期刊文献+

Mesoscale oceanic eddies in the South China Sea from 1992 to 2012:evolution processes and statistical analysis 被引量:3

Mesoscale oceanic eddies in the South China Sea from 1992 to 2012:evolution processes and statistical analysis
下载PDF
导出
摘要 Automated identification and tracking of mesoscale ocean eddies has recently become one research hotspot in physical oceanography. Several methods have been developed and applied to survey the general kinetic and geometric characteristics of the ocean eddies in the South China Sea(SCS). However, very few studies attempt to examine eddies' internal evolution processes. In this study, we reported a hybrid method to trace eddies' propagation in the SCS based on their internal structures, which are characterized by eddy centers, footprint borders, and composite borders. Eddy identification and tracking results were represented by a GIS-based spatiotemporal model. Information on instant states, dynamic evolution processes, and events of disappearance, reappearance, split, and mergence is stored in a GIS database. Results were validated by comparing against the ten Dongsha Cyclonic Eddies(DCEs) and the three long-lived anticyclonic eddies(ACEs) in the northern SCS, which were reported in previous literature. Our study confirmed the development of these eddies. Furthermore, we found more DCE-like and ACE-like eddies in these areas from 2005 to 2012 in our database. Spatial distribution analysis of disappearing, reappearing, splitting, and merging activities shows that eddies in the SCS tend to cluster to the northwest of Luzon Island, southwest of Luzon Strait, and around the marginal sea of Vietnam. Kuroshio intrusions and the complex sea floor topography in these areas are the possible factors that lead to these spatial clusters. Automated identification and tracking of mesoscale ocean eddies has recently become one research hotspot in physical oceanography. Several methods have been developed and applied to survey the general kinetic and geometric characteristics of the ocean eddies in the South China Sea(SCS). However, very few studies attempt to examine eddies' internal evolution processes. In this study, we reported a hybrid method to trace eddies' propagation in the SCS based on their internal structures, which are characterized by eddy centers, footprint borders, and composite borders. Eddy identification and tracking results were represented by a GIS-based spatiotemporal model. Information on instant states, dynamic evolution processes, and events of disappearance, reappearance, split, and mergence is stored in a GIS database. Results were validated by comparing against the ten Dongsha Cyclonic Eddies(DCEs) and the three long-lived anticyclonic eddies(ACEs) in the northern SCS, which were reported in previous literature. Our study confirmed the development of these eddies. Furthermore, we found more DCE-like and ACE-like eddies in these areas from 2005 to 2012 in our database. Spatial distribution analysis of disappearing, reappearing, splitting, and merging activities shows that eddies in the SCS tend to cluster to the northwest of Luzon Island, southwest of Luzon Strait, and around the marginal sea of Vietnam. Kuroshio intrusions and the complex sea floor topography in these areas are the possible factors that lead to these spatial clusters.
出处 《Acta Oceanologica Sinica》 SCIE CAS CSCD 2014年第11期36-47,共12页 海洋学报(英文版)
基金 The National Science Foundation of China under contract Nos 41071250 and 41371378 the Innovation Projects of the State Key Laboratory of Resource and Environment Information System,Chinese Academy of Sciences,under contract No.088RA500TA
关键词 mesoscale eddies identification and tracking algorithms spatiotemporal model eddy splitting and merging South China Sea mesoscale eddies,identification and tracking algorithms,spatiotemporal model,eddy splitting and merging,South China Sea
  • 相关文献

参考文献2

二级参考文献4

共引文献19

同被引文献32

  • 1王东晓,王卫强,施平,郭佩芳,甘子钧.Establishment and adjustment of monsoon-driven circulation in the South China Sea[J].Science China Earth Sciences,2003,46(2):173-181. 被引量:2
  • 2林鹏飞,王凡,陈永利,唐晓晖.南海中尺度涡的时空变化规律Ⅰ.统计特征分析[J].海洋学报,2007,29(3):14-22. 被引量:34
  • 3Han J,Lee J-G,Kamber M.An overview of clustering methods in geographic data analysis[A].In Miller H J,Han J.Geographic data mining and knowledge discovery[M].London:CRC Press,2009:149-187.
  • 4Jeung H,Yiu M,Jensen C.Trajectory pattern mining[A].In Zheng Y,Zhou X.Computing with spatial trajectories[M].New York:Springer,2011:143-177.
  • 5Dykes J A,Mountain D M.Seeking structure in records of spatio-temporal behaviour:visualization issues,efforts and applications[J].Computational Statistics & Data Analysis,2003,43(4):581-603.
  • 6Camargo S J,Robertson A,Gaffney S,et al.Cluster analysis of western North Pacific tropical cyclone tracks[C].The 26th conference on hurricanes and tropical meteorology,2004:250-251.
  • 7Lee J-G,Han J,Whang K-Y.Trajectory clustering:a partition-and-group framework[C].Proceedings of the the 2007 ACM SIGMOD international conference on Management of data,2007:593-604.
  • 8Benkert M,Djordjevic B,Gudmundsson J,et al.Finding Popular Places[M].In:Tokuyama T.Algorithms and Computation.Berlin,Heidelberg:Springer,2007:776-787.
  • 9Shaw S-L,Yu H,Bombom L S.A space-time GIS approach to exploring large individual-based spatiotemporal datasets[J].Transactions in GIS,2008,12(4):425-441.
  • 10Shoshany M,Even-Paz A,Bekhor S.Evolution of clusters in dynamic point patterns:with a case study of Ants' simulation[J].International Journal of Geographical Information Science,2007,21(7):777-797.

引证文献3

二级引证文献30

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部