气候变化领域集成服务门户(CCPortal): Uncovering the Forced Climate Response from a Single Ensemble Member Using Statistical Learning

CCPortal

DOI	10.1175/JCLI-D-18-0882.1
	Uncovering the Forced Climate Response from a Single Ensemble Member Using Statistical Learning
	Sippel, Sebastian; Meinshausen, Nicolai; Merrifield, Anna; Lehner, Flavio; Pendergrass, Angeline G.; Fischer, Erich; Knutti, Reto
发表日期	2019-09-01
ISSN	0894-8755
EISSN	1520-0442
卷号	32 期号:17 页码:5677-5699
英文摘要	Internal atmospheric variability fundamentally limits predictability of climate and obscures evidence of anthropogenic climate change regionally and on time scales of up to a few decades. Dynamical adjustment techniques estimate and subsequently remove th
关键词	Atmospheric circulation Climate change Climate prediction Regression analysis Statistical techniques Climate variability
学科领域	Meteorology & Atmospheric Sciences
语种	英语
WOS记录号	WOS:000480264800001
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/81792
作者单位	Swiss Fed Inst Technol, Inst Atmospher & Climate Sci, Zurich, Switzerland
推荐引用方式 GB/T 7714	Sippel, Sebastian,Meinshausen, Nicolai,Merrifield, Anna,et al. Uncovering the Forced Climate Response from a Single Ensemble Member Using Statistical Learning[J],2019,32(17):5677-5699.
APA	Sippel, Sebastian.,Meinshausen, Nicolai.,Merrifield, Anna.,Lehner, Flavio.,Pendergrass, Angeline G..,...&Knutti, Reto.(2019).Uncovering the Forced Climate Response from a Single Ensemble Member Using Statistical Learning.JOURNAL OF CLIMATE,32(17),5677-5699.
MLA	Sippel, Sebastian,et al."Uncovering the Forced Climate Response from a Single Ensemble Member Using Statistical Learning".JOURNAL OF CLIMATE 32.17(2019):5677-5699.