministically. We conduct extensive simulations with a wide range of parameters, including fluid layer density ratio, internal wave amplitude, and parametric wind speed. We use the ratio of the mean surface slope between the rough and smooth bands, which are identified in the simulated surface wave field, to systematically investigate their response to the internal wave forcing across all our simulation cases. Our results show that, among the internal wave parameters, the upper‐lower layer density ratio causes the strongest surface heterogeneity. Spectral analysis of the surface wave elevation and slope variance reveals that the wavenumbers above the peak are most impacted. We demonstrate that accounting for the internal wave‐induced modulation requires including wave steepness statistics, for example, when modeling air‐sea exchange using a surface roughness, z0, parameter. Currently, these statistics are not included in typically coupled modeling schemes, and these systems cannot account for the impact of internal waves, even if the solitary wave phenomena are resolved.

Document Details

Document Type
Pub Defense Publication
Publication Date
Nov 01, 2022
Source ID
10.1029/2022ea002394

Entities

People

  • David G. Ortiz‐Suslow
  • Jie Wu
  • Lian Shen
  • Qing Wang
  • Xuanting Hao

Organizations

  • Naval Postgraduate School
  • Office of Naval Research
  • University of Minnesota

Tags

Fields of Study

  • Environmental science

Readers

  • Atmospheric Science / Meteorology, specifically Wind Wave Turbulence.
  • Ocean-Atmosphere Mesoscale Modeling, Data Assimilation, and Flux Boundary Layers