Attribution of Biases of Interhemispheric Temperature Contrast in CMIP6 Models

被引:0
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作者
Shiyan ZHANG [1 ]
Yongyun HU [1 ]
Jiankai ZHANG [2 ]
Yan XIA [3 ]
机构
[1] Laboratory for Climate and Ocean-Atmosphere Studies, Department of Atmospheric and Oceanic Sciences,School of Physics, Peking University
[2] College of Atmospheric Sciences, Lanzhou University
[3] School of Systems Science, Beijing Normal University
基金
中国国家自然科学基金;
关键词
D O I
暂无
中图分类号
P423 [大气温度];
学科分类号
0706 ; 070601 ;
摘要
One of the basic characteristics of Earth’s modern climate is that the Northern Hemisphere(NH) is climatologically warmer than the Southern Hemisphere(SH). Here, model performances of this basic state are examined using simulation results from 26 CMIP6 models. Results show that the CMIP6 models underestimate the contrast in interhemispheric surface temperatures on average(0.8 K for CMIP6 mean versus 1.4 K for reanalysis data mean), and that there is a large intermodel spread, ranging from -0.7 K to 2.3 K. A box model energy budget analysis shows that the contrast in interhemispheric shortwave absorption at the top of the atmosphere, the contrast in interhemispheric greenhouse trapping, and the crossequatorial northward ocean heat transport, are all underestimated in the multimodel mean. By examining the intermodel spread, we find intermodel biases can be tracked back to biases in midlatitude shortwave cloud forcing in AGCMs. Models with a weaker interhemispheric temperature contrast underestimate the shortwave cloud reflection in the SH but overestimate the shortwave cloud reflection in the NH, which are respectively due to underestimation of the cloud fraction over the SH extratropical ocean and overestimation of the cloud liquid water content over the NH extratropical continents.Models that underestimate the interhemispheric temperature contrast exhibit larger double ITCZ biases, characterized by excessive precipitation in the SH tropics. Although this intermodel spread does not account for the multimodel ensemble mean biases, it highlights that improving cloud simulation in AGCMs is essential for simulating the climate realistically in coupled models.
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页码:325 / 340
页数:16
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