Long-term link detection in the CO2 concentration climate network

Na Ying, Dong Zhou, Qinghua Chen, Qian Ye, Zhangang Han

Research output: Contribution to journalArticlepeer-review

19 Scopus citations

Abstract

Carbon dioxide (CO2) is a prominent anthropogenic greenhouse gas and its increase is believed to be the major factor in global warming. Here we develop a network theory-based approach to identify and quantify the long-range dependency relations of CO2 concentrations in different regions. Based on CO2 concentrations retrieval from the Atmospheric Infrared Radiation Sounder, we find that the distribution of degrees, weighted degrees, and edge lengths can be described by positively skewed log-normal distribution. The locations of the total weighted degree hubs of the climate network are qualitatively similar to the transient heat flux. Careful analyses further reveal that long distance links spreading from west to east are the most dominant in the climate network. More specifically, we captured an eastward link from East Asia to the Northeastern Pacific Ocean and even the western North America region following the subtropical westerly jet. And the long-term link from North America extending eastward to the western North Atlantic and Mediterranean belongs to southern part of the storm track in the North Atlantic. The connection between the western Russia and southern China generated by North Atlantic Oscillation from the North Atlantic to East Asia is also apparent. Besides, links along the pathway of atmospheric Rossby waves perform evident in the southern hemisphere. These results and methodology reported here provide a useful way to investigate CO2 remote links around the globe and predict future climate.

Original languageEnglish
Pages (from-to)1403-1408
Number of pages6
JournalJournal of Cleaner Production
Volume208
DOIs
StatePublished - 20 Jan 2019

Bibliographical note

Publisher Copyright:
© 2018 Elsevier Ltd

Funding

We wish to thank the National Key Research and Development Program of China (Grant No. 2016YFA0602503 ). We also thank NASA for providing AIRS CO 2 data sets.

FundersFunder number
National Basic Research Program of China (973 Program)2016YFA0602503

    Fingerprint

    Dive into the research topics of 'Long-term link detection in the CO2 concentration climate network'. Together they form a unique fingerprint.

    Cite this