Predicting future uncertainty constraints on global warming projections

被引:37
|
作者
Shiogama, H. [1 ]
Stone, D. [2 ]
Emori, S. [1 ]
Takahashi, K. [3 ]
Mori, S. [4 ]
Maeda, A. [5 ]
Ishizaki, Y. [1 ]
Allen, M. R. [6 ,7 ]
机构
[1] Natl Inst Environm Studies, Ctr Global Environm Res, Tsukuba, Ibaraki 3058506, Japan
[2] Univ Calif Berkeley, Lawrence Berkeley Natl Lab, Computat Res Div, Berkeley, CA 94720 USA
[3] Natl Inst Environm Studies, Ctr Social & Environm Syst Res, Tsukuba, Ibaraki 3058506, Japan
[4] Tokyo Univ Sci, Fac Sci & Technol, Dept Ind Adm, Chiba 2788510, Japan
[5] Univ Tokyo, Grad Sch Arts & Sci, Meguro Ku, Tokyo 1538902, Japan
[6] Univ Oxford, Sch Geog & Environm, Oxford OX1 3QY, England
[7] Univ Oxford, Dept Phys, Oxford OX1 3QY, England
来源
SCIENTIFIC REPORTS | 2016年 / 6卷
关键词
CLIMATE; RISK;
D O I
10.1038/srep18903
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Projections of global mean temperature changes (Delta T) in the future are associated with intrinsic uncertainties. Much climate policy discourse has been guided by "current knowledge" of the Delta Ts uncertainty, ignoring the likely future reductions of the uncertainty, because a mechanism for predicting these reductions is lacking. By using simulations of Global Climate Models from the Coupled Model Intercomparison Project Phase 5 ensemble as pseudo past and future observations, we estimate how fast and in what way the uncertainties of Delta T can decline when the current observation network of surface air temperature is maintained. At least in the world of pseudo observations under the Representative Concentration Pathways (RCPs), we can drastically reduce more than 50% of the Delta Ts uncertainty in the 2040 s by 2029, and more than 60% of the Delta Ts uncertainty in the 2090 s by 2049. Under the highest forcing scenario of RCPs, we can predict the true timing of passing the 2 degrees C (3 degrees C) warming threshold 20 (30) years in advance with errors less than 10 years. These results demonstrate potential for sequential decision-making strategies to take advantage of future progress in understanding of anthropogenic climate change.
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页数:7
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