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DOI | 10.1175/JCLI-D-16-0850.1 |
Detection and Attribution of Multivariate Climate Change Signals Using Discriminant Analysis and Bayesian Theorem | |
Paeth, Heiko; Pollinger, Felix; Ring, Christoph | |
2017-10-01 | |
发表期刊 | JOURNAL OF CLIMATE |
ISSN | 0894-8755 |
EISSN | 1520-0442 |
出版年 | 2017 |
卷号 | 30期号:19 |
文章类型 | Article |
语种 | 英语 |
国家 | Germany |
英文摘要 | Detection and attribution methods in climatological research aim at assessing whether observed climate anomalies and trends are still consistent with the range of natural climate variations or rather an indication of anthropogenic climate change. In this study, the authors pursue a novel approach by using discriminant analysis to enhance the distinction between past and future climates from state-of-the-art climate model simulations. The method is based on multivariate fingerprints that are defined in the space of several prominent climate indices representing the thermal, dynamical, and hygric aspects of climate change. Attribution is carried out by means of a Bayesian classification approach. The leading discriminant function accounts for more than 99% of total discriminability, with temperature variables, extratropical precipitation, and extratropical circulation modes mainly contributing to the discriminant power. The misclassification probability between probability density functions of past and future climates is substantially reduced by the discriminant analysis: from >50% to <15%. Since the mid-1980s, the observed anomalies of the considered climate indices are more or less consistently attributed to a climate under strong radiative forcing, projected for the first half of the twenty-first century. The authors also assess the sensitivity of their results to different emissions scenarios from the CMIP3 and CMIP5 multimodel ensembles, seasons, prior probabilities for the early twenty-first-century climate, estimates of the observational error, low-pass filters, variable compositions, group numbers, and reference data. |
领域 | 气候变化 |
收录类别 | SCI-E |
WOS记录号 | WOS:000411436700009 |
WOS关键词 | TEMPERATURE-CHANGE ; SENSITIVITY ; OSCILLATION ; MONSOON ; TRENDS ; NORTH |
WOS类目 | Meteorology & Atmospheric Sciences |
WOS研究方向 | Meteorology & Atmospheric Sciences |
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/21096 |
专题 | 气候变化 |
作者单位 | Univ Wurzburg, Inst Geog & Geol, Wurzburg, Germany |
推荐引用方式 GB/T 7714 | Paeth, Heiko,Pollinger, Felix,Ring, Christoph. Detection and Attribution of Multivariate Climate Change Signals Using Discriminant Analysis and Bayesian Theorem[J]. JOURNAL OF CLIMATE,2017,30(19). |
APA | Paeth, Heiko,Pollinger, Felix,&Ring, Christoph.(2017).Detection and Attribution of Multivariate Climate Change Signals Using Discriminant Analysis and Bayesian Theorem.JOURNAL OF CLIMATE,30(19). |
MLA | Paeth, Heiko,et al."Detection and Attribution of Multivariate Climate Change Signals Using Discriminant Analysis and Bayesian Theorem".JOURNAL OF CLIMATE 30.19(2017). |
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