Rossby Waves Detection in the CO2 and Temperature Multilayer Climate Network

N. Ying; D. Zhou; Z. G. Han; Q. H. Chen; Q. Ye; Z. G. Xue

doi:10.1029/2019gl086507

Rossby Waves Detection in the CO2 and Temperature Multilayer Climate Network

N. Ying, D. Zhou, Z. G. Han, Q. H. Chen, Q. Ye, Z. G. Xue

Research output: Contribution to journal › Article › peer-review

17 Scopus citations

Abstract

Increasing atmospheric carbon dioxide (CO₂) is the main factor of global warming. Carbon satellites have proven that CO₂ concentrations have nonuniform spatio-temporal distributions. The relationship between unevenly distributed CO₂ and global surface air temperature (SAT) is seldom known. The success of complex networks provides an opportunity to address this issue. This paper proposes a multilayer climate network approach to identify the impacts of nonuniform CO₂ on SAT. The results show that the probability density function (PDF) of degrees, weighted degrees, and link lengths follows power-law distributions. A large fraction of strong correlation links resides in proximal distance (smaller than 2,000 km), indicating that CO₂ nodes are strongly connected to the surrounding SAT nodes. The enhanced distributions of large positive weights, time delays, and degree patterns are all consistent with the properties of Rossby waves. This framework can be useful for predicting future climate changes and policy-making for carbon reduction.

Original language	English
Article number	e2019GL086507
Journal	Geophysical Research Letters
Volume	47
Issue number	2
DOIs	https://doi.org/10.1029/2019gl086507
State	Published - 28 Jan 2020
Externally published	Yes

Bibliographical note

Publisher Copyright:
©2020. American Geophysical Union. All Rights Reserved.

Funding

The participation of Dr. Na Ying in this study was supported in parts by the National Key Research and Development Program of China (Grant 2016YFA0602503) and National Key Research and Development Program of China (Grant 2019YFC0214201). The authors wish to thank NASA for providing the AIRS mid-tropospheric CO2 data sets and NECP for providing the SAT data sets. The data for the work in this paper can be downloaded from the figshare website (available from https://dx.doi.org/10.6084/m9.figshare.9885902). The data for the work in the supporting information can be downloaded from the figshare website (available from https://dx.doi.org/10.6084/m9.figshare.11301503).

Funders	Funder number
National Aeronautics and Space Administration
National Basic Research Program of China (973 Program)	2016YFA0602503, 2019YFC0214201

Keywords

Rossby waves
mid-troposphere CO concentrations
multilayer climate network
surface air temperature

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1029/2019gl086507

Cite this

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abstract = "Increasing atmospheric carbon dioxide (CO2) is the main factor of global warming. Carbon satellites have proven that CO2 concentrations have nonuniform spatio-temporal distributions. The relationship between unevenly distributed CO2 and global surface air temperature (SAT) is seldom known. The success of complex networks provides an opportunity to address this issue. This paper proposes a multilayer climate network approach to identify the impacts of nonuniform CO2 on SAT. The results show that the probability density function (PDF) of degrees, weighted degrees, and link lengths follows power-law distributions. A large fraction of strong correlation links resides in proximal distance (smaller than 2,000 km), indicating that CO2 nodes are strongly connected to the surrounding SAT nodes. The enhanced distributions of large positive weights, time delays, and degree patterns are all consistent with the properties of Rossby waves. This framework can be useful for predicting future climate changes and policy-making for carbon reduction.",

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AU - Zhou, D.

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AU - Xue, Z. G.

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Rossby Waves Detection in the CO2 and Temperature Multilayer Climate Network

Abstract

Bibliographical note

Funding

Keywords

UN SDGs

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