Assessments of the Northern Hemisphere snow cover response to 1.5 and 2.0 °C warming

被引:15
|
作者
Wang, Aihui [1 ]
Xu, Lianlian [1 ]
Kong, Xianghui [1 ]
机构
[1] Chinese Acad Sci, Inst Atmospher Phys, Nansen Zhu Int Res Ctr, Beijing 100029, Peoples R China
关键词
INTERACTIVE MULTISENSOR SNOW; COMMUNITY LAND MODEL; VARIABILITY; IMPACTS; TEMPERATURE; ICE; SIMULATIONS; CYCLES; TRENDS; CMIP5;
D O I
10.5194/esd-9-865-2018
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
The 2015 Paris Agreement set a goal to pursue a global mean temperature below 1.5 degrees C and well below 2 degrees C above preindustrial levels. Although it is an important surface hydrology variable, the response of snow under different warming levels has not been well investigated. This study provides a comprehensive assessment of the snow cover fraction (SCF) and snow area extent (SAE), as well as the associated land surface air temperature (LSAT) over the Northern Hemisphere (NH) based on the Community Earth System Model Large Ensemble project (CESM-LE), the CESM 1.5 and 2 degrees C projects, and the CMIP5 historical RCP2.6 and RCP4.5 products. The results show that the spatiotemporal variations in those modeled products are grossly consistent with observations. The projected SAE magnitude change in RCP2.6 is comparable to that in 1.5 degrees C, but lower than that in 2 degrees C. The snow cover differences between 1.5 and 2 degrees C are prominent during the second half of the 21st century. The signal-to-noise ratios (SNRs) of both SAE and LSAT over the majority of land areas are greater than 1, and for the long-term period, the dependences of SAE on LSAT changes are comparable for different ensemble products. The contribution of an increase in LSAT to the reduction of snow cover differs across seasons, with the greatest occurring in boreal autumn (49-55 %) and the lowest occurring in boreal summer (10-16 %). The snow cover uncertainties induced by the ensemble variability are invariant over time across CESM members but show an increase in the warming signal between the CMIP5 models. This feature reveals that the physical parameterization of the model plays the predominant role in long-term snow simulations, while they are less affected by internal climate variability.
引用
收藏
页码:865 / 877
页数:13
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