Enhancing the accuracy of automatic eddy detection and the capability of recognizing the multi-core structures from maps of sea level anomaly release_c5wlic7gsvfjnjoovy3klx7vy4

by J. Yi, Y. Du, Z. He, C. Zhou


<strong>Abstract.</strong> Automated methods are important for automatically detecting mesoscale eddies in large volumes of altimeter data. While many algorithms have been proposed in the past, this paper presents a new method, called hybrid detection (HD), to enhance the eddy detection accuracy and the capability of recognizing eddy multi-core structures from maps of sea level anomaly (SLA). The HD method has integrated the criteria of the Okubo–Weiss (OW) method and the sea surface height-based (SSH-based) method, two commonly used eddy detection algorithms. Evaluation of the detection accuracy shows that the successful detection rate of HD is ~ 96.6% and the excessive detection rate is ~ 14.2%, which outperforms the OW and those methods using SLA extrema to identify eddies. The capability of recognizing multi-core structures and its significance in tracking eddy splitting or merging events have been illustrated by comparing with the detection results of different algorithms and observations in previous literature.
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Published in Ocean Science (OS) by Copernicus GmbH
ISSN-L 1812-0784
Volume 10
Page(s) 39-48
Release Date 2014-02-10
Publisher Copernicus GmbH
Primary Language en (lookup)

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Date   2014-02-10
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