Editorial Type:
Article
Article Type:
Research Article

Comparison of Eight Detection Algorithms for the Quantification and Characterization of Mesoscale Eddies in the South China Sea

Zhan Lian Laboratory of Marine Science and Numerical Modeling, First Institute of Oceanography, State Oceanic Administration, and Laboratory for Regional Oceanography and Numerical Modeling, Qingdao National Laboratory for Marine Science and Technology, Qingdao, China.

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Baonan Sun Laboratory of Marine Science and Numerical Modeling, First Institute of Oceanography, State Oceanic Administration, and Laboratory for Regional Oceanography and Numerical Modeling, Qingdao National Laboratory for Marine Science and Technology, Qingdao, China.

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Zexun Wei Laboratory of Marine Science and Numerical Modeling, First Institute of Oceanography, State Oceanic Administration, and Laboratory for Regional Oceanography and Numerical Modeling, Qingdao National Laboratory for Marine Science and Technology, Qingdao, China.

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Yonggang Wang Laboratory of Marine Science and Numerical Modeling, First Institute of Oceanography, State Oceanic Administration, and Laboratory for Regional Oceanography and Numerical Modeling, Qingdao National Laboratory for Marine Science and Technology, Qingdao, China.

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Xinyi Wang Laboratory of Marine Science and Numerical Modeling, First Institute of Oceanography, State Oceanic Administration, and Laboratory for Regional Oceanography and Numerical Modeling, Qingdao National Laboratory for Marine Science and Technology, Qingdao, China.

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Print Publication:
01 Jul 2019
DOI:
https://doi.org/10.1175/JTECH-D-18-0201.1
Page(s):
1361–1380
Restricted access

Abstract

Numerous oceanic mesoscale eddies occur in the South China Sea (SCS). The present study employs eight automatic eddy detection algorithms to identify these mesoscale eddies and compares the results. Eddy probabilities and areas detected by various algorithms differ substantially. Most regions of the SCS with a high discrepancy of eddy probabilities are those with few mesoscale eddies, except for the area west of the Luzon Strait, the area west of Luzon Island between 12° and 17°N, and the southernmost end of the SCS basin. They are primarily caused by strong interference, noncircular eddy shapes, and gentle sea level anomaly (SLA) gradients, respectively. The SLA, winding angle, and hybrid methods can easily detect the mesoscale eddies with wavelike features. The Okubo–Weiss (OW) and the spatially smoothed OW methods better identify grouping phenomena of mesoscale eddies in the SCS. Suggestions are presented on choosing suitable algorithms for studying mesoscale eddies in the SCS. No single algorithm is perfect for all research purposes. For different studies, the most suitable algorithm is different.

© 2019 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Zexun Wei, weizx@fio.org.cn

Abstract

Numerous oceanic mesoscale eddies occur in the South China Sea (SCS). The present study employs eight automatic eddy detection algorithms to identify these mesoscale eddies and compares the results. Eddy probabilities and areas detected by various algorithms differ substantially. Most regions of the SCS with a high discrepancy of eddy probabilities are those with few mesoscale eddies, except for the area west of the Luzon Strait, the area west of Luzon Island between 12° and 17°N, and the southernmost end of the SCS basin. They are primarily caused by strong interference, noncircular eddy shapes, and gentle sea level anomaly (SLA) gradients, respectively. The SLA, winding angle, and hybrid methods can easily detect the mesoscale eddies with wavelike features. The Okubo–Weiss (OW) and the spatially smoothed OW methods better identify grouping phenomena of mesoscale eddies in the SCS. Suggestions are presented on choosing suitable algorithms for studying mesoscale eddies in the SCS. No single algorithm is perfect for all research purposes. For different studies, the most suitable algorithm is different.

© 2019 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Zexun Wei, weizx@fio.org.cn
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