Mesoscale eddy in situ observation and characterization via underwater glider and complex network theory.

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS
Wei Guo, Zezhong Li, Xinlin Sun, Yatao Zhou, Rongshun Juan, Zhongke Gao, Jürgen Kurths
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Abstract

Mesoscale eddies have attracted increased attention due to their central role in ocean energy and mass transport. The observations of their three-dimensional structure will facilitate the understanding of nonlinear eddy dynamics. In this paper, we propose a novel framework, the mesoscale eddy characterization from ordinal modalities recurrence networks method (MeC-OMRN), that utilizes a Petrel-II underwater glider for in situ observations and vertical structure characterization of a moving mesoscale eddy in the northern South China Sea. First, higher resolution continuous observation profile data collected throughout the traversal by the underwater glider are acquired and preprocessed. Subsequently, we analyze and compute these nonlinear data. To further amplify the hidden structural features of the mesoscale eddy, we construct ordinal modalities sequences rich in spatiotemporal characteristics based on the measured vertical density of the mesoscale eddy. Based on this, we employ ordinal modalities recurrence plots (OMRPs) to depict the vertical structure inside and outside the eddy, revealing significant differences in the OMRPs and the unevenness of density stratification within the eddy. To validate our intriguing findings from the perspective of complex network theory, we build the multivariate weighted ordinal modalities recurrence networks, through which network measures exhibit a more random distribution of vertical density stratification within the eddy, possibly due to more intense vertical convection and oscillations within the eddy's seawater micelles. These framework and intriguing findings are anticipated to be applied to more data-driven in situ observation tasks of oceanic phenomena.

通过水下滑翔机和复杂网络理论对中尺度涡流进行现场观测和定性。
中尺度漩涡在海洋能量和质量传输中发挥着核心作用,因此受到越来越多的关注。观测它们的三维结构将有助于理解非线性漩涡动力学。在本文中,我们提出了一个新颖的框架--中尺度漩涡表征的序模态递归网络方法(MeC-OMRN),利用 Petrel-II 水下滑翔机对南海北部一个移动的中尺度漩涡进行原位观测和垂直结构表征。首先,我们获取并预处理了水下滑翔机在整个穿越过程中收集的更高分辨率的连续观测剖面数据。随后,我们对这些非线性数据进行分析和计算。为了进一步放大中尺度漩涡的隐含结构特征,我们根据测得的中尺度漩涡垂直密度构建了富含时空特征的顺序模态序列。在此基础上,我们采用序模态复现图(OMRPs)来描述漩涡内外的垂直结构,结果发现了 OMRPs 的显著差异和漩涡内密度分层的不均匀性。为了从复杂网络理论的角度验证我们的发现,我们建立了多变量加权序模态递归网络,通过该网络测量显示漩涡内垂直密度分层的分布更随机,这可能是由于漩涡海水胶束内更强烈的垂直对流和振荡造成的。这些框架和有趣的发现有望应用于更多数据驱动的海洋现象现场观测任务。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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