气候变化领域集成服务门户(CCPortal): Multi-source forcing effects analysis using Liang–Kleeman information flow method and the community atmosphere model (CAM4.0)

CCPortal

DOI	10.1007/s00382-019-04914-x
	Multi-source forcing effects analysis using Liang–Kleeman information flow method and the community atmosphere model (CAM4.0)
	Jiang S.Y.; Hu H.B.; Zhang N.; Lei L.P.; Bai H.K.
发表日期	2019
ISSN	0930-7575
起始页码	6035
结束页码	6053
卷号	53 期号:2020-09-10
英文摘要	To understand the individual influences of the land cover, sea temperature, sea ice and carbon dioxide concentration on the global climate, sensitive experiments using the General Atmospheric Circulation Model 4.0 are designed to compare with the observation in this study. Firstly, through the analysis of Liang–Kleeman information flow method, it is straightforward that the pronounced causal relationships exist from these forcing to air temperature. In numerical experiments, the temperature is influenced by the albedo and atmospheric dynamic process. More detailed, in winter, the changes of each forcing will cause the positive Pacific-North American Pattern (PNA) phase, which makes the North American colder. The negative North Atlantic Oscillation (NAO) phase caused by the changes of CO2 and sea ice induces cold winter over the Europe. This coincides with the extreme cold weather in Europe and North America in 2018. Whereas in summer, all forcings cause positive Arctic Oscillation (AO) phase, resulting in the most northern hemisphere warmer. It is noteworthy that for precipitation, the changes of each forcing increase winds from the sea surface to the land in East Asia, so the precipitable water increases, thus the precipitation overall increases. However, when CO2 changes, the precipitation decreases due to the lack of dynamic conditions in some areas. © 2019, The Author(s).
英文关键词	Atmospheric teleconnection; CAM4.0; East Asian precipitation; Multi-source forcing; Temperature change; The Liang–Kleeman information flow
语种	英语
scopus关键词	air temperature; atmospheric forcing; atmospheric modeling; carbon dioxide; global climate; global warming; land cover; precipitation (climatology); sea ice; sea surface temperature; teleconnection; Europe; Far East; North America
来源期刊	Climate Dynamics
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/145879
作者单位	CMA-NJU Joint Laboratory for Climate Prediction Studies, School of Atmospheric Science, Instituted for Climate and Global Change Research, Nanjing University, Nanjing, 210093, China; Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, 100094, China; KLME & CIC-FEMD, Nanjing University of Information Science and Technology, Nanjing, China
推荐引用方式 GB/T 7714	Jiang S.Y.,Hu H.B.,Zhang N.,等. Multi-source forcing effects analysis using Liang–Kleeman information flow method and the community atmosphere model (CAM4.0)[J],2019,53(2020-09-10).
APA	Jiang S.Y.,Hu H.B.,Zhang N.,Lei L.P.,&Bai H.K..(2019).Multi-source forcing effects analysis using Liang–Kleeman information flow method and the community atmosphere model (CAM4.0).Climate Dynamics,53(2020-09-10).
MLA	Jiang S.Y.,et al."Multi-source forcing effects analysis using Liang–Kleeman information flow method and the community atmosphere model (CAM4.0)".Climate Dynamics 53.2020-09-10(2019).