Altimetry-Based Diagnosis of Deep-Reaching Sub-Mesoscale Ocean Fronts

Type Article
Date 2020-09
Language English
Author(s) Siegelman Lia1, 2, Klein Patrice1, 2, 3, 4, Thompson Andrew F.1, Torres Hector S.2, Menemenlis Dimitris2
Affiliation(s) 1 : Environmental Science and Engineering, California Institute of Technology, Pasadena, CA 91125, USA
2 : Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109, USA
3 : Laboratory for Ocean Physics and Satellite remote sensing, Ifremer, CNRS, Univ. de Bretagne Occidentale, 29280 Plouzane, France
4 : Laboratoire de Meteorologie Dynamique, Ecole Normale Superieure, CNRS, 75005 Paris, France
Source Fluids (2311-5521) (MDPI AG), 2020-09 , Vol. 5 , N. 3 , P. 145 (23p.)
DOI 10.3390/fluids5030145
Note This article belongs to the Special Issue Submesoscale Processes in the Ocean
Keyword(s) altimetry, finite-size Lyapunov exponent, ocean dynamics, sub-mesoscale
Abstract

Recent studies demonstrate that energetic sub-mesoscale fronts (10–50 km width) extend in the ocean interior, driving large vertical velocities and associated fluxes. However, diagnosing the dynamics of these deep-reaching fronts from in situ observations remains challenging because of the lack of information on the 3-D structure of the horizontal velocity. Here, a realistic numerical simulation in the Antarctic Circumpolar Current (ACC) is used to study the dynamics of submesocale fronts in relation to velocity gradients, responsible for the formation of these fronts. Results highlight that the stirring properties of the flow at depth, which are related to the velocity gradients, can be inferred from finite-size Lyapunov exponent (FSLE) at the surface. Satellite altimetry observations of FSLE and velocity gradients are then used in combination with recent in situ observations collected by an elephant seal in the ACC to reconstruct frontal dynamics and their associated vertical velocities down to 500 m. The approach proposed here is well suited for the analysis of sub-mesoscale-resolving datasets and the design of future sub-mesoscale field campaigns.

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