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Article Dans Une Revue Journal of Atmospheric and Oceanic Technology Année : 2016

Mean structure of the North Atlantic subtropical permanent pycnocline from in-situ observations

Résumé

A new Objective Algorithm for the Characterization of the permanent Pycnocline (OACP) in subtropical gyres is proposed. OAC-P is based on a pragmatic analysis of vertical density gradient features to identify the permanent pycnocline: OAC-P identifies the permanent pycnocline as the stratified layer found below surface mode waters. OAC-P provides the permanent pycnocline depth, unequivocally associated with a local maximum in the stratification, and top and bottom thicknesses, associated with upward and downward decreases in stratification. OAC-P uses half Gaussian curves as asymmetric non-linear analytical models of the stratification peak. It is the first time that an algorithm is proposed to characterize objectively the permanent pycnocline for a region where handling the stronger stratification peak of the seasonal pycnocline is complex. A guideline for how-to implement OAC-P is given, with application to the North Atlantic Ocean Argo data as example. OAC-P provides a detailed description of the mean structure of the North Atlantic subtropical permanent pycnocline. OAC-P detects a permanent pycnocline throughout the subtropical gyre north of the North Equatorial Current. The large scale description of the permanent pycnocline depth structure as a classic bowl shape is captured however with much more details. New regional information is provided. In particular: (i) there is only one region - the southern recirculation gyre of the Gulf Stream Extension - where the permanent pycnocline is along an isopycnal surface and (ii) vertical asymmetries clearly discriminate one region from another.
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Dates et versions

hal-04200817 , version 1 (06-10-2023)

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Charlene Feucher, Guillaume Maze, Herle Mercier. Mean structure of the North Atlantic subtropical permanent pycnocline from in-situ observations. Journal of Atmospheric and Oceanic Technology, 2016, 33 (6), pp.1285-1308. ⟨10.1175/JTECH-D-15-0192.1⟩. ⟨hal-04200817⟩
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