Generation of Internal Waves by Barotropic Tidal Flow Over a Steep Ridge

Abstract

A three-dimensional nonhydrostatic numerical model is used to study the generation of internal waves by the barotropic tidal flow over a steep two-dimensional ridge in an ocean with strong upper-ocean stratification. The process is examined by varying topographic width, amplitude of the barotropic tide, and stratification at three ridge heights. The results show that a large amount of energy is converted from the barotropic tide to the baroclinic wave when the slope parameter, defined as the ratio of the maximum ridge slope to the maximum wave slope, is greater than 1. The energy flux of internal waves can be normalized by the vertical integral of the buoyancy frequency over the ridge depths and the kinetic energy of the barotropic tides in the water column. A relationship between the normalized energy flux and the slope parameter is derived. The normalized energy flux reaches a constant value independent of the slope parameter when the slope parameter is greater than 1.5. It is inferred that internal wave generation is most efficient at the presence of strong upper-ocean stratification over a steep, tall ridge. In the Luzon Strait, the strength of the shallow thermocline and the location of the Kuroshio front could affect generation of internal solitary waves in the northern South China Sea.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2010
Accession Number
ADA532905

Entities

People

  • Dong S. Ko
  • Hui Qian
  • Ping-tung Shaw

Organizations

  • United States Naval Research Laboratory

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Buoyancy
  • Demographic Cohorts
  • Fluid Mechanics
  • Frequency
  • Froude Number
  • Internal Waves
  • Oceanography
  • Physical Oceanography
  • Ridges
  • Solitons
  • Standing Waves
  • Three Dimensional
  • Tidal Currents
  • Topography
  • Two Dimensional
  • Wave Power
  • Waves

Readers

  • Coastal Oceanography
  • Mathematics or Statistics

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference