Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1002/2017GL073688 |
A Bayesian hierarchical model for climate change detection and attribution | |
Katzfuss, Matthias1; Hammerling, Dorit2; Smith, Richard L.3,4 | |
2017-06-16 | |
发表期刊 | GEOPHYSICAL RESEARCH LETTERS
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ISSN | 0094-8276 |
EISSN | 1944-8007 |
出版年 | 2017 |
卷号 | 44期号:11 |
文章类型 | Article |
语种 | 英语 |
国家 | USA |
英文摘要 | Regression-based detection and attribution methods continue to take a central role in the study of climate change and its causes. Here we propose a novel Bayesian hierarchical approach to this problem, which allows us to address several open methodological questions. Specifically, we take into account the uncertainties in the true temperature change due to imperfect measurements, the uncertainty in the true climate signal under different forcing scenarios due to the availability of only a small number of climate model simulations, and the uncertainty associated with estimating the climate variability covariance matrix, including the truncation of the number of empirical orthogonal functions (EOFs) in this covariance matrix. We apply Bayesian model averaging to assign optimal probabilistic weights to different possible truncations and incorporate all uncertainties into the inference on the regression coefficients. We provide an efficient implementation of our method in a software package and illustrate its use with a realistic application. |
英文关键词 | optimal fingerprinting Bayesian model averaging regression empirical orthogonal functions global circulation models uncertainty |
领域 | 气候变化 |
收录类别 | SCI-E |
WOS记录号 | WOS:000404382600053 |
WOS关键词 | PART I ; TEMPERATURE ; ATMOSPHERE |
WOS类目 | Geosciences, Multidisciplinary |
WOS研究方向 | Geology |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/27880 |
专题 | 气候变化 |
作者单位 | 1.Texas A&M Univ, Dept Stat, College Stn, TX 77843 USA; 2.Natl Ctr Atmospher Res, Inst Math Appl Geosci, POB 3000, Boulder, CO 80307 USA; 3.Stat & Appl Math Sci Inst, Res Triangle Pk, NC USA; 4.Univ N Carolina, Dept Stat & Operat Res, Chapel Hill, NC USA |
推荐引用方式 GB/T 7714 | Katzfuss, Matthias,Hammerling, Dorit,Smith, Richard L.. A Bayesian hierarchical model for climate change detection and attribution[J]. GEOPHYSICAL RESEARCH LETTERS,2017,44(11). |
APA | Katzfuss, Matthias,Hammerling, Dorit,&Smith, Richard L..(2017).A Bayesian hierarchical model for climate change detection and attribution.GEOPHYSICAL RESEARCH LETTERS,44(11). |
MLA | Katzfuss, Matthias,et al."A Bayesian hierarchical model for climate change detection and attribution".GEOPHYSICAL RESEARCH LETTERS 44.11(2017). |
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