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An unsupervised clustering using a Gaussian mixture model is applied to Argoprofiles distributed over the entire ocean. We employ as the coordinatecomponents in feature space the path signature, which is a central notion inrough path theory. This allows us to better identify the oceanic condition ateach horizontal point with distinct clusters, than by using conventionaltemperature and salinity coordinate. To the best of my knowledge, it is thefirst attempt at clustering almost all of the existing Argo profiles with thefull use of measured sequences of temperature, salinity, and pressure. We willalso discuss why the path signature is relevant to representing the property ofa profile.

Clustering global ocean profiles according to temperature-salinity structure