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Journal of Atmospheric and Oceanic Technology

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Editorial Type:
Article
Article Type:
Research Article

A Parallel SLA-Based Algorithm for Global Mesoscale Eddy Identification

Yingjie Liu1, Ge Chen1, Miao Sun1, Shuai Liu1, and Fenglin Tian1
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  • 1 Qingdao Collaborative Innovation Center of Marine Science and Technology, College of Information Science and Engineering, Ocean University of China, and Laboratory for Regional Oceanography and Numerical Modeling, Qingdao National Laboratory for Marine Science and Technology, Qingdao, China
Print Publication:
01 Dec 2016
DOI:
https://doi.org/10.1175/JTECH-D-16-0033.1
Page(s):
2743–2754
Restricted access

Abstract

This paper proposes a new algorithm for parallel identification of mesoscale eddies from global satellite altimetry data. By simplifying the recognition process and the sea level anomaly (SLA) contours’ search range, the method improves identification efficiency compared with the previous SSH-based method even in the single-threaded process. The global SLA map is divided into several regions. These regions are identified simultaneously with a new SSH-based method. All the eddy identification results of these regions are merged seamlessly into a global eddy map. A β-plane approximation is used to calculate the geostrophic speed in the equatorial band. Compared with the computation complexity of the previous SSH-based method, which is , the computation complexity of the new method is , where K is the number of threads and L is the number of regional SLA maps. When applying the new method to the global SLA map, the computation is ~100 times faster than the previous SSH-based method on an average computer. The new method characterizes an eddy structure by radius, amplitude, eddy core, closed SLA contour, and closed SLA contour with maximum average geostrophic speed. In situ data and another global eddy dataset are applied to validate the reliability of eddies detected by the new algorithm. Global eddy mean properties, variability, and the geographical distribution of both datasets are analyzed to demonstrate the performance of this new method and to help understand eddy activities on a global scale.

Corresponding author address: Fenglin Tian, Ocean University of China, 238 Songling Road, Qingdao, Shandong 266100, China. E-mail: tianfenglin@ouc.edu.cn

Abstract

This paper proposes a new algorithm for parallel identification of mesoscale eddies from global satellite altimetry data. By simplifying the recognition process and the sea level anomaly (SLA) contours’ search range, the method improves identification efficiency compared with the previous SSH-based method even in the single-threaded process. The global SLA map is divided into several regions. These regions are identified simultaneously with a new SSH-based method. All the eddy identification results of these regions are merged seamlessly into a global eddy map. A β-plane approximation is used to calculate the geostrophic speed in the equatorial band. Compared with the computation complexity of the previous SSH-based method, which is , the computation complexity of the new method is , where K is the number of threads and L is the number of regional SLA maps. When applying the new method to the global SLA map, the computation is ~100 times faster than the previous SSH-based method on an average computer. The new method characterizes an eddy structure by radius, amplitude, eddy core, closed SLA contour, and closed SLA contour with maximum average geostrophic speed. In situ data and another global eddy dataset are applied to validate the reliability of eddies detected by the new algorithm. Global eddy mean properties, variability, and the geographical distribution of both datasets are analyzed to demonstrate the performance of this new method and to help understand eddy activities on a global scale.

Corresponding author address: Fenglin Tian, Ocean University of China, 238 Songling Road, Qingdao, Shandong 266100, China. E-mail: tianfenglin@ouc.edu.cn
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