Improving the understanding of the influencing factors on sea level based on wavelet coherence and partial wavelet coherence

Chao SONG; Xiaohong CHEN; Wenjun XIA

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Improving the understanding of the influencing factors on sea level based on wavelet coherence and partial wavelet coherence

Physics | Updated：2024-10-14

- Improving the understanding of the influencing factors on sea level based on wavelet coherence and partial wavelet coherence
- Journal of Oceanology and Limnology Vol. 41, Issue 5, Pages: 1643-1659(2023)
- Affiliations：
  
  1.School of Civil Engineering, Sun Yat-sen University, Guangzhou 510275, China
  2.Guangdong Engineering Technology Research Center of Water Security Regulation and Control for Southern China, Sun Yat-sen University, Guangzhou 510275, China
  3.Key Laboratory of Water Cycle and Water Security in Southern China of Guangdong High Education Institute, Sun Yat-sen University, Guangzhou 510275, China
- Author bio：
  
  eescxh@mail.sysu.edu.cn
- Funds：
- DOI：
  CLC：
- Received：06 March 2022，
  
  Accepted：08 July 2022，
  
  Online First：16 August 2022，
  
  Published：01 September 2023
- Accepted：
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SONG Chao,CHEN Xiaohong,XIA Wenjun.Improving the understanding of the influencing factors on sea level based on wavelet coherence and partial wavelet coherence[J].Journal of Oceanology and Limnology,2023,41(05):1643-1659.
DOI：

SONG Chao,CHEN Xiaohong,XIA Wenjun.Improving the understanding of the influencing factors on sea level based on wavelet coherence and partial wavelet coherence[J].Journal of Oceanology and Limnology,2023,41(05):1643-1659. DOI：

摘要

Abstract

Relationship between sea level change and a single climate indicator has been widely discussed. However

few studies focused on the relationship between monthly mean sea level (MMSL) and several key impact factors

including CO

concentration

sea ice area

and sunspots

on various time scales. In addition

research on the independent relationship between climate factors and sea level on various time scales is lacking

especially when the dependence of climate factors on Niño 3.4 is excluded. Based on this

we use wavelet coherence (WC) and partial wavelet coherence (PWC) to establish a relationship between MMSL and its influencing factors. The WC results show that the influence of climate indices on MMSL has strong regional characteristics. The significant correlation between Southern Hemisphere sea ice area and MMSL is opposite to that between Northern Hemisphere sea ice area and MMSL. The PWC results show that after removing the influence of Niño 3.4

the significant coherent regions of the Pacific Decadal Oscillation (PDO)

Dipole Mode Index (DMI)

Atlantic Multidecadal Oscillation (AMO)

and Southern Oscillation Index (SOI) decrease to varying degrees on different time scales in different regions

demonstrating the influence of Niño 3.4. Our work emphasizes the interrelationship and independent relationship between MMSL and its influencing factors on various time scales and the use of PWC and WC to describe this relationship. The study has an important reference significance for selecting the best predictors of sea level change or climate systems.

关键词

Keywords

references

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