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

• Published in: Journal of Atmospheric and Oceanic Technology
• Main Authors: Feucher, Charlene, Maze, Guillaume, Mercier, Herle
• Format: Text
• Language: English
• Published: Amer Meteorological Soc
• Subjects: geo; envir; North Atlantic
• Online Access: https://doi.org/10.1175/JTECH-D-15-0192.1; https://archimer.ifremer.fr/doc/00326/43710/44712.pdf; https://archimer.ifremer.fr/doc/00326/43710/

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.