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Breaking of Internal Waves and Turbulent Dissipation in an Anticyclonic Mode Water Eddy

Bieito Fernández Castro, Dafydd Gwyn Evans, Eleanor Frajka‐Williams, Clément Vic, Alberto C. Naveira Garabato

2020Journal of Physical Oceanography36 citationsDOIOpen Access PDF

Abstract

Abstract A 4-month glider mission was analyzed to assess turbulent dissipation in an anticyclonic eddy at the western boundary of the subtropical North Atlantic. The eddy (radius ≈ 60 km) had a core of low potential vorticity between 100 and 450 m, with maximum radial velocities of 0.5 m s −1 and Rossby number ≈ −0.1. Turbulent dissipation was inferred from vertical water velocities derived from the glider flight model. Dissipation was suppressed in the eddy core ( ε ≈ 5 × 10 −10 W kg −1 ) and enhanced below it (>10 −9 W kg −1 ). Elevated dissipation was coincident with quasiperiodic structures in the vertical velocity and pressure perturbations, suggesting internal waves as the drivers of dissipation. A heuristic ray-tracing approximation was used to investigate the wave–eddy interactions leading to turbulent dissipation. Ray-tracing simulations were consistent with two types of wave–eddy interactions that may induce dissipation: the trapping of near-inertial wave energy by the eddy’s relative vorticity, or the entry of an internal tide (generated at the nearby continental slope) to a critical layer in the eddy shear. The latter scenario suggests that the intense mesoscale field characterizing the western boundaries of ocean basins might act as a “leaky wall” controlling the propagation of internal tides into the basin’s interior.

Topics & Concepts

Potential vorticityDissipationInternal waveGeophysicsGeologyMesoscale meteorologyMechanicsAnticycloneTurbulenceInertial waveHydraulic jumpPhysicsEddyVorticityMode waterVortexAtmospheric sciencesClimatologyWave propagationFlow (mathematics)Ocean gyreMechanical waveThermodynamicsQuantum mechanicsSubtropicsLongitudinal waveBiologyFisheryOceanographic and Atmospheric ProcessesOcean Waves and Remote SensingClimate variability and models
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