Identification of Kuroshio meanderings south of Japan via a topological data analysis for sea surface height

Abstract

AbstractThis study proposes an algorithm to identify stable Kuroshio meanderings by extracting topological features from a sea surface height (SSH) gridded dataset in 1993–2020. Based on the mathematical theory of topological classifications for streamline patterns, the algorithm provides a unique symbolic representation and a discrete graph structure, which is referred to as the partially cyclically ordered rooted tree (COT) representation and the Reeb graph, respectively, to structurally stable Hamiltonian vector fields. We have confirmed that the temporal variations in the Kuroshio southernmost position south of the Tokai district captured by the algorithm are well consistent with the existing results by the Japan Meteorological Agency (JMA). The algorithm based on the topology detects five meandering periods: The three of them correspond to large meandering events detected by the JMA, while the two of them are offshore non-large meandering events. The topological data analysis reveals that a large cyclonic eddy inside of the meandering is split into two small eddies near the termination of the most meandering events.