Rossby Waves Detection in the CO2 and Temperature Multilayer Climate Network
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 succe...
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description | 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.
Plain Language Summary
Carbon dioxide (CO2) is a prominent anthropogenic greenhouse gas in the atmosphere, and the increasing CO2 is the main reason for global climate warming. The CO2 concentration from satellites has revealed that the spatial distribution of CO2 is uneven. In previous studies, the relationship between CO2 and temperature is based on global CO2 concentration mean assumptions. Here, we propose a multilayer climate network approach to identify their relations using satellite data. We find that the PDF of degrees, weighted degrees, and link lengths follows power‐law distributions. The most dominant links, with a geographical distance larger than 2,000 km, are found for distances of 7,000 km, coinciding with the wavelengths of atmospheric Rossby waves. The time delays associated with these distances are in agreement with the group velocity of the atmospheric Rossby waves. Moreover, the pronounced band over 50°S, the dominance in the Southern Hemisphere relative to the Northern Hemisphere, and the similar patterns to transient heat flux are consistent with the properties of Rossby waves. The proposed approach leads to a better understanding of the role played by CO2 in forcing global temperatures and future climate change.
Key Points
There are short‐term correlations between global mid‐troposphere CO2 concentrations and global surface air temperature
The degrees, weighted degrees, and link lengths of CO2 and SAT mult |
doi_str_mv | 10.1029/2019GL086507 |
format | Article |
fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_2358824676</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2358824676</sourcerecordid><originalsourceid>FETCH-LOGICAL-c4152-864ddd4fcfbab629fa8da146126e921ed11daf8cbeaa8ef8d415487230eae2093</originalsourceid><addsrcrecordid>eNp9kD1PwzAQhi0EEqWw8QMssRI4O67jjCjQghSoVBUxRk58FilpUhyHKv8eozIwMd0Nz3sfDyGXDG4Y8PSWA0sXOSg5g-SITFgqRKQAkmMyAUhDzxN5Ss76fgMAMcRsQvJV1_flSN_0F_b0Hj1Wvu5aWrfUvyPNlpzq1tA1bnfotB8c0ueh8XWjR3Q0a-qt9khf0O8793FOTqxuerz4rVPyOn9YZ49Rvlw8ZXd5VAk245GSwhgjbGVLXUqeWq2MZkIyLjHlDA1jRltVlai1QqtMSAmV8BhQI4c0npKrw9yd6z4H7H2x6QbXhpUFj2dKcSETGajrA1W58KNDW-xcONeNBYPix1fx11fA-QHf1w2O_7LFYpXLYJTH39GDa34</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2358824676</pqid></control><display><type>article</type><title>Rossby Waves Detection in the CO2 and Temperature Multilayer Climate Network</title><source>Wiley-Blackwell Journals</source><source>Wiley Free Archive</source><source>Wiley-Blackwell AGU Digital Archive</source><source>EZB Electronic Journals Library</source><creator>Ying, N. ; Zhou, D. ; Han, Z. G. ; Chen, Q. H. ; Ye, Q. ; Xue, Z. G.</creator><creatorcontrib>Ying, N. ; Zhou, D. ; Han, Z. G. ; Chen, Q. H. ; Ye, Q. ; Xue, Z. G.</creatorcontrib><description>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.
Plain Language Summary
Carbon dioxide (CO2) is a prominent anthropogenic greenhouse gas in the atmosphere, and the increasing CO2 is the main reason for global climate warming. The CO2 concentration from satellites has revealed that the spatial distribution of CO2 is uneven. In previous studies, the relationship between CO2 and temperature is based on global CO2 concentration mean assumptions. Here, we propose a multilayer climate network approach to identify their relations using satellite data. We find that the PDF of degrees, weighted degrees, and link lengths follows power‐law distributions. The most dominant links, with a geographical distance larger than 2,000 km, are found for distances of 7,000 km, coinciding with the wavelengths of atmospheric Rossby waves. The time delays associated with these distances are in agreement with the group velocity of the atmospheric Rossby waves. Moreover, the pronounced band over 50°S, the dominance in the Southern Hemisphere relative to the Northern Hemisphere, and the similar patterns to transient heat flux are consistent with the properties of Rossby waves. The proposed approach leads to a better understanding of the role played by CO2 in forcing global temperatures and future climate change.
Key Points
There are short‐term correlations between global mid‐troposphere CO2 concentrations and global surface air temperature
The degrees, weighted degrees, and link lengths of CO2 and SAT multilayer climate network are conformed to power‐law distributions
Significant correlation links of the constructed climate network yield a clear association with Rossby waves</description><identifier>ISSN: 0094-8276</identifier><identifier>EISSN: 1944-8007</identifier><identifier>DOI: 10.1029/2019GL086507</identifier><language>eng</language><publisher>Washington: John Wiley & Sons, Inc</publisher><subject>Air temperature ; Anthropogenic factors ; Carbon ; Carbon dioxide ; Carbon dioxide atmospheric concentrations ; Carbon dioxide concentration ; Climate change ; Distance ; Environmental impact ; Future climates ; Global climate ; Global temperatures ; Global warming ; Greenhouse effect ; Greenhouse gases ; Group velocity ; Heat flux ; Heat transfer ; Human influences ; mid‐troposphere CO2 concentrations ; multilayer climate network ; Multilayers ; Nodes ; Northern Hemisphere ; Planetary waves ; Probability density function ; Probability density functions ; Probability theory ; Properties ; Rossby waves ; Satellite data ; Satellites ; Southern Hemisphere ; Spatial distribution ; surface air temperature ; Surface temperature ; Surface-air temperature relationships ; Temperature ; Timing ; Wavelengths</subject><ispartof>Geophysical research letters, 2020-01, Vol.47 (2), p.n/a</ispartof><rights>2020. American Geophysical Union. All Rights Reserved.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c4152-864ddd4fcfbab629fa8da146126e921ed11daf8cbeaa8ef8d415487230eae2093</citedby><cites>FETCH-LOGICAL-c4152-864ddd4fcfbab629fa8da146126e921ed11daf8cbeaa8ef8d415487230eae2093</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1029%2F2019GL086507$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1029%2F2019GL086507$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,776,780,1411,1427,11494,27903,27904,45553,45554,46388,46447,46812,46871</link.rule.ids></links><search><creatorcontrib>Ying, N.</creatorcontrib><creatorcontrib>Zhou, D.</creatorcontrib><creatorcontrib>Han, Z. G.</creatorcontrib><creatorcontrib>Chen, Q. H.</creatorcontrib><creatorcontrib>Ye, Q.</creatorcontrib><creatorcontrib>Xue, Z. G.</creatorcontrib><title>Rossby Waves Detection in the CO2 and Temperature Multilayer Climate Network</title><title>Geophysical research letters</title><description>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.
Plain Language Summary
Carbon dioxide (CO2) is a prominent anthropogenic greenhouse gas in the atmosphere, and the increasing CO2 is the main reason for global climate warming. The CO2 concentration from satellites has revealed that the spatial distribution of CO2 is uneven. In previous studies, the relationship between CO2 and temperature is based on global CO2 concentration mean assumptions. Here, we propose a multilayer climate network approach to identify their relations using satellite data. We find that the PDF of degrees, weighted degrees, and link lengths follows power‐law distributions. The most dominant links, with a geographical distance larger than 2,000 km, are found for distances of 7,000 km, coinciding with the wavelengths of atmospheric Rossby waves. The time delays associated with these distances are in agreement with the group velocity of the atmospheric Rossby waves. Moreover, the pronounced band over 50°S, the dominance in the Southern Hemisphere relative to the Northern Hemisphere, and the similar patterns to transient heat flux are consistent with the properties of Rossby waves. The proposed approach leads to a better understanding of the role played by CO2 in forcing global temperatures and future climate change.
Key Points
There are short‐term correlations between global mid‐troposphere CO2 concentrations and global surface air temperature
The degrees, weighted degrees, and link lengths of CO2 and SAT multilayer climate network are conformed to power‐law distributions
Significant correlation links of the constructed climate network yield a clear association with Rossby waves</description><subject>Air temperature</subject><subject>Anthropogenic factors</subject><subject>Carbon</subject><subject>Carbon dioxide</subject><subject>Carbon dioxide atmospheric concentrations</subject><subject>Carbon dioxide concentration</subject><subject>Climate change</subject><subject>Distance</subject><subject>Environmental impact</subject><subject>Future climates</subject><subject>Global climate</subject><subject>Global temperatures</subject><subject>Global warming</subject><subject>Greenhouse effect</subject><subject>Greenhouse gases</subject><subject>Group velocity</subject><subject>Heat flux</subject><subject>Heat transfer</subject><subject>Human influences</subject><subject>mid‐troposphere CO2 concentrations</subject><subject>multilayer climate network</subject><subject>Multilayers</subject><subject>Nodes</subject><subject>Northern Hemisphere</subject><subject>Planetary waves</subject><subject>Probability density function</subject><subject>Probability density functions</subject><subject>Probability theory</subject><subject>Properties</subject><subject>Rossby waves</subject><subject>Satellite data</subject><subject>Satellites</subject><subject>Southern Hemisphere</subject><subject>Spatial distribution</subject><subject>surface air temperature</subject><subject>Surface temperature</subject><subject>Surface-air temperature relationships</subject><subject>Temperature</subject><subject>Timing</subject><subject>Wavelengths</subject><issn>0094-8276</issn><issn>1944-8007</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><recordid>eNp9kD1PwzAQhi0EEqWw8QMssRI4O67jjCjQghSoVBUxRk58FilpUhyHKv8eozIwMd0Nz3sfDyGXDG4Y8PSWA0sXOSg5g-SITFgqRKQAkmMyAUhDzxN5Ss76fgMAMcRsQvJV1_flSN_0F_b0Hj1Wvu5aWrfUvyPNlpzq1tA1bnfotB8c0ueh8XWjR3Q0a-qt9khf0O8793FOTqxuerz4rVPyOn9YZ49Rvlw8ZXd5VAk245GSwhgjbGVLXUqeWq2MZkIyLjHlDA1jRltVlai1QqtMSAmV8BhQI4c0npKrw9yd6z4H7H2x6QbXhpUFj2dKcSETGajrA1W58KNDW-xcONeNBYPix1fx11fA-QHf1w2O_7LFYpXLYJTH39GDa34</recordid><startdate>20200128</startdate><enddate>20200128</enddate><creator>Ying, N.</creator><creator>Zhou, D.</creator><creator>Han, Z. G.</creator><creator>Chen, Q. H.</creator><creator>Ye, Q.</creator><creator>Xue, Z. G.</creator><general>John Wiley & Sons, Inc</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7TG</scope><scope>7TN</scope><scope>8FD</scope><scope>F1W</scope><scope>FR3</scope><scope>H8D</scope><scope>H96</scope><scope>KL.</scope><scope>KR7</scope><scope>L.G</scope><scope>L7M</scope></search><sort><creationdate>20200128</creationdate><title>Rossby Waves Detection in the CO2 and Temperature Multilayer Climate Network</title><author>Ying, N. ; Zhou, D. ; Han, Z. G. ; Chen, Q. H. ; Ye, Q. ; Xue, Z. G.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c4152-864ddd4fcfbab629fa8da146126e921ed11daf8cbeaa8ef8d415487230eae2093</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Air temperature</topic><topic>Anthropogenic factors</topic><topic>Carbon</topic><topic>Carbon dioxide</topic><topic>Carbon dioxide atmospheric concentrations</topic><topic>Carbon dioxide concentration</topic><topic>Climate change</topic><topic>Distance</topic><topic>Environmental impact</topic><topic>Future climates</topic><topic>Global climate</topic><topic>Global temperatures</topic><topic>Global warming</topic><topic>Greenhouse effect</topic><topic>Greenhouse gases</topic><topic>Group velocity</topic><topic>Heat flux</topic><topic>Heat transfer</topic><topic>Human influences</topic><topic>mid‐troposphere CO2 concentrations</topic><topic>multilayer climate network</topic><topic>Multilayers</topic><topic>Nodes</topic><topic>Northern Hemisphere</topic><topic>Planetary waves</topic><topic>Probability density function</topic><topic>Probability density functions</topic><topic>Probability theory</topic><topic>Properties</topic><topic>Rossby waves</topic><topic>Satellite data</topic><topic>Satellites</topic><topic>Southern Hemisphere</topic><topic>Spatial distribution</topic><topic>surface air temperature</topic><topic>Surface temperature</topic><topic>Surface-air temperature relationships</topic><topic>Temperature</topic><topic>Timing</topic><topic>Wavelengths</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Ying, N.</creatorcontrib><creatorcontrib>Zhou, D.</creatorcontrib><creatorcontrib>Han, Z. 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G.</creatorcontrib><collection>CrossRef</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Oceanic Abstracts</collection><collection>Technology Research Database</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Engineering Research Database</collection><collection>Aerospace Database</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>Meteorological & Geoastrophysical Abstracts - Academic</collection><collection>Civil Engineering Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><collection>Advanced Technologies Database with Aerospace</collection><jtitle>Geophysical research letters</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Ying, N.</au><au>Zhou, D.</au><au>Han, Z. G.</au><au>Chen, Q. H.</au><au>Ye, Q.</au><au>Xue, Z. G.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Rossby Waves Detection in the CO2 and Temperature Multilayer Climate Network</atitle><jtitle>Geophysical research letters</jtitle><date>2020-01-28</date><risdate>2020</risdate><volume>47</volume><issue>2</issue><epage>n/a</epage><issn>0094-8276</issn><eissn>1944-8007</eissn><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.
Plain Language Summary
Carbon dioxide (CO2) is a prominent anthropogenic greenhouse gas in the atmosphere, and the increasing CO2 is the main reason for global climate warming. The CO2 concentration from satellites has revealed that the spatial distribution of CO2 is uneven. In previous studies, the relationship between CO2 and temperature is based on global CO2 concentration mean assumptions. Here, we propose a multilayer climate network approach to identify their relations using satellite data. We find that the PDF of degrees, weighted degrees, and link lengths follows power‐law distributions. The most dominant links, with a geographical distance larger than 2,000 km, are found for distances of 7,000 km, coinciding with the wavelengths of atmospheric Rossby waves. The time delays associated with these distances are in agreement with the group velocity of the atmospheric Rossby waves. Moreover, the pronounced band over 50°S, the dominance in the Southern Hemisphere relative to the Northern Hemisphere, and the similar patterns to transient heat flux are consistent with the properties of Rossby waves. The proposed approach leads to a better understanding of the role played by CO2 in forcing global temperatures and future climate change.
Key Points
There are short‐term correlations between global mid‐troposphere CO2 concentrations and global surface air temperature
The degrees, weighted degrees, and link lengths of CO2 and SAT multilayer climate network are conformed to power‐law distributions
Significant correlation links of the constructed climate network yield a clear association with Rossby waves</abstract><cop>Washington</cop><pub>John Wiley & Sons, Inc</pub><doi>10.1029/2019GL086507</doi><tpages>9</tpages></addata></record> |
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subjects | Air temperature Anthropogenic factors Carbon Carbon dioxide Carbon dioxide atmospheric concentrations Carbon dioxide concentration Climate change Distance Environmental impact Future climates Global climate Global temperatures Global warming Greenhouse effect Greenhouse gases Group velocity Heat flux Heat transfer Human influences mid‐troposphere CO2 concentrations multilayer climate network Multilayers Nodes Northern Hemisphere Planetary waves Probability density function Probability density functions Probability theory Properties Rossby waves Satellite data Satellites Southern Hemisphere Spatial distribution surface air temperature Surface temperature Surface-air temperature relationships Temperature Timing Wavelengths |
title | Rossby Waves Detection in the CO2 and Temperature Multilayer Climate Network |
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