Interaction of Superinertial Waves with Submesoscale Cyclonic Filaments in the North Wall of the Gulf Stream

Abstract

High-resolution, nearly Lagrangian observations of velocity and density made in the North Wall of the Gulf Stream reveal banded shear structures characteristic of near-inertial waves (NIWs). Here, the current follows submesoscale dynamics, with Rossby and Richardson numbers near one, and the vertical vorticity is positive. This allows for a unique analysis of the interaction of NIWs with a submesoscale current dominated by cyclonic as opposed to anticyclonic vorticity. Rotary spectra reveal that the vertical shear vector rotates primarily clockwise with depth and with time at frequencies near and above the local Coriolis frequency f. At some depths, more than half of the measured shear variance is explained by clockwise rotary motions with frequencies between f and 1.7f. The dominant superinertial frequencies are consistent with those inferred from a dispersion relation for NIWs in submesoscale currents that depends on the observed aspect ratio of the wave shear as well as the vertical vorticity, baroclinicity, and stratification of the balanced flow. These observations motivate a ray tracing calculation of superinertial wave propagation in the North Wall, where multiple filaments of strong cyclonic vorticity strongly modify wave propagation. The calculation shows that the minimum permissible frequency for inertia–gravity waves is mostly greater than the Coriolis frequency, and superinertial waves can be trapped and amplified at slantwise critical layers between cyclonic vortex filaments, providing a new plausible explanation for why the observed shear variance is dominated by superinertial waves.

Document Details

Document Type
Pub Defense Publication
Publication Date
Jan 01, 2018
Source ID
10.1175/jpo-d-17-0079.1

Entities

People

  • Craig Lee
  • Daniel B. Whitt
  • Eric A. D'Asaro
  • Jody M. Klymak
  • Leif N. Thomas

Organizations

  • National Center for Atmospheric Research
  • National Science Foundation
  • Office of Naval Research
  • Stanford University
  • University of Victoria
  • University of Washington

Tags

Fields of Study

  • Environmental science

Readers

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

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference