Tracking the evolution processes and behaviors of mesoscale eddies in the South China Sea:a global nearest neighbor filter approach

YI Jiawei DU Yunyan WANG Dongxiao ZHOU Chenghu

易嘉伟, 杜云艳, 王东晓, 周成虎. 南海中尺度涡的演化过程与行为追踪:一种基于全局最邻近滤波的方法[J]. 海洋学报英文版, 2017, 36(11): 27-37. doi: 10.1007/s13131-017-1136-6
引用本文: 易嘉伟, 杜云艳, 王东晓, 周成虎. 南海中尺度涡的演化过程与行为追踪:一种基于全局最邻近滤波的方法[J]. 海洋学报英文版, 2017, 36(11): 27-37. doi: 10.1007/s13131-017-1136-6
YI Jiawei, DU Yunyan, WANG Dongxiao, ZHOU Chenghu. Tracking the evolution processes and behaviors of mesoscale eddies in the South China Sea:a global nearest neighbor filter approach[J]. Acta Oceanologica Sinica, 2017, 36(11): 27-37. doi: 10.1007/s13131-017-1136-6
Citation: YI Jiawei, DU Yunyan, WANG Dongxiao, ZHOU Chenghu. Tracking the evolution processes and behaviors of mesoscale eddies in the South China Sea:a global nearest neighbor filter approach[J]. Acta Oceanologica Sinica, 2017, 36(11): 27-37. doi: 10.1007/s13131-017-1136-6

南海中尺度涡的演化过程与行为追踪:一种基于全局最邻近滤波的方法

doi: 10.1007/s13131-017-1136-6

Tracking the evolution processes and behaviors of mesoscale eddies in the South China Sea:a global nearest neighbor filter approach

  • 摘要: 本文提出了一种基于全局最邻近滤波的涡旋追踪算法(GNNF),用于探索分析南海中尺度涡旋的时空演化过程以及演化行为特征。该算法主要结合了卡尔曼滤波和最优数据关联技术来实现涡旋的迭代追踪。在追踪模拟生成的涡旋轨迹实验中,GNNF算法的追踪错误率约为0.2%,优于目前常用的其他两种涡旋追踪算法。本文采用GNNF方法对1993-2012年的南海涡旋进行了实例研究,一共提取出4912条生命时间超过一周的涡旋轨迹。通过对其中3445条简单演化轨迹的统计分析,本文发现涡旋的生命演化过程存在比较明显的增长和消亡阶段,涡旋的半径、强度和涡度等属性在生命前半段平缓上升变化,后半段平缓下降,涡旋属性的整个变化趋势基本呈开口向下的抛物线状。通过对演化行为进行分析,本文发现涡旋的产生集中在吕宋岛西北和西南两个区域,而涡旋的消亡集中在西沙群岛附近。涡旋的分裂和合并主要分布在吕宋海峡以西,吕宋岛西北,以及越南外海东南海域,而涡旋消隐重现则主要发生在前面两个区域。通过分析涡旋属性在分裂合并等演化行为的前后变化,本文发现涡旋分裂往往导致半径减小和强度减弱,而能量密度和涡度均增加,相反,合并往往增大涡旋半径和强度,但降低了涡旋的能量密度与涡度。
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  • 收稿日期:  2016-07-27
  • 修回日期:  2016-11-29

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