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DOI10.1029/2020JD033402
Simulation of the Present and Future Projection of Permafrost on the Qinghai-Tibet Plateau with Statistical and Machine Learning Models
Ni, Jie; Wu, Tonghua; Zhu, Xiaofan; Hu, Guojie; Zou, Defu; Wu, Xiaodong; Li, Ren; Xie, Changwei; Qiao, Yongping; Pang, Qiangqiang; Hao, Junming; Yang, Cheng
通讯作者Wu, TH (通讯作者),Chinese Acad Sci, Cryosphere Res Stn Qinghai Tibet Plateau, State Key Lab Cryospher Sci, Northwest Inst Ecoenvironm & Resources, Lanzhou, Peoples R China. ; Wu, TH (通讯作者),Southern Marine Sci & Engn Guangdong Lab, Guangzhou, Peoples R China.
发表日期2021
ISSN2169-897X
EISSN2169-8996
卷号126期号:2
英文摘要The comprehensive understanding of the occurred changes of permafrost, including the changes of mean annual ground temperature (MAGT) and active layer thickness (ALT), on the Qinghai-Tibet Plateau (QTP) is critical to project permafrost changes due to climate change. Here, we use statistical and machine learning (ML) modeling approaches to simulate the present and future changes of MAGT and ALT in the permafrost regions of the QTP. The results show that the combination of statistical and ML method is reliable to simulate the MAGT and ALT, with the root-mean-square error of 0.53 degrees C and 0.69 m for the MAGT and ALT, respectively. The results show that the present (2000-2015) permafrost area on the QTP is 1.04 x 10(6) km(2) (0.80-1.28 x 10(6) km(2)), and the average MAGT and ALT are -1.35 +/- 0.42 degrees C and 2.3 +/- 0.60 m, respectively. According to the classification system of permafrost stability, 37.3% of the QTP permafrost is suffering from the risk of disappearance. In the future (2061-2080), the near-surface permafrost area will shrink significantly under different Representative Concentration Pathway scenarios (RCPs). It is predicted that the permafrost area will be reduced to 42% of the present area under RCP8.5. Overall, the future changes of MAGT and ALT are pronounced and region-specific. As a result, the combined statistical method with ML requires less parameters and input variables for simulation permafrost thermal regimes and could present an efficient way to figure out the response of permafrost to climatic changes on the QTP.
英文关键词active layer; climate change; mean annual ground temperature; permafrost; Qinghai-Tibet Plateau
语种英语
WOS研究方向Meteorology & Atmospheric Sciences
WOS类目Meteorology & Atmospheric Sciences
WOS记录号WOS:000613703000007
来源期刊JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES
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/253963
作者单位[Ni, Jie; Wu, Tonghua; Zhu, Xiaofan; Hu, Guojie; Zou, Defu; Wu, Xiaodong; Li, Ren; Xie, Changwei; Qiao, Yongping; Pang, Qiangqiang; Hao, Junming; Yang, Cheng] Chinese Acad Sci, Cryosphere Res Stn Qinghai Tibet Plateau, State Key Lab Cryospher Sci, Northwest Inst Ecoenvironm & Resources, Lanzhou, Peoples R China; [Ni, Jie; Hao, Junming; Yang, Cheng] Univ Chinese Acad Sci, Coll Resources & Environm, Beijing, Peoples R China; [Wu, Tonghua] Southern Marine Sci & Engn Guangdong Lab, Guangzhou, Peoples R China; [Hao, Junming] Lanzhou Univ Technol, Sch Civil Engn, Lanzhou, Peoples R China
推荐引用方式
GB/T 7714
Ni, Jie,Wu, Tonghua,Zhu, Xiaofan,et al. Simulation of the Present and Future Projection of Permafrost on the Qinghai-Tibet Plateau with Statistical and Machine Learning Models[J]. 中国科学院西北生态环境资源研究院,2021,126(2).
APA Ni, Jie.,Wu, Tonghua.,Zhu, Xiaofan.,Hu, Guojie.,Zou, Defu.,...&Yang, Cheng.(2021).Simulation of the Present and Future Projection of Permafrost on the Qinghai-Tibet Plateau with Statistical and Machine Learning Models.JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES,126(2).
MLA Ni, Jie,et al."Simulation of the Present and Future Projection of Permafrost on the Qinghai-Tibet Plateau with Statistical and Machine Learning Models".JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES 126.2(2021).
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