Correlation analysis of the sea surface features under eddy modulation in the global ocean using remote sensing data

HUANG Chunming; CHEN Xiaoyan; WANG Xuan; CHEN Ge

doi:10.11834/jrs.20231830

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Correlation analysis of the sea surface features under eddy modulation in the global ocean using remote sensing data
Vol. 28, Issue 8, Pages: 2002-2013(2024)
Received：04 January 2022，

Published：07 August 2024
DOI： 10.11834/jrs.20231830
稿件说明：

移动端阅览

黄春铭，陈笑炎，王璇，陈戈.2024.中尺度涡调制下全球海洋遥感特征相关性分析.遥感学报，28（8）： 2002-2013 DOI： 10.11834/jrs.20231830.

Huang C M， Chen X Y， Wang X and Chen G. 2024. Correlation analysis of the sea surface features under eddy modulation in the global ocean using remote sensing data. National Remote Sensing Bulletin， 28（8）：2002-2013 DOI： 10.11834/jrs.20231830.

摘要

本文旨在探寻反气旋性涡旋（AE）、气旋性涡旋（CE）调制下海表特征的相关性分布及其与涡旋外部（OE）区域的差异，为进一步厘清中尺度涡对海气界面的调制机制，改进海洋数值模拟提供理论依据。本文利用2010年—2019年长时序遥感观测数据以及皮尔逊积距相关系数、涡旋识别等方法，系统分析了全球中尺度涡调制下海表温度异常、海面高度异常、叶绿素浓度异常、风速异常4种参数相关性的时空分布特征及其差异。结果表明各参数之间相关性分布赤道太平洋地区相关性最强，印度洋地区以及北美洲西南岸相关性较为显著，其他地区相关性偏弱，且各参数分布呈现出较强的涡旋信号。此外，各参数的相关系数在OE中相比于CE以及AE内部降低0.2左右，相关系数分布的平滑程度约为AE与CE中相关系数分布的20倍，且相关性相反两区域之间存在明显的过渡区域。可以得出结论中尺度涡调制下各参数的相关性分布表现很强的地域特征，其差异主要表现在相关程度以及整体平滑性方面。

Abstract

Mesoscale eddies are broadly distributed in the global ocean and have significant effects on the Sea Surface Temperature (SST)

Sea Surface Height (SSH)

Chlorophyll (Chl)

Wind Speed (WS)

and other ocean parameters. Accordingly

the coupling analysis of mesoscale eddies and ocean key parameters is an important aspect of ocean research. The Anti-cyclonic Eddy (AE)

Cyclonic Eddy (CE)

and Outside Eddy (OE) can be better distinguished with the realization of the individual eddy identification technology. Accordingly

we can comprehensively study the distribution and difference of correlation of sea surface features by comparing OE with AE and CE

providing a theoretical basis for further clarifying the modulation mechanism of the mesoscale eddy on the air‒sea interface and improving ocean numerical simulation. This study calculated the Pearson correlation coefficient using Sea Surface Temperature Anomaly (SSTA)

Sea Level Anomaly (SLA)

Chlorophyll Anomaly (CHLA)

and Wind Speed Abnormal (WSA) data from 2010 to 2019 through distinguishing AE

and OE and compared the smoothness of the correlation coefficient. Results show that the correlation distribution among the parameters has significant regional characteristics. In CE and AE

the correlation is ±0.5 in most areas of the ocean and ±0.7 in the Northern Indian Ocean and the Equatorial Pacific. In OE

the correlation is ±0.2 in most regions and ±0.4 in the Northern Indian Ocean and the Equatorial Pacific. In addition

when a positive (negative) correlation occurs in OE

it generally shows a large range of positive (negative) correlation

and a noticeable transition region exists between the two. However

the extreme correlation regions are smaller and mainly present as scattered points under the influence of eddy

and the transition regions between the positive and the negative regions are narrow. The smoothness coefficient of the correlation coefficient of each parameter in OE is about 15

while those of AE and CE is about 450

which is much lower than that in the OE area. We conclude that the influence of eddy on the correlation of each parameter is mainly reflected in the value

distribution

and smoothness of the correlation coefficient. The correlation coefficient of each parameter in OE is about 0.2 lower than that in CE and AE

and the smoothness of the correlation coefficient in OE is about 30 times that in AE and CE. The correlation distribution also has a strong point feature in the original distribution mode due to the modulation of the eddy.

关键词

Keywords

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