Exploring the propagation characteristics of ocean eddies from the perspective of complex networks: A case study in the South China Sea

Du Yunyan; Mo Yang; Wang Huimeng; Yi Jiawei

doi:10.3969/j.issn.0253-4193.2017.07.011

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Du Yunyan, Mo Yang, Wang Huimeng, Yi Jiawei. Exploring the propagation characteristics of ocean eddies from the perspective of complex networks: A case study in the South China Sea[J]. Haiyang Xuebao, 2017, 39(7): 110-123. doi: 10.3969/j.issn.0253-4193.2017.07.011

Citation:

Du Yunyan, Mo Yang, Wang Huimeng, Yi Jiawei. Exploring the propagation characteristics of ocean eddies from the perspective of complex networks: A case study in the South China Sea[J]. Haiyang Xuebao, 2017, 39(7): 110-123. doi: 10.3969/j.issn.0253-4193.2017.07.011

Citation:

Du Yunyan, Mo Yang, Wang Huimeng, Yi Jiawei. Exploring the propagation characteristics of ocean eddies from the perspective of complex networks: A case study in the South China Sea[J]. Haiyang Xuebao, 2017, 39(7): 110-123. doi: 10.3969/j.issn.0253-4193.2017.07.011

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Exploring the propagation characteristics of ocean eddies from the perspective of complex networks: A case study in the South China Sea

doi: 10.3969/j.issn.0253-4193.2017.07.011

State Key Lab of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Science, Beijing 100101, China;University of Chinese Academy of Sciences, Beijing 100049, China

Received Date: 2016-09-04
Rev Recd Date: 2016-11-29

Abstract

Abstract

Mesoscale eddies are a prominent dynamic phenomenon in the ocean with complex and continuous changes during lifecycles. It has become a research focus to investigate eddy propagation characteristics using data driven techniques. From the perspective that eddy trajectories collectively create a spatial network, this study presents a community detection method to uncover latent clusters of eddy activities. The creation of the mobility network is achieved by dividing the study area, the South China Sea, into regular grids and projecting eddy trajectories obtained from 1992 to 2011 to this grid-like network with stop locations as nodes and transitions as edges. The trajectories are preprocessed and generalized at four different granularities:trajectory partitions (TP), origin-destination transitions (OD), minimum description length (MDL), and regeneration of strong processes (RSP). Then, a fast unfolding algorithm is applied to the networks created at different granularities to discover potential communities. Finally, the relationships between different communities are visually analyzed using the chord diagram. The results show that the RSP data of eddy tracks overcome the data insufficiency in TP-network, and the method is able to identify major paths and clustering patterns of eddy activities throughout the life from the RSP data.
- complex networks,
- regionalization,
- propagation,
- ocean eddy,
- South China Sea

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References(33)

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