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Global monthly gridded atmospheric carbon dioxide concentrations under the historical and future scenarios
Increases in atmospheric carbon dioxide (CO(2)) concentrations is the main driver of global warming due to fossil fuel combustion. Satellite observations provide continuous global CO(2) retrieval products, that reveal the nonuniform distributions of atmospheric CO(2) concentrations. However, climate...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8917170/ https://www.ncbi.nlm.nih.gov/pubmed/35277521 http://dx.doi.org/10.1038/s41597-022-01196-7 |
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author | Cheng, Wei Dan, Li Deng, Xiangzheng Feng, Jinming Wang, Yongli Peng, Jing Tian, Jing Qi, Wei Liu, Zhu Zheng, Xinqi Zhou, Demin Jiang, Sijian Zhao, Haipeng Wang, Xiaoyu |
author_facet | Cheng, Wei Dan, Li Deng, Xiangzheng Feng, Jinming Wang, Yongli Peng, Jing Tian, Jing Qi, Wei Liu, Zhu Zheng, Xinqi Zhou, Demin Jiang, Sijian Zhao, Haipeng Wang, Xiaoyu |
author_sort | Cheng, Wei |
collection | PubMed |
description | Increases in atmospheric carbon dioxide (CO(2)) concentrations is the main driver of global warming due to fossil fuel combustion. Satellite observations provide continuous global CO(2) retrieval products, that reveal the nonuniform distributions of atmospheric CO(2) concentrations. However, climate simulation studies are almost based on a globally uniform mean or latitudinally resolved CO(2) concentrations assumption. In this study, we reconstructed the historical global monthly distributions of atmospheric CO(2) concentrations with 1° resolution from 1850 to 2013 which are based on the historical monthly and latitudinally resolved CO(2) concentrations accounting longitudinal features retrieved from fossil-fuel CO(2) emissions from Carbon Dioxide Information Analysis Center. And the spatial distributions of nonuniform CO(2) under Shared Socio-economic Pathways and Representative Concentration Pathways scenarios were generated based on the spatial, seasonal and interannual scales of the current CO(2) concentrations from 2015 to 2150. Including the heterogenous CO(2) distributions could enhance the realism of global climate modeling, to better anticipate the potential socio-economic implications, adaptation practices, and mitigation of climate change. |
format | Online Article Text |
id | pubmed-8917170 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-89171702022-03-28 Global monthly gridded atmospheric carbon dioxide concentrations under the historical and future scenarios Cheng, Wei Dan, Li Deng, Xiangzheng Feng, Jinming Wang, Yongli Peng, Jing Tian, Jing Qi, Wei Liu, Zhu Zheng, Xinqi Zhou, Demin Jiang, Sijian Zhao, Haipeng Wang, Xiaoyu Sci Data Data Descriptor Increases in atmospheric carbon dioxide (CO(2)) concentrations is the main driver of global warming due to fossil fuel combustion. Satellite observations provide continuous global CO(2) retrieval products, that reveal the nonuniform distributions of atmospheric CO(2) concentrations. However, climate simulation studies are almost based on a globally uniform mean or latitudinally resolved CO(2) concentrations assumption. In this study, we reconstructed the historical global monthly distributions of atmospheric CO(2) concentrations with 1° resolution from 1850 to 2013 which are based on the historical monthly and latitudinally resolved CO(2) concentrations accounting longitudinal features retrieved from fossil-fuel CO(2) emissions from Carbon Dioxide Information Analysis Center. And the spatial distributions of nonuniform CO(2) under Shared Socio-economic Pathways and Representative Concentration Pathways scenarios were generated based on the spatial, seasonal and interannual scales of the current CO(2) concentrations from 2015 to 2150. Including the heterogenous CO(2) distributions could enhance the realism of global climate modeling, to better anticipate the potential socio-economic implications, adaptation practices, and mitigation of climate change. Nature Publishing Group UK 2022-03-11 /pmc/articles/PMC8917170/ /pubmed/35277521 http://dx.doi.org/10.1038/s41597-022-01196-7 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) applies to the metadata files associated with this article. |
spellingShingle | Data Descriptor Cheng, Wei Dan, Li Deng, Xiangzheng Feng, Jinming Wang, Yongli Peng, Jing Tian, Jing Qi, Wei Liu, Zhu Zheng, Xinqi Zhou, Demin Jiang, Sijian Zhao, Haipeng Wang, Xiaoyu Global monthly gridded atmospheric carbon dioxide concentrations under the historical and future scenarios |
title | Global monthly gridded atmospheric carbon dioxide concentrations under the historical and future scenarios |
title_full | Global monthly gridded atmospheric carbon dioxide concentrations under the historical and future scenarios |
title_fullStr | Global monthly gridded atmospheric carbon dioxide concentrations under the historical and future scenarios |
title_full_unstemmed | Global monthly gridded atmospheric carbon dioxide concentrations under the historical and future scenarios |
title_short | Global monthly gridded atmospheric carbon dioxide concentrations under the historical and future scenarios |
title_sort | global monthly gridded atmospheric carbon dioxide concentrations under the historical and future scenarios |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8917170/ https://www.ncbi.nlm.nih.gov/pubmed/35277521 http://dx.doi.org/10.1038/s41597-022-01196-7 |
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