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

Abstract

This 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.

LORA: a local ensemble transform Kalman filter-based ocean research analysis

“…In c, circles and triangles indicate significant and no significant RMSD differences, respectively, at a 99% confidence level using high-resolution atmospheric forcing because nearshore weak wind speed may be an artifact of low-resolution atmospheric forcing and the reason for the nearshore high SST biases in the LORA. Furthermore, we will investigate the predictability for the Kuroshio path shift to a large meander path in summer 2017 (Sugimoto et al 2020;Sakajo et al 2022) by conducting ensemble prediction experiments. Although the system still includes tuning parameters for ensemble size, localization scales, observation errors, and uncertainty in the atmospheric forcing, which might improve the accuracy, it is beyond the scope of the present study to survey them.…”

Anomalous Nutricline Drives Marked Biogeochemical Contrasts During the Kuroshio Large Meander

“…Here, the Kuroshio path is defined as a LM when the southernmost axis of the Kuroshio is located south of 32°N in the 136°–140°E segment. This definition is one of the two criteria for LM determination used by the JMA (Sakajo et al., 2022). The other criterion is the sea level difference between Kushimoto and Uragami (Figure 1) which is disregarded here because these two locations are much closer than the horizontal resolution of our model (Section 2.2).…”

“…To assess the model performance in simulating the Kuroshio path variability, we downloaded the monthly Kuroshio axis time series produced by the JMA. The data provide the southernmost latitude of the Kuroshio in the 136°–140°E segment from 1961 to 2022 determined based on satellite and hydrographic observations (Qiu & Chen, 2021; Sakajo et al., 2022). The data contain several missing values during 1961–1968 and 1992–1999 (Figure S1 in Supporting Information ).…”

Topological Identification of Vortical Flow Structures in the Left Ventricle of the Heart

“…In the meantime, based on the mathematical theory by Ma and Wang [13], a method of topological flow data analysis (TFDA) has been developed [25], where a unique symbolic graph expression, named COT (partially Cyclically Ordered rooted Tree) representation, is assigned to every topological streamline pattern generated by structurally stable 2D Hamiltonian flows. It has also been expected as practical as numerical pattern recognition for 2D incompressible and viscous flows [20], and has wide applications to practical problems in atmospheric science [23] and oceanography [19], for instance. The topological classification theory is recently extended for 2D compressible flows and a projection of 3D flows on a plane, and it is applied to some industrial problems [22].…”