| DOI: | 10.1002/wcc.477
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| Scopus记录号: | 2-s2.0-85020127880
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| 论文题名: | Climate model pluralism beyond dynamical ensembles |
| 作者: | Mazzocchi F; , Pasini A
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| 刊名: | Wiley Interdisciplinary Reviews: Climate Change
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| ISSN: | 17577780
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| 出版年: | 2017
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| 卷: | 8, 期:6 | | 语种: | 英语
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| 英文关键词: | Statistical tests
; Data driven
; Dynamical model
; Global climate model
; Granger Causality
; Methodological approach
; Modeling type
; Research strategy
; Traditional approaches
; Climate models
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| 英文摘要: | Using pluralist research strategies can be a profitable way to study complex systems. This contribution focuses on the approaches for studying the climate that make use of multiple different models, aiming to increase the reliability (in terms of robustness) of attribution results. This Opinion article argues that the traditional approach, which is based on ensemble runs of global climate models, only partially allows the application of a robustness scheme, owing to the difficulty to match or evaluate the conditions required for robustness (i.e., independence or heterogeneity among models). An alternative ‘multi-approach’ strategy is advanced, beyond dynamical modeling but still preserving the idea of model pluralism. Such a strategy, which uses a set of ensembles of different model types by combining dynamical modeling with data-driven methodological approaches (i.e., neural networks and Granger causality), seems to better match the condition of independence. In addition, neural networks and Granger causality lead to achievements in attribution studies that can complement those obtained by dynamical modeling. WIREs Clim Change 2017, 8:e477. doi: 10.1002/wcc.477. For further resources related to this article, please visit the WIREs website. © 2017 Wiley Periodicals, Inc. |
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| 资源类型: | 期刊论文
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| 标识符: | http://119.78.100.158/handle/2HF3EXSE/76148
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| Appears in Collections: | 影响、适应和脆弱性
气候变化与战略
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作者单位: | CNR, Institute for Complex Systems, Rome, Italy; CNR, Institute of Atmospheric Pollution Research, Rome, Italy
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| Recommended Citation: | |
Mazzocchi F,, Pasini A. Climate model pluralism beyond dynamical ensembles[J]. Wiley Interdisciplinary Reviews: Climate Change,2017-01-01,8(6)
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