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Chenghai Wang, Kai Yang, Yiling Li, Di Wu, and Yue Bo

). Changes of snow in the Northern Hemisphere ( Déry and Brown 2007 ; Brown and Mote 2009 ; McCabe and Wolock 2010 ; Brown and Robinson 2011 ; Shi and Wang 2015 ) have greatly influenced the regional and global climate ( Cohen and Entekhabi 1999 ; Kumar and Yang 2003 ) and caused remote precipitation anomalies ( Chen et al. 2008 ; Ding and Gao 2015 ). Numerous studies have demonstrated that changes in the spatiotemporal distribution of snow cover over Eurasia in response to a changing climate are

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Yong-Keun Lee, Cezar Kongoli, and Jeffrey Key

1. Introduction Snow is one of the most dynamic hydrological variables on the earth’s surface and is the cryospheric component with the largest seasonal variation in spatial extent. Over Northern Hemisphere lands, snow cover ranges from about 45.2 × 10 6 km 2 in January to 1.9 × 10 6 km 2 in August ( Barry et al. 2007 ). Because of its dramatic seasonal variation and high reflectivity, snow plays a key role in the global energy and water budget ( Barry et al. 2007 ; IPCC 2007 ). Snow

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Dorothy K. Hall, Son V. Nghiem, Ignatius G. Rigor, and Jeffrey A. Miller

in March and April of 2012 to investigate impacts of Arctic sea ice reduction on chemical processes, transport, and distribution of bromine, ozone, and mercury from snow-covered sea ice and land surfaces ( Nghiem et al. 2013a , b ; Moore et al. 2014 ). Temperature is a key factor in chemical reactions ( Tarasick and Bottenheim 2002 ), and an increase in temperature fluctuations may lead to more episodes of the halogen chemical process known as bromine explosion ( Wennberg 1999 ) and more

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Jie Zhang, Qianrong Ma, Haishan Chen, Siwen Zhao, and Zhiheng Chen

Niño enhanced the water vapor supply from the Arabian Sea to central Asia via the Hadley cell. The Eurasian snow cover in the preceding autumn influenced the wintertime Arctic Oscillation and the Northern Hemispheric Rossby wave trough over central Asia and led to more precipitation. However, there is limited research on the precipitation in those drylands and related forcing beyond the interannual time scale. Therefore, it is necessary to determine whether the increased precipitation will remain

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Jicheng Liu, Curtis E. Woodcock, Rae A. Melloh, Robert E. Davis, Ceretha McKenzie, and Thomas H. Painter

1. Introduction Snow, because of its unique properties such as high albedo and low thermal conductivity, affects land surface radiation budgets and water balance ( Yang et al. 1999 ). Significant gains have been made in snow cover mapping using remotely sensed data in recent decades, but the presence of forests continues to present challenges ( Simpson et al. 1998 ; Hall et al. 1998 ; Hall et al. 2002 ; Dozier and Painter 2004 ). An understanding of the manner in which forest canopies

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Chad W. Thackeray, Christopher G. Fletcher, Lawrence R. Mudryk, and Chris Derksen

1. Introduction Seasonal snow cover is a crucial component of the climate system, with major impacts on the surface energy budget and water balance. At its peak, snow covers approximately 47 × 10 6 km 2 of Northern Hemisphere (NH) land (about 40% of the land area) each year ( Hall 1988 ; Robinson and Frei 2000 ). The reflective properties of snow mean that it has a very strong influence on land surface albedo, controlling its seasonal evolution. This high albedo has a cooling influence on

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Guillaume Gastineau, Javier García-Serrano, and Claude Frankignoul

-Serrano et al. 2015 ; Koenigk et al. 2016 ; King et al. 2016 ) and Eurasian snow cover extent (SCE, e.g., Cohen and Entekhabi 1999 ; Cohen et al. 2007 ; Cohen and Jones 2011 ) have some influence on the atmosphere during winter. Such influence may account for an improvement in skill of long-range prediction due to continental snow ( Jeong et al. 2013 ; Orsolini et al. 2013 ) and sea ice ( Scaife et al. 2014 ) initialization and improved physics ( Riddle et al. 2013 ) in current forecast systems

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Stephen J. Vavrus, Fuyao Wang, Jonathan E. Martin, Jennifer A. Francis, Yannick Peings, and Julien Cattiaux

the extratropical circulation induced by AA, as hypothesized by FV12 , but it closely conforms to the proposed mechanisms via the loss of sea ice and snow cover. Consistent with expectations, the simulated AA in these experiments promotes marine-based ridging over high latitudes during winter and terrestrial-based ridging over the northern extratropics during summer, both of which cause weaker westerlies aloft on their equatorward flanks. FV12 further hypothesized that the weaker circulation

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D. S. Wilks

predictor data for seasonal forecasts, other persistent surface conditions may also contribute skill. In particular, autumn Eurasian snow cover has been found to provide skill in statistical forecasts of North American winter temperatures ( Foster et al. 1983 ; Cohen and Fletcher 2007 ; Lin and Wu 2011 ; Brands 2013 ). The physical basis for this predictive skill appears to be the connection between Eurasian snow cover and the Arctic Oscillation ( Cohen and Entekhabi 1999 ; Cohen et al. 2007 ; Gong

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Juan Dou and Zhiwei Wu

1. Introduction As the third pole of Earth, the Tibetan Plateau (TP) is a huge cooling source in the midtroposphere in the cold seasons and a tremendous heating source in the warm seasons ( Yeh et al. 1957 ; Ye and Wu 1998 ). TP snow cover (TPSC) greatly affects the thermal characteristics of the plateau through its high albedo and low thermal conductivity ( Luo and Yanai 1984 ; Namias 1985 ; Cohen and Rind 1991 ; Xu and Dirmeyer 2013 ), and then exerts a huge influence on the global and

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