Lagrangian flows within reflecting internal waves at a horizontal free-slip surface

Abstract

In this paper sequel to Zhou and Diamessis [“Reflection of an internal gravity wave beam off a horizontal free-slip surface,” Phys. Fluids 25, 036601 (2013)], we consider Lagrangian flows within nonlinear internal waves (IWs) reflecting off a horizontal free-slip rigid lid, the latter being a model of the ocean surface. The problem is approached both analytically using small-amplitude approximations and numerically by tracking Lagrangian fluid particles in direct numerical simulation (DNS) datasets of the Eulerian flow. Inviscid small-amplitude analyses for both plane IWs and IW beams (IWBs) show that Eulerian mean flow due to wave-wave interaction and wave-induced Stokes drift cancels each other out completely at the second order in wave steepness A, i.e., O(A2), implying zero Lagrangian mean flow up to that order. However, high-accuracy particle tracking in finite-Reynolds-number fully nonlinear DNS datasets from the work of Zhou and Diamessis suggests that the Euler-Stokes cancelation on O(A2) is not complete. This partial cancelation significantly weakens the mean Lagrangian flows but does not entirely eliminate them. As a result, reflecting nonlinear IWBs produce mean Lagrangian drifts on O(A2) and thus particle dispersion on O(A4). The above findings can be relevant to predicting IW-driven mass transport in the oceanic surface and subsurface region which bears important observational and environmental implications, under circumstances where the effect of Earth rotation can be ignored.

Document Details

Document Type
Pub Defense Publication
Publication Date
Dec 01, 2015
Source ID
10.1063/1.4936578

Entities

People

  • Peter J Diamessis
  • Qi Zhou

Organizations

  • Cornell University
  • Engineering and Physical Sciences Research Council
  • National Science Foundation
  • Office of Naval Research
  • University of Cambridge

Tags

Readers

  • Atmospheric Science / Meteorology, specifically Wind Wave Turbulence.
  • Computational Fluid Dynamics (CFD)