On Constraining Projections of Future Climate Using Observations and Simulations From Multiple Climate Models

• 成果类型: Article
• 署名作者: Sansom, Philip G.; Stephenson, David B.; Bracegirdle, Thomas J.
• 署名单位: University of Exeter; UK Research & Innovation (UKRI); Natural Environment Research Council (NERC); NERC British Antarctic Survey
• 刊物名称: JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
• ISSN/ISSBN: 0162-1459
• DOI: 10.1080/01621459.2020.1851696
• 发表日期: 2021
• 页码: 546-557
• 关键词: emergent constraints; multimodel ensemble; uncertainty; temperature; cmip5; variability; generation; prediction; dependence; BIAS

摘要

Numerical climate models are used to project future climate change due to both anthropogenic and natural causes. Differences between projections from different climate models are a major source of uncertainty about future climate. Emergent relationships shared by multiple climate models have the potential to constrain our uncertainty when combined with historical observations. We combine projections from 13 climate models with observational data to quantify the impact of emergent relationships on projections of future warming in the Arctic at the end of the 21st century. We propose a hierarchical Bayesian framework based on a coexchangeable representation of the relationship between climate models and the Earth system. We show how emergent constraints fit into the coexchangeable representation, and extend it to account for internal variability simulated by the models and natural variability in the Earth system. Our analysis shows that projected warming in some regions of the Arctic may be more than 2 degrees C lower and our uncertainty reduced by up to 30% when constrained by historical observations. A detailed theoretical comparison with existing multi-model projection frameworks is also provided. In particular, we show that projections may be biased if we do not account for internal variability in climate model predictions. for this article, including a standardized description of the materials available for reproducing the work, are available as an online supplement.