Preprints
https://doi.org/10.5194/essd-2022-77
https://doi.org/10.5194/essd-2022-77
 
25 Feb 2022
25 Feb 2022
Status: this preprint is currently under review for the journal ESSD.

SEIA: a scale-selective eddy identification algorithm for the global ocean

Yikai Yang1,2, Lili Zeng1,3, and Qiang Wang1 Yikai Yang et al.
  • 1State Key Laboratory of Tropical Oceanography (LTO), South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou, 510301, China
  • 2University of Chinese Academy of Sciences, Beijing, China
  • 3Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou), Guangzhou, China

Abstract. Automatic eddy identification algorithms are crucial for global eddy research. This study presents a scale-selective eddy identification algorithm (SEIA; https://github.com/Yk-Yang/SEIA) for the global ocean based on closed sea level anomalies (SLAs) that features two improvements in the detection and tracking processes. First, the scale-selective scheme replaces the previously used threshold for defining the eddy boundary and restricts the numbers of upper and lower grid points based on the data resolution and eddy spatial scale. Under such conditions, the eddy boundary is as large as possible, while the eddy region is not overestimated. Furthermore, a novel and effective overlap scheme is used to track eddies by calculating the intersecting ratio of time-step-successive eddies. SEIA generates 278,630 anticyclonic eddies and 274,351 cyclonic eddies from AVISO’s SLA dataset over a five-year period (2015–2019; http://www.doi.org/10.11922/sciencedb.o00035.00004; Yang et al., 2022). The global distribution of eddies, propagation speed, and eddy path characteristics in the Southern Ocean verify the validity of SEIA.

Yikai Yang et al.

Status: open (extended)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on essd-2022-77', Anonymous Referee #1, 03 Mar 2022 reply
  • RC2: 'Comment on essd-2022-77', Anonymous Referee #2, 18 Mar 2022 reply

Yikai Yang et al.

Data sets

Five years (2015-2019) of global eddy product from SEIA Yikai Yang, Lili Zeng, Qiang Wang http://www.doi.org/10.11922/sciencedb.o00035.00004

Model code and software

A MATLAB- and SLA- based scale-selective eddy identification algorithm Yikai Yang, Lili Zeng, Qiang Wang https://github.com/Yk-Yang/SEIA

Yikai Yang et al.

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Short summary
The study of mesoscale eddies is highly reliant on the physical characteristics of the real ocean. In this study, we build an eddy identification algorithm that features two improvements over the previous ones. First, in the detection process, a scale-selective approach is employed to define the eddy boundary, avoiding the subjective constraint of the eddy shape. Second, a novel and effective overlap scheme is used to track eddies while taking into account their propagation characteristics.