globalchange  > 科学计划与规划
DOI: 10.1002/2016GL071035
论文题名:
Global warming projection in the 21st century based on an observational data-driven model
作者: Zeng X.; Geil K.
刊名: Geophysical Research Letters
ISSN: 0094-8504
EISSN: 1944-8235
出版年: 2016
卷: 43, 期:20
起始页码: 10947
结束页码: 10954
语种: 英语
英文关键词: decadal hincast ; decadal prediction ; global warming projection ; observation-based model
Scopus关键词: Earth sciences ; Geophysics ; Anthropogenic warming ; decadal hincast ; Decadal predictions ; Earth system model ; Multidecadal variability ; nocv1 ; Observation-based model ; Observational data ; Projection uncertainty ; Global warming
英文摘要: Global warming has been projected primarily by Earth system models (ESMs). Complementary to this approach, here we provide the decadal and long-term global warming projections based on an observational data-driven model. This model combines natural multidecadal variability with anthropogenic warming that depends on the history of annual emissions. It shows good skill in decadal hindcasts with the recent warming slowdown well captured. While our ensemble mean temperature projections at the end of 21st century are consistent with those from ESMs, our decadal warming projection of 0.35 (0.30-0.43) K from 1986–2005 to 2016–2035 is within their projection range and only two-thirds of the ensemble mean from ESMs. Our predicted warming rate in the next few years is slower than in the 1980s and 1990s, followed by a greater warming rate. Our projection uncertainty range is just one-third of that from ESMs, and its implication is also discussed. ©2016. American Geophysical Union. All Rights Reserved.
URL: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84995610490&doi=10.1002%2f2016GL071035&partnerID=40&md5=fb8269f741ceef5a14e1a8bf9556835f
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/9467
Appears in Collections:科学计划与规划
气候变化与战略

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作者单位: Department of Hydrology and Atmospheric Sciences, University of Arizona, Tucson, AZ, United States

Recommended Citation:
Zeng X.,Geil K.. Global warming projection in the 21st century based on an observational data-driven model[J]. Geophysical Research Letters,2016-01-01,43(20).
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