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DOI | 10.1002/joc.7528 |
Assimilating an expanded tree ring dataset to reconstruct the millennial air temperature fields for the Northern Hemisphere | |
Fang, Miao; Zheng, Jingyun; Wang, Jianglin; Zhu, Haifeng; Zhang, Xuezhen | |
通讯作者 | Zheng, JY (通讯作者),Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, 11A Datun Rd, Beijing 100101, Peoples R China. |
发表日期 | 2020 |
ISSN | 0899-8418 |
EISSN | 1097-0088 |
英文摘要 | The spatiotemporal variations of the climate of the last millennium provide the context for understanding the recent climate. However, there are few 1000-year-long spatiotemporally continuous climate reconstructions at hemispheric to global scales. Here, a millennial, spatiotemporally continuous and annually resolved air temperature dataset for the Northern Hemisphere (NH) was reconstructed using paleoclimate data assimilation (PDA) approach based on an expanded tree ring proxy dataset and artificial neural network-based proxy system models. Verifications show the PDA-based reconstruction agrees well with instrumental temperature, previous proxy-based reconstructions and the Last Millennium Climate Reanalysis version 2 (LMRv2) dataset in space and time domains. Since the PDA-based reconstruction is spatiotemporally continuous fields without missing value over the whole NH, which is a distinct advantage of the PDA-based reconstruction over other proxy-based NH-averaged temperature reconstructions, we focussed on analysing the spatial variations of the NH temperature during the last millennium, for example, the primary modes of temperature variabilities and the spatial variabilities of the NH temperature in three typical climatic epochs of the millennium. Results show that the first-leading mode (explained variance of 72.50%) of the NH temperature variability is a spatially consistent mode, while the second-leading mode (explained variance of 10.60%) exhibits a different pattern that is different from the first-leading empirical orthogonal function mode, particularly in the Arctic, which shows a dipole structure anomaly. The 20th century was the warmest, with 94.17% of the NH displaying positive anomalies. The 11th century was the second warmest century in the record, with 70.26% of the NH showing a positive anomaly. The 19th century was the coldest, with negative anomalies covering 86.97% of the NH. Northwest North America and the Northern Europe-Barents Sea are two distinctly anomalous centres during these three centuries. Overall, the reconstructed air temperatures provide a new and reliable dataset for studying the millennial NH temperature variations. |
关键词 | ARTIFICIAL NEURAL-NETWORKSLAST-MILLENNIUMCLIMATEWIDTHMODELSIMULATIONSVARIABILITYREANALYSISATMOSPHERERESOLUTION |
英文关键词 | Northern Hemisphere; paleoclimate data assimilation; temperature field reconstruction; the last millennium; tree ring proxy |
语种 | 英语 |
WOS研究方向 | Meteorology & Atmospheric Sciences |
WOS类目 | Meteorology & Atmospheric Sciences |
WOS记录号 | WOS:000750869900001 |
来源期刊 | INTERNATIONAL JOURNAL OF CLIMATOLOGY
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来源机构 | 中国科学院西北生态环境资源研究院 |
文献类型 | 期刊论文 |
条目标识符 | http://gcip.llas.ac.cn/handle/2XKMVOVA/254588 |
作者单位 | [Fang, Miao; Wang, Jianglin] Chinese Acad Sci, Northwest Inst Ecoenvironm & Resources, Lanzhou, Peoples R China; [Zheng, Jingyun; Zhang, Xuezhen] Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, 11A Datun Rd, Beijing 100101, Peoples R China; [Zhu, Haifeng] Chinese Acad Sci, Inst Tibetan Plateau Res, Beijing, Peoples R China |
推荐引用方式 GB/T 7714 | Fang, Miao,Zheng, Jingyun,Wang, Jianglin,et al. Assimilating an expanded tree ring dataset to reconstruct the millennial air temperature fields for the Northern Hemisphere[J]. 中国科学院西北生态环境资源研究院,2020. |
APA | Fang, Miao,Zheng, Jingyun,Wang, Jianglin,Zhu, Haifeng,&Zhang, Xuezhen.(2020).Assimilating an expanded tree ring dataset to reconstruct the millennial air temperature fields for the Northern Hemisphere.INTERNATIONAL JOURNAL OF CLIMATOLOGY. |
MLA | Fang, Miao,et al."Assimilating an expanded tree ring dataset to reconstruct the millennial air temperature fields for the Northern Hemisphere".INTERNATIONAL JOURNAL OF CLIMATOLOGY (2020). |
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