Quantifying the Uncertainty in Historical and Future Simulations of Northern Hemisphere Spring Snow Cover

被引:42
|
作者
Thackeray, Chad W. [1 ]
Fletcher, Christopher G. [1 ]
Mudryk, Lawrence R. [2 ]
Derksen, Chris [3 ]
机构
[1] Univ Waterloo, Dept Geog & Environm Management, 200 Univ Ave W, Waterloo, ON N2L 3G1, Canada
[2] Univ Toronto, Dept Phys, Toronto, ON, Canada
[3] Environm & Climate Change Canada, Div Climate Res, Toronto, ON, Canada
基金
加拿大自然科学与工程研究理事会;
关键词
SURFACE AIR-TEMPERATURE; CLIMATE-CHANGE; SEA-ICE; INTERNAL VARIABILITY; WATER EQUIVALENT; ALBEDO FEEDBACK; MODEL; CMIP5; AMPLIFICATION; ASSIMILATION;
D O I
10.1175/JCLI-D-16-0341.1
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
Projections of twenty-first-century Northern Hemisphere (NH) spring snow cover extent (SCE) from two climate model ensembles are analyzed to characterize their uncertainty. Phase 5 of the Coupled Model Intercomparison Project (CMIP5) multimodel ensemble exhibits variability resulting from both model differences and internal climate variability, whereas spread generated from a Canadian Earth System Model-Large Ensemble (CanESM-LE) experiment is solely a result of internal variability. The analysis shows that simulated 1981-2010 spring SCE trends are slightly weaker than observed (using an ensemble of snow products). Spring SCE is projected to decrease by 23.7% +/- 1.1% decade 21 within the CMIP5 ensemble over the twenty-first century. SCE loss is projected to accelerate for all spring months over the twenty-first century, with the exception of June (because most snow in this month has melted by the latter half of the twenty-first century). For 30-yr spring SCE trends over the twenty-first century, internal variability estimated from CanESM-LE is substantial, but smaller than intermodel spread from CMIP5. Additionally, internal variability in NH extratropical land warming trends can affect SCE trends in the near future (R-2 = 0.45), while variability in winter precipitation can also have a significant (but lesser) impact on SCE trends. On the other hand, a majority of the intermodel spread is driven by differences in simulated warming (dominant in March-May) and snow cover available for melt (dominant in June). The strong temperature-SCE linkage suggests that model uncertainty in projections of SCE could be potentially reduced through improved simulation of spring season warming over land.
引用
收藏
页码:8647 / 8663
页数:17
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