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
Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China.
Key Laboratory of Land Surface Pattern and Simulation, Chinese Academy of Sciences, Beijing, 100101, China.
Sci Data. 2022 Mar 11;9(1):83. doi: 10.1038/s41597-022-01196-7.
Increases in atmospheric carbon dioxide (CO) concentrations is the main driver of global warming due to fossil fuel combustion. Satellite observations provide continuous global CO retrieval products, that reveal the nonuniform distributions of atmospheric CO concentrations. However, climate simulation studies are almost based on a globally uniform mean or latitudinally resolved CO concentrations assumption. In this study, we reconstructed the historical global monthly distributions of atmospheric CO concentrations with 1° resolution from 1850 to 2013 which are based on the historical monthly and latitudinally resolved CO concentrations accounting longitudinal features retrieved from fossil-fuel CO emissions from Carbon Dioxide Information Analysis Center. And the spatial distributions of nonuniform CO under Shared Socio-economic Pathways and Representative Concentration Pathways scenarios were generated based on the spatial, seasonal and interannual scales of the current CO concentrations from 2015 to 2150. Including the heterogenous CO distributions could enhance the realism of global climate modeling, to better anticipate the potential socio-economic implications, adaptation practices, and mitigation of climate change.
由于化石燃料燃烧导致大气中二氧化碳(CO)浓度增加是全球变暖的主要驱动因素。卫星观测提供了连续的全球CO反演产品,揭示了大气CO浓度的不均匀分布。然而,气候模拟研究几乎都是基于全球均匀均值或纬向分辨率的CO浓度假设。在本研究中,我们基于从二氧化碳信息分析中心的化石燃料CO排放中检索到的考虑纵向特征的历史月度和纬向分辨率的CO浓度,重建了1850年至2013年1°分辨率的历史全球大气CO浓度月度分布。并根据2015年至2150年当前CO浓度的空间、季节和年际尺度,生成了共享社会经济路径和代表性浓度路径情景下不均匀CO的空间分布。纳入不均匀的CO分布可以提高全球气候模型的真实性,以便更好地预测潜在的社会经济影响、适应措施和气候变化缓解情况。