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Coherent heat patterns revealed by unsupervised classification of Argo temperature profiles in the North Atlantic Ocean ArchiMer
Maze, Guillaume; Mercier, Herle; Fablet, Ronan; Tandeo, Pierre; Radcenco, Manuel Lopez; Lenca, Philippe; Feucher, Charlene; Le Goff, Clement.
A quantitative understanding of the integrated ocean heat content depends on our ability to determine how heat is distributed in the ocean and what are the associated coherent patterns. This study demonstrates how this can be achieved using unsupervised classification of Argo temperature profiles. The classification method used is a Gaussian Mixture Model (GMM) that decomposes the Probability Density Function of a dataset into a weighted sum of Gaussian modes. It is determined that the North Atlantic Argo dataset of temperature profiles con- tains 8 groups of vertically coherent heat patterns, or classes. Each of the temperature profile classes reveals unique and physically coherent heat distributions along the vertical axis. A key result of this study is...
Tipo: Text Palavras-chave: Heat content; Classification North Atlantic; Stratification; Water mass; Thermocline; Argo; Pattern.
Ano: 2017 URL:
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