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Xiaogang Shi, Stephen J. Déry, Pavel Ya. Groisman, and Dennis P. Lettenmaier

1. Introduction Snow cover is an important climatic and hydrologic land surface variable. Its long-term variations serve as both indicators and controls of climate change over much of the Northern Hemisphere land area ( Gray and Male 1981 ; Groisman et al. 1994 ; Frei and Robinson 1999 ; Robinson and Frei 2000 ). Therefore, spatial and temporal variations of snow cover across the Northern Hemisphere have attracted considerable scientific attention. Many studies have used the visible

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Noah Knowles

1. Introduction For much of the United States, snow on the ground is the defining feature of the winter season. The local impact of snow cover ranges from traffic disruption to providing essential ecological services to a wide variety of flora and fauna ( Jones et al. 2013 ). In many regions, snowpacks are integral to water supply and management strategies, while also presenting the potential for hazards such as infrastructure damage and flooding. Snow cover also alters surface albedo

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Benjamin F. Zaitchik and Matthew Rodell

1. Introduction Average monthly snow cover in the Northern Hemisphere varies from 7% of all land area to more than 40%, making snow cover the fastest varying large-scale surface feature on Earth ( Chang et al. 1990 ; Hall 1988 ). This variability has a dramatic impact on surface moisture and energy fluxes. Snow insulates the ground beneath, moderating soil temperatures during winter ( Decker et al. 2003 ). Because of its high albedo, snow significantly reduces the absorption of radiation at

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Shinji Matsumura and Koji Yamazaki

1. Introduction The climate system of northern latitudes is a dynamic and interactive system involving couplings between atmospheric, oceanic, and land surface processes. Arctic and subarctic climate systems develop in response to a variety of meteorological conditions, related to both snow and ice. Snow cover and the presence of sea ice are two factors that impact climate and exhibit interannual temporal and spatial variations. Summer sea ice cover in the Arctic Ocean has experienced an

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Samantha Pullen, Clive Jones, and Gabriel Rooney

1. Introduction Snow is an extremely important component of the land surface system, substantially affecting the radiative and hydrological properties of the surface and consequently the way it interacts with the atmosphere. Most important is that snow cover dramatically increases the land surface albedo from between 0.05 and 0.4 (typical for bare soil and vegetation) to up to 0.9 for pure snow ( Nolin and Liang 2000 ), which has a huge effect on diabatic heating. In hydrological terms, water

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Zhixiang Xiao and Anmin Duan

1. Introduction Snow cover exerts a significant influence on local surface radiation budgets and hydrological fluxes through its high reflectivity, high emissivity, and low thermal conductivity ( Yasunari et al. 1991 ; Mote 2008 ; Xu and Dirmeyer 2013 ). However, in addition to local effects, snow cover might also impact downstream climate systems ( Xu et al. 2012 ) and the global climate ( Barnett et al. 1988 , 1989 ). Eurasian snow cover has long been thought to significantly influence the

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Jiarui Dong, Mike Ek, Dorothy Hall, Christa Peters-Lidard, Brian Cosgrove, Jeff Miller, George Riggs, and Youlong Xia

contain large errors attributable to land surface complexities and temporally frequent snowmelt processes in the western United States (e.g., Tait and Armstrong 1996 ; Rodell et al. 2004 ; Foster et al. 2005 ; Dong et al. 2005 ; Tong et al. 2010 ), the 500-m daily Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 5 (C5) snow cover area (SCA) product has been widely used as an important constraint on snowpack processes in land surface and hydrological models. Assimilation

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Qigang Wu, Haibo Hu, and Lujun Zhang

1. Introduction The significant impact of Siberian autumn snow cover anomalies on the wintertime Arctic Oscillation/North Atlantic Oscillation (AO/NAO)-like atmospheric circulation in the North Atlantic sector has been identified in observations (e.g., Cohen and Entekhabi 1999 ; Saito et al. 2001 ) and through numerical modeling (e.g., Gong et al. 2003 ; Fletcher et al. 2009 , hereafter F09 ). There are also indications that Eurasian snow cover influences atmospheric circulation over Asia

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P. Ducharme, A. Houdayer, Y. Choquette, B. Kapfer, and J. P. Martin

. This is the type of function [Eq. (5) ] used so far to extract SWE measurements from data collected by airborne gamma detectors: where N is the counts of gammas detected and α is the exponential coefficient. In Fig. 3 , we present the results of the numerical simulations (dotted line) over a totally dry soil for varying values of SWE. The counts for the different values of SWE are plotted as ratios to the counts ( N o ) detected in absence of a snow cover and soil moisture. An exponential of

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Hai Lin and Zhiwei Wu

), other lower boundary forcing mechanisms need to be investigated to further improve seasonal predictions ( Wu et al. 2011 ). Of these, one of the most important is likely to be snow cover, as an anomaly in snow cover is associated with changes in solar radiation absorption and surface heat fluxes. The effect of Eurasian snow cover on global climate has long been noticed (e.g., Gong et al. 2002 , 2003 , 2004 ; Fletcher et al. 2009 ; Sobolowski et al. 2010 ). A possible relation between the

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