气候变化领域集成服务门户(CCPortal): A New Framework for Estimating and Decomposing the Uncertainty of Climate Projections

CCPortal

DOI	10.1175/JCLI-D-23-0064.1
	A New Framework for Estimating and Decomposing the Uncertainty of Climate Projections
	Zhang, Shaobo; Zhou, Zuhao; Peng, Peiyi; Xud, Chongyu
发表日期	2024
ISSN	0894-8755
EISSN	1520-0442
起始页码	37
结束页码	2
卷号	37 期号:2
英文摘要	Climate projections obtained by running global climate models (GCMs) are subject to multisource uncer-tainties. The existing framework based on analysis of variance (ANOVA) for decomposing such uncertainties is unable to include the interaction effect between GCM and internal climate variability, which ranks only second to the main effect of GCM in significance. In this study, a three-way ANOVA framework is presented, and all main effects and interaction ef-fects are investigated. The results show that, although the overall uncertainty (O) is mainly contributed by main effects, in-teraction effects are considerable. Specifically, in the twenty-first century, the global mean (calculated at the grid-cell level and then averaged, and likewise below) relative contributions of all main effects are 54% for precipitation and 82% for temperature; those of all interaction effects are, respectively, 46% and 18%. As the three-way ANOVA cannot investi-gate the uncertainty components resulting from uncertainty sources, it is improved by deducing the relationship between uncertainty components resulting from uncertainty sources and those resulting from the main effects and interaction effects. By the improved three-way ANOVA, Ois decomposed into uncertainty components resulting from the emission scenario (S), GCM (M), and internal climate variability (V). The results reveal that Ois mainly contributed by M in the twenty-first century for precipitation, and by M before the 2060s whereas by S thereafter for temperature. The robustness of the V characterization is explored by investigating the variation of Von the number of included ensemble members. The extent of the underestima-tion of the V contribution is roughly an average of 4% for precipitation and 1% for temperature.
英文关键词	Climate change; Climate prediction; Uncertainty; Climate models; Internal variability
语种	英语
WOS研究方向	Meteorology & Atmospheric Sciences
WOS类目	Meteorology & Atmospheric Sciences
WOS记录号	WOS:001128428800001
来源期刊	JOURNAL OF CLIMATE
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/300625
作者单位	Anhui University of Finance & Economics; China Institute of Water Resources & Hydropower Research; Chongqing Jiaotong University; University of Oslo
推荐引用方式 GB/T 7714	Zhang, Shaobo,Zhou, Zuhao,Peng, Peiyi,et al. A New Framework for Estimating and Decomposing the Uncertainty of Climate Projections[J],2024,37(2).
APA	Zhang, Shaobo,Zhou, Zuhao,Peng, Peiyi,&Xud, Chongyu.(2024).A New Framework for Estimating and Decomposing the Uncertainty of Climate Projections.JOURNAL OF CLIMATE,37(2).
MLA	Zhang, Shaobo,et al."A New Framework for Estimating and Decomposing the Uncertainty of Climate Projections".JOURNAL OF CLIMATE 37.2(2024).