A new automatic oceanic mesoscale eddy detection method using satellite altimeter data based on density clustering
A new automatic oceanic mesoscale eddy detection method using satellite altimeter data based on density clustering
复制标题
基于密度聚类的卫星高度计数据海洋中尺度涡自动探测新方法
DOI：
10.1007/s13131-019-1447-x
复制
发表时间：
2019-05-01
影响因子：
1.4
通讯作者：
Cui, Wei
中科院分区：
文献类型：
--
作者：
Li, Jitao;Liang, Yongquan;Cui, Wei
中尺度涡旋是一种典型的传递海洋能量的中尺度海洋现象。中尺度涡旋的探测和提取是物理海洋学的一个重要方面，而自动中尺度涡旋探测算法是探测和分析中尺度涡旋的最基本工具。用于中尺度涡旋探测的主要数据是由多颗卫星高度计数据合并而成的海平面异常(SLA)数据。这些数据客观地描述了海面高度的状态。中尺度涡旋可以用被SLA闭合轮廓包围的局部等效区来表示，检测过程需要从SLA地图中提取稳定的闭合轮廓结构。针对基于SLA数据的中尺度涡旋检测的特点，提出了一种新的基于聚类的中尺度涡旋自动检测算法。通过分离和过滤SLA数据集来分离中尺度涡区和非涡区，然后建立涡区之间的关系并将它们映射到SLA图上，可以提取中尺度涡旋结构。本文克服了参数设置对传统检测算法的影响，不需要进行灵敏度测试的问题。因此，所提出的算法具有更强的适应性。算法中加入了涡流判别机制，保证了被检测涡流结构的稳定性，提高了检测精度。在此基础上，本文选取了西北太平洋和南海中国海进行了中尺度涡旋探测实验。实验结果表明，该算法比传统算法具有更高的效率，且算法结果稳定。该算法不仅能检测到稳定的单核涡流，而且还能检测到稳定的多核涡结构。
The mesoscale eddy is a typical mesoscale oceanic phenomenon that transfers ocean energy. The detection and extraction of mesoscale eddies is an important aspect of physical oceanography, and automatic mesoscale eddy detection algorithms are the most fundamental tools for detecting and analyzing mesoscale eddies. The main data used in mesoscale eddy detection are sea level anomaly (SLA) data merged by multi-satellite altimeters’ data. These data objectively describe the state of the sea surface height. The mesoscale eddy can be represented by a local equivalent region surrounded by an SLA closed contour, and the detection process requires the extraction of a stable closed contour structure from SLA maps. In consideration of the characteristics of mesoscale eddy detection based on SLA data, this paper proposes a new automatic mesoscale eddy detection algorithm based on clustering. The mesoscale eddy structure can be extracted by separating and filtering SLA data sets to separate a mesoscale eddy region and non-eddy region and then establishing relationships among eddy regions and mapping them on SLA maps. This paper overcomes the problem of the sensitivity of parameter setting that affects the traditional detection algorithm and does not require a sensitivity test. The proposed algorithm is thus more adaptable. An eddy discrimination mechanism is added to the algorithm to ensure the stability of the detected eddy structure and to improve the detection accuracy. On this basis, the paper selects the Northwest Pacific Ocean and the South China Sea to carry out a mesoscale eddy detection experiment. Experimental results show that the proposed algorithm is more efficient than the traditional algorithm and the results of the algorithm remain stable. The proposed algorithm detects not only stable single-core eddies but also stable multi-core eddy structures.