Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1038/s41467-018-07191-0 |
A novel probabilistic forecast system predicting anomalously warm 2018-2022 reinforcing the long-term global warming trend | |
Sevellec, Florian1,2; Drijfhout, Sybren S.2,3 | |
2018-08-14 | |
发表期刊 | NATURE COMMUNICATIONS
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ISSN | 2041-1723 |
出版年 | 2018 |
卷号 | 9 |
文章类型 | Article |
语种 | 英语 |
国家 | France; England; Netherlands |
英文摘要 | In a changing climate, there is an ever-increasing societal demand for accurate and reliable interannual predictions. Accurate and reliable interannual predictions of global temperatures are key for determining the regional climate change impacts that scale with global temperature, such as precipitation extremes, severe droughts, or intense hurricane activity, for instance. However, the chaotic nature of the climate system limits prediction accuracy on such timescales. Here we develop a novel method to predict global-mean surface air temperature and sea surface temperature, based on transfer operators, which allows, by-design, probabilistic forecasts. The prediction accuracy is equivalent to operational forecasts and its reliability is high. The post-1998 global warming hiatus is well predicted. For 2018-2022, the probabilistic forecast indicates a warmer than normal period, with respect to the forced trend. This will temporarily reinforce the long-term global warming trend. The coming warm period is associated with an increased likelihood of intense to extreme temperatures. The important numerical efficiency of the method (a few hundredths of a second on a laptop) opens the possibility for real-time probabilistic predictions carried out on personal mobile devices. |
领域 | 资源环境 |
收录类别 | SCI-E |
WOS记录号 | WOS:000441516700001 |
WOS关键词 | DECADAL PREDICTABILITY ; CLIMATE ; HIATUS ; MODEL ; LINK |
WOS类目 | Multidisciplinary Sciences |
WOS研究方向 | Science & Technology - Other Topics |
URL | 查看原文 |
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/204083 |
专题 | 资源环境科学 |
作者单位 | 1.Univ Brest, Lab Oceanog Phys & Spatiale, CNRS, IFREMER,UBO,IRD,UMR6523, Brest, France; 2.Univ Southampton, Ocean & Earth Sci, Southampton, Hants, England; 3.Koninklijk Nederlands Meteorol Inst, De Bilt, Netherlands |
推荐引用方式 GB/T 7714 | Sevellec, Florian,Drijfhout, Sybren S.. A novel probabilistic forecast system predicting anomalously warm 2018-2022 reinforcing the long-term global warming trend[J]. NATURE COMMUNICATIONS,2018,9. |
APA | Sevellec, Florian,&Drijfhout, Sybren S..(2018).A novel probabilistic forecast system predicting anomalously warm 2018-2022 reinforcing the long-term global warming trend.NATURE COMMUNICATIONS,9. |
MLA | Sevellec, Florian,et al."A novel probabilistic forecast system predicting anomalously warm 2018-2022 reinforcing the long-term global warming trend".NATURE COMMUNICATIONS 9(2018). |
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