Global Observations of Deep Ocean Kinetic Energy Transfers

Author:

Sévellec F.12,Colin de Verdière A.1,Kolodziejczyk N.1

Affiliation:

1. a Laboratoire d’Océanographie Physique et Spatiale, Univ. Brest CNRS IRD Ifremer, Brest, France

2. b ODYSSEY Project-Team, INRIA CNRS, Brest, France

Abstract

Abstract Observations of deep Argo displacements (located between 950 and 1150 dbar) and their associated integrated Lagrangian velocities allow for the first time to compute worldwide deep horizontal transfers of kinetic energy (KE) between the 3° × 3° mean and eddy reservoirs [mean kinetic energy (MKE) and eddy kinetic energy (EKE), respectively]. This diagnostic reveals that the transfers are mainly localized along western boundaries and in the Southern Ocean. Overall, the MKE-to-EKE transfers appear dominant globally and in all specifically tested regions (i.e., Gulf Stream, Kuroshio, Agulhas Current, and Antarctic Circumpolar Current). However, an important exception is the Zapiola Gyre where EKE-to-MKE transfers dominate. Beyond that, we find that horizontal KE transfers are better described by the horizontal properties of the mean flow deformation (divergence and strain) than by the horizontal properties of the turbulent velocities. Our theoretical analysis also demonstrates that the mean flow vorticity does not contribute to KE transfers. We show the existence of two consistent transfer modes: one from MKE to EKE and one from EKE to MKE, which are based on the eigendirections of the mean flow deformation tensor. The alignment of the turbulence along these directions selects the transfer modes, and it is the competition between these two transfer modes that leads to the actual transfers. We compute these transfer modes globally, regionally, and locally. We explain the distinctive situation of the Zapiola Gyre by the favored alignment of the turbulence with the EKE-to-MKE transfer mode. Overall, the dominance of the large-scale flow properties on the structure of the MKE-to-EKE transfers suggests the potential for large-scale parameterization.

Funder

French CNRS/INSU/LEFE program

Publisher

American Meteorological Society

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