Multi-source forcing effects analysis using Liang–Kleeman information flow method and the community atmosphere model (CAM4.0)
Multi-source forcing effects analysis using Liang–Kleeman information flow method and the community atmosphere model (CAM4.0)
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基于Liang-Kleeman信息流法和群落氛围模型的多源强迫效应分析(CAM4.0)
DOI:
10.1007/s00382-019-04914-x
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发表时间:
2019-11
期刊:
影响因子:
4.6
通讯作者:
HaoKun Bai
中科院分区:
文献类型:
--
作者:
ShunYu Jiang;HaiBo Hu;Ning Zhang;LiPing Lei;HaoKun Bai
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.
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