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
... [Show full abstract] 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.