Contrasting sensitivity of air temperature trends to surface soil temperature trends between climate models and reanalyses (vol 7, 43, 2024)

被引:0
作者
Qiao, Yumeng [1 ]
Wang, Guojie [2 ]
Hagan, Daniel Fiifi Tawia [1 ]
Sian, Kenny Thiam Choy Lim Kam
Chen, Liangzhi [1 ,2 ]
Aalto, Juha
Li, Shijie [1 ]
Zou, Xiao [1 ]
Lu, Jiao
机构
[1] Swiss Fed Inst Forest Snow & Landscape Res, Birmensdorf, Switzerland
[2] Swiss Fed Res Inst WSL, Dynam Macroecol, Birmensdorf, Switzerland
来源
NPJ CLIMATE AND ATMOSPHERIC SCIENCE | 2024年 / 7卷 / 01期
基金
中国国家自然科学基金;
关键词
D O I
10.1038/s41612-024-00647-9
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
The sensitivity strength of air temperature (T) to surface soil temperature (sST) (namely beta hereafter) constitutes a significant factor in how global climate models quantify changes in the climate. This study examines how this sensitivity is represented in the CMIP6 models. Results show regional differences and even contrasts in the beta trends at interannual scales between climate models and two reanalysis products during 1980-2014. At high latitudes in the Northern Hemisphere (NH), beta is stronger in the CMIP6 models than in the reanalysis data. Additionally, the beta trends differ between the CMIP6 and reanalysis data, which may be related to the different precipitation (PR) and soil water availability (PR-ET) trends between the models. In the regions of increasing beta intensity at high latitudes in the NH, sST is more sensitive to PR and PR-ET. Consequently, increasing PR and PR-ET leads to slower sST changes, potentially making beta intensity stronger in CMIP6 models. However, in the reanalysis data, decreases in PR and PR-ET accelerate sST changes, leading to a weakening of the beta intensity. A resulting implication is that beta, based on high-emission scenarios, shows a stronger trend during 2015-2100, although this trend could potentially be overestimated. The findings contribute to a better understanding of the sensitivity of T to sST and facilitate the assessment of energy exchange between the land surface and the atmosphere in climate models.
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[1]  
Qiao YM, 2024, NPJ CLIM ATMOS SCI, V7, DOI 10.1038/s41612-024-00588-3