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A new mesoscale eddy tracking methodology based on fast normalized cross-correlation and its validation in the Northwest Pacific

ORCID Icon, , , &
Pages 175-193 | Received 04 Jun 2022, Accepted 15 Sep 2022, Published online: 21 Oct 2022
 

Abstract

Most mesoscale eddy tracking methodologies used prior to this study evaluated eddy features using a distance-based proximity relationship, rather than considering similarities between eddies. This study applies a fast normalized cross-correlation methodology in the field of image registration to propose a novel mesoscale eddy tracking methodology that can rapidly and comprehensively calculate the similarities between two eddies and judge their relationship through the correlation coefficient, thus facilitating a more accurate mesoscale eddy trajectory tracking. The sea level anomaly data field is employed to identify the positions of eddies over time. The tracking methodology is then used to track the mesoscale eddy trajectories. After comparing the local nearest neighbor methodology (LNN) with our proposed new methodology in the Northwest Pacific Ocean, we conclude that the proposed methodology can address issues of discontinuity in tracking; especially in cases involving eddies with long lifespans. The tracking trajectories utilized in the proposed methodology achieve superior continuity and integrity and a higher degree of characterization than LNN, with the tracking results showing greater consistency with real eddy motion. The new methodology proposed in this paper has great significance for more widespread use.

Acknowledgements

The altimeter products were produced and distributed by CMEMS (Copernicus Marine and Environment Monitoring Service; http://marine.copernicus.eu)

Disclosure statement

No potential conflict of interest was reported by the authors.

Data availability statement

The data that support the findings of this study are openly available in [Copernicus Marine and Environment Monitoring Service (CMEMS)] at https://doi.org/10.48670/moi-00148 [doi].

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