气候变化领域集成服务门户(CCPortal): Quantifying the anthropogenic greenhouse gas contribution to the observed spring snow-cover decline using the CMIP6 multimodel ensemble

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DOI	10.1175/JCLI-D-20-0002.1
	Quantifying the anthropogenic greenhouse gas contribution to the observed spring snow-cover decline using the CMIP6 multimodel ensemble
	Paik S.; Min S.-K.
发表日期	2020
ISSN	0894-8755
起始页码	9261
结束页码	9269
卷号	33 期号:21
英文摘要	This study conducts a detection and attribution analysis of the observed changes in boreal spring snow-cover extent (SCE) for an extended period of 1925-2019 for early spring (March and April) and 1970-2019 for late spring (May and June) using updated observations and multimodel simulations from phase 6 of the Coupled Model Intercomparison Project (CMIP6). The observed and simulated SCE changes over the Northern Hemisphere (NH), Eurasia, and North America are compared using an optimal fingerprinting technique. Detection results indicate that anthropogenic influences are robustly detected in the observed SCE decrease over NH and the continental regions, in separation from natural forcing influences. In contrast to previous studies, anthropogenic response in the early spring SCE shows a consistent magnitude with observations, due to an extension of the time period to 2019. It is demonstrated for the first time that the greenhouse gas (GHG) influence is robustly detected in separation from anthropogenic aerosol and natural forcing influences, and that most of the observed spring SCE decrease is attributable to GHG influences. The observed SCE decline is also found to be closely associated with the surface warming over the corresponding extratropical lands. Our first quantification of GHG contribution to the observed SCE changes has important implications for reliable future projections of the SCE changes and its hydrological and ecological impacts. © 2020 American Meteorological Society.
英文关键词	Greenhouse gases; Anthropogenic aerosols; Anthropogenic influence; Coupled Model Intercomparison Project; Detection and attributions; Greenhouse gas contributions; Multi-model ensemble; Multi-Model Simulations; Optimal fingerprinting technique; Snow; aerosol composition; aerosol formation; anthropogenic effect; carbon emission; climate modeling; ensemble forecasting; greenhouse gas; snow cover; spring (season); Eurasia; North America
语种	英语
来源期刊	Journal of Climate
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/171063
作者单位	Division of Environmental Science and Engineering, Pohang University of Science and Technology, Pohang, South Korea
推荐引用方式 GB/T 7714	Paik S.,Min S.-K.. Quantifying the anthropogenic greenhouse gas contribution to the observed spring snow-cover decline using the CMIP6 multimodel ensemble[J],2020,33(21).
APA	Paik S.,&Min S.-K..(2020).Quantifying the anthropogenic greenhouse gas contribution to the observed spring snow-cover decline using the CMIP6 multimodel ensemble.Journal of Climate,33(21).
MLA	Paik S.,et al."Quantifying the anthropogenic greenhouse gas contribution to the observed spring snow-cover decline using the CMIP6 multimodel ensemble".Journal of Climate 33.21(2020).