Atmospheric Response to Mesoscale Ocean Eddies over the South China Sea

2018 ◽  
Vol 35 (9) ◽  
pp. 1189-1204 ◽  
Author(s):  
Haoya Liu ◽  
Weibiao Li ◽  
Shumin Chen ◽  
Rong Fang ◽  
Zhuo Li
2019 ◽  
Vol 8 (12) ◽  
pp. 574 ◽  
Author(s):  
Huimeng Wang ◽  
Yunyan Du ◽  
Yong Sun ◽  
Fuyuan Liang ◽  
Jiawei Yi ◽  
...  

Many real-world dynamic features such as ocean eddies, rain clouds, and air masses may split or merge while they are migrating within a space. Topologically, the migration trajectories of such features are structurally more complex as they may have multiple branches due to the splitting and merging processes. Identifying the spatial aggregation patterns of the trajectories could help us better understand how such features evolve. We propose a method, a Global Similarity Measuring Algorithm for the Complex Trajectories (GSMCT), to examine the spatial proximity and topologic similarity among complex trajectories. The method first transforms the complex trajectories into graph structures with nodes and edges. The global similarity between two graph structures (i.e., two complex trajectories) is calculated by averaging their topologic similarity and the spatial proximity, which are calculated using the Comprehensive Structure Matching (CSM) and the Hausdorff distance (HD) methods, respectively. We applied the GSMCT, the HD, and the Dynamic Time Warping (DTW) methods to examine the complex trajectories of the 1993–2016 mesoscale eddies in the South China Sea (SCS). Based on the similarity evaluation results, we categorized the complex trajectories across the SCS into four groups, which are similar to the zoning results reported in previous studies, though difference exists. Moreover, the yearly numbers of complex trajectories in the clusters in the northernmost (Cluster 1) and the southernmost SCS (Cluster 4) are almost the same. However, their seasonal variation and migration characteristics are totally opposite. Such new knowledge is very useful for oceanographers of interest to study and numerically simulate the mesoscale ocean eddies in the SCS.


2016 ◽  
Vol 158 ◽  
pp. 173-181 ◽  
Author(s):  
Yunyan Du ◽  
Di Wu ◽  
Fuyuan Liang ◽  
Jiawei Yi ◽  
Yang Mo ◽  
...  

2020 ◽  
Vol 9 (7) ◽  
pp. 441
Author(s):  
Huimeng Wang ◽  
Yunyan Du ◽  
Jiawei Yi ◽  
Nan Wang ◽  
Fuyuan Liang

Real-word phenomena, such as ocean eddies and clouds, tend to split and merge while they are moving around within a space. Their trajectories usually bear one or more branches and are accordingly defined as complex trajectories in this study. The trajectories may show significant spatiotemporal variations in terms of their structures and some of them may be more prominent than the others. The identification of prominent structures in the complex trajectories of such real-world phenomena could better reveal their evolution processes and even shed new light on the driving factors behind them. Methods have been proposed for the extraction of periodic patterns from simple trajectories (i.e., those with linear structure and without any branches) with a focus on mining the related temporal, spatial or semantic information. Unfortunately, it is not appropriate to directly use such methods to examine complex trajectories. This study proposes a novel method to study the periodic patterns of complex trajectories by considering the inherent spatial, temporal and topological information. First, we use a sequence of symbols to represent the various structures of a complex trajectory over its lifespan. We then, on the basis of the PrefixSpan algorithm, propose a periodic pattern mining of structural evolution (PPSE) algorithm and use it to identify the largest and most frequent patterns (LFPs) from the symbol sequence. We also identify potential periodic behaviors. The PPSE method is then used to examine the complex trajectories of the mesoscale eddy in the South China Sea (SCS) from 1993 to 2016. The complex trajectories of ocean eddies in the southeast of Vietnam show are different from other regions in the SCS in terms of their structural evolution processes, as indicated by the LFPs with the longest lifespan, the widest active range, the highest complexity, and the most active behaviors. The LFP in the southeast of Vietnam has the longest lifespan, the widest active range, the highest complexity, and the most active behaviors. Across the SCS, we found seven migration channels. The LFPs of the eddies that migrate through these channels have a temporal cycle of 17–24 years. These channels are also the regions where eddies frequently emerge, as revealed by flow field data.


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