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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Veröffentlicht in:Geophysical research letters 2020-01, Vol.47 (2), p.n/a
Hauptverfasser: Ying, N., Zhou, D., Han, Z. G., Chen, Q. H., Ye, Q., Xue, Z. G.
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Chen, Q. H.
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Xue, Z. G.
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
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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 &amp; 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. 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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. 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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 &amp; 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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