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Tomoko Nitta, Kei Yoshimura, and Ayako Abe-Ouchi

, respectively]. We always applied the wetland scheme everywhere except in land ice grids. The spatial resolution is T42, which corresponds to a gridcell size of about 310 km at the equator, and the model has 40 levels in the vertical. We used climatological monthly sea surface temperature (SST) and sea ice distributions from 1979 to 1996 as boundary conditions. We conducted a 30-yr simulation with zero surface storage as an initial condition and excluded the first 10 years from the analysis as a spinup. 2

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Ayumi Fujisaki-Manome, Lindsay E. Fitzpatrick, Andrew D. Gronewold, Eric J. Anderson, Brent M. Lofgren, Christopher Spence, Jiquan Chen, Changliang Shao, David M. Wright, and Chuliang Xiao

modeled λE and H , we tested three different meteorological forcings that drove FVCOM and three different algorithms to calculate λE and H within FVCOM, yielding a total of nine FVCOM runs. The selected flux algorithms were the Coupled Ocean–Atmosphere Response Experiment (COARE)-Met Flux Algorithm ( Fairall et al. 1996a , b ; https://coaps.fsu.edu/COARE/flux_algor/ ); the method built in the Los Alamos Sea Ice Model, hereafter referred to as J99 ( Jordan et al. 1999 ; Hunke et al. 2015

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Daqing Yang, Baisheng Ye, and Alexander Shiklomanov

1. Introduction Discharge from northern-flowing rivers is the primary freshwater source to the Arctic Ocean. Studies show that both the amount and the timing of freshwater inflow to the ocean systems are important to ocean circulation, salinity, and sea ice dynamics ( Aagaard and Carmack 1989 ; Macdonald 2000 ; Peterson et al. 2002 ). Climate over Arctic regions has experienced significant changes during the past few decades. For instance, climate changes over Siberian regions include

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Xiaogang Shi, Matthew Sturm, Glen E. Liston, Rachel E. Jordan, and Dennis P. Lettenmaier

from layered snowpacks over land ( Mätzler et al. 1999 ) and sea ice ( Powell et al. 2006 ). The input data to MEMLS includes snow temperature (K), volumetric liquid water content (0–1), snow density (kg m −3 ), snow salinity (parts per thousand, ppt), and correlation length (used to characterize the size of the snow particles within a snow layer) for each of a number of user-defined snow layers. The snow grain size in SNTHERM is the optical grain diameter ( d o ; Jordan 1991 ), which has a linear

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Louise Mimeau, Michel Esteves, Hans-Werner Jacobi, and Isabella Zin

resources management. Precipitation in the HKH region is influenced by two major synoptical situations: the summer Indian monsoon system, which starts in the Bay of Bengal and progresses toward the Himalayan mountain range, bringing heavy precipitation between June and September, and the westerlies originating from the Mediterranean, Arabian, or Caspian Seas and bringing precipitation during winter ( Lang and Barros 2004 ; Wang 2006 ; Bookhagen and Burbank 2010 ). However, at high elevations, due to

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Andrea Camplani, Daniele Casella, Paolo Sanò, and Giulia Panegrossi

water within the snowpack strongly enhances the absorption at the expense of the volume scattering ( Rott and Nagler 1995 ; Amlien 2008 ). Hewison and English (1999) developed a model representing the microwave emissivity spectra of sea ice and snow cover obtained by airborne measurements. Different behaviors have been observed for different types of snowpacks, with an evident decrease of the emissivity with increasing frequency (within MW) for dry snow, and a high and stable emissivity for fresh

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Marc Stieglitz, Agnès Ducharne, Randy Koster, and Max Suarez

source for the yearly ground moisture budget ( Aguado 1985 ). Further, at high latitudes the magnitude and timing of spring snowmelt water delivered to the Arctic Ocean affect the stability of the ocean’s surface layer and thereby affect ocean circulation and seasonal sea ice formation ( Mysak and Venegas 1998 ). Because a snowpack is thermally insulating and limits the otherwise efficient heat exchange between the ground and the atmosphere, it controls the evolution of wintertime ground temperatures

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M. Diakhaté, B. Rodríguez-Fonseca, I. Gómara, E. Mohino, A. L. Dieng, and A. T. Gaye

calculated by removing the seasonal mean. The obtained time series are standardized and high-pass filtered (Lanczos; 8-yr cutoff period) to keep only with interannual variability (one data point per year). The resultant time series are considered as our rainfall indices along the whole study. The SST dataset from the Met Office Hadley Centre Sea Ice and Sea Surface Temperature dataset (HadISST) is used and regressed on precipitation indices to search for possible oceanic teleconnections. The SST data

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Liming Zhu, Junzhi Liu, A-Xing Zhu, Meiling Sheng, and Zheng Duan

) pointed out that the low-level convergence by land/sea in southern China was the main reason for the prevailing nocturnal rainfall on the windward slope of the mountainous area in the Pearl River Delta (PRD) region. But over large-scale mountains and adjacent plains or basins in the west and north of China, many researchers also pointed out that propagation of the diurnal rainfall peak from late afternoon to night is strongly associated with the thermally driven regional mountain–plains solenoid (MPS

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T. Zhang, T. Scambos, T. Haran, L. D. Hinzman, Roger G. Barry, and D. L. Kane

1. Introduction The surface energy balance at high latitudes is in large part determined by the surface albedo. It has long been hypothesized that a positive feedback relationship exists between changes in surface albedo associated with changes in snow and ice conditions (i.e., areal extent, thickness, distribution, snow grain size and wetness, lead fraction, and melt pond characteristics over sea ice) and local climate ( Kellog 1973 ; Shine and Henderson-Sellers 1985 ; Curry et al. 1995

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