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Article: Global monthly gridded atmospheric carbon dioxide concentrations under the historical and future scenarios

TitleGlobal monthly gridded atmospheric carbon dioxide concentrations under the historical and future scenarios
Authors
Issue Date2022
Citation
Scientific Data, 2022, v. 9, n. 1, article no. 83 How to Cite?
AbstractIncreases in atmospheric carbon dioxide (CO2) concentrations is the main driver of global warming due to fossil fuel combustion. Satellite observations provide continuous global CO2 retrieval products, that reveal the nonuniform distributions of atmospheric CO2 concentrations. However, climate simulation studies are almost based on a globally uniform mean or latitudinally resolved CO2 concentrations assumption. In this study, we reconstructed the historical global monthly distributions of atmospheric CO2 concentrations with 1° resolution from 1850 to 2013 which are based on the historical monthly and latitudinally resolved CO2 concentrations accounting longitudinal features retrieved from fossil-fuel CO2 emissions from Carbon Dioxide Information Analysis Center. And the spatial distributions of nonuniform CO2 under Shared Socio-economic Pathways and Representative Concentration Pathways scenarios were generated based on the spatial, seasonal and interannual scales of the current CO2 concentrations from 2015 to 2150. Including the heterogenous CO2 distributions could enhance the realism of global climate modeling, to better anticipate the potential socio-economic implications, adaptation practices, and mitigation of climate change.
Persistent Identifierhttp://hdl.handle.net/10722/334814
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorCheng, Wei-
dc.contributor.authorDan, Li-
dc.contributor.authorDeng, Xiangzheng-
dc.contributor.authorFeng, Jinming-
dc.contributor.authorWang, Yongli-
dc.contributor.authorPeng, Jing-
dc.contributor.authorTian, Jing-
dc.contributor.authorQi, Wei-
dc.contributor.authorLiu, Zhu-
dc.contributor.authorZheng, Xinqi-
dc.contributor.authorZhou, Demin-
dc.contributor.authorJiang, Sijian-
dc.contributor.authorZhao, Haipeng-
dc.contributor.authorWang, Xiaoyu-
dc.date.accessioned2023-10-20T06:50:56Z-
dc.date.available2023-10-20T06:50:56Z-
dc.date.issued2022-
dc.identifier.citationScientific Data, 2022, v. 9, n. 1, article no. 83-
dc.identifier.urihttp://hdl.handle.net/10722/334814-
dc.description.abstractIncreases in atmospheric carbon dioxide (CO2) concentrations is the main driver of global warming due to fossil fuel combustion. Satellite observations provide continuous global CO2 retrieval products, that reveal the nonuniform distributions of atmospheric CO2 concentrations. However, climate simulation studies are almost based on a globally uniform mean or latitudinally resolved CO2 concentrations assumption. In this study, we reconstructed the historical global monthly distributions of atmospheric CO2 concentrations with 1° resolution from 1850 to 2013 which are based on the historical monthly and latitudinally resolved CO2 concentrations accounting longitudinal features retrieved from fossil-fuel CO2 emissions from Carbon Dioxide Information Analysis Center. And the spatial distributions of nonuniform CO2 under Shared Socio-economic Pathways and Representative Concentration Pathways scenarios were generated based on the spatial, seasonal and interannual scales of the current CO2 concentrations from 2015 to 2150. Including the heterogenous CO2 distributions could enhance the realism of global climate modeling, to better anticipate the potential socio-economic implications, adaptation practices, and mitigation of climate change.-
dc.languageeng-
dc.relation.ispartofScientific Data-
dc.titleGlobal monthly gridded atmospheric carbon dioxide concentrations under the historical and future scenarios-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1038/s41597-022-01196-7-
dc.identifier.pmid35277521-
dc.identifier.scopuseid_2-s2.0-85126389489-
dc.identifier.volume9-
dc.identifier.issue1-
dc.identifier.spagearticle no. 83-
dc.identifier.epagearticle no. 83-
dc.identifier.eissn2052-4463-
dc.identifier.isiWOS:000767813100011-

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