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Jennifer V. Lukovich, Julienne C. Stroeve, Alex Crawford, Lawrence Hamilton, Michel Tsamados, Harry Heorton, and François Massonnet

1. Introduction Over the last four decades, the Arctic Ocean has lost over 40% of its summer sea ice cover (e.g., Stroeve and Notz 2018 ). This loss, together with an increasing desire to utilize the Arctic’s abundant natural resources and potential shipping routes, provides for increased marine access throughout the Arctic Ocean. This access has increased the need for reliable sea ice forecasts, especially at 1–3-month lead times. In response, the Study of Environmental Arctic Change (SEARCH

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Annie P. S. Wong and Stephen C. Riser

1. Introduction Each year, from early autumn to late spring, the heat lost from the sea surface around Antarctica leads to the development of a seasonal sea ice cover whose extent, at its maximum, essentially doubles the surface area of the continent. The presence of sea ice has a direct influence on the physical and biological processes in the ocean in the region. For example, the melting of sea ice in summer results in a stable and shallow surface mixed layer into which solar radiation can

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Xiaojun Yuan, Dake Chen, Cuihua Li, Lei Wang, and Wanqiu Wang

1. Introduction The rapid summer Arctic sea ice retreat has not only been an icon of climate change but has also created more commercial opportunities in the newly opened Arctic waters, such as shipping and oil drilling ( Eicken 2013 ). However, lower summer sea ice cover comes with larger ice variability ( Goosse et al. 2009 ), causing tremendous difficulties in planning, and even threatening, commercial operations in the Arctic. Therefore, skillful sea ice prediction will become a needed

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R. Kwok

1. Introduction In this paper, we provide an updated and expanded 29-yr view of the Arctic sea ice outflow into the Greenland and Barents Seas. This adds to the record of Fram Strait ice flux reported in Kwok and Rothrock (1999 , hereafter KR99 ) and Kwok et al. (2004) , and to the estimates of ice flux into the Barents Sea ( Kwok et al. 2005 ). The examination of ice outflow bears on two problems: the mass balance and ice volume of the Arctic sea ice cover, and the potential impact of this

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Qiang Huang, John Hanesiak, Sergiy Savelyev, Tim Papakyriakou, and Peter A. Taylor

using wind speed, air temperature, and time since last snowfall as predictors. This technique is more practical than other visibility models and achieved a critical success index as high as 66%. In our present research, visibility, snow particle drift density, and standard meteorological data over Arctic sea ice were collected during blowing snow events to investigate the relationship between visibility, snow particle counter readings, and wind speed. The purpose is to provide an empirical set of

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Tamás Kovács, Rüdiger Gerdes, and John Marshall

1. Introduction The wind drives sea surface temperature (SST) anomalies through the modification of air–sea heat fluxes associated with large-scale modes of the atmospheric circulation ( Cayan 1992 ; Marshall et al. 2001 ). The wind stress curl can result in anomalous upwelling, influencing stratification and thus the SST ( Furevik and Nilsen 2005 ). In high latitudes sea ice plays an important role as a mediator of air–sea fluxes ( Meneghello et al. 2018 ). Because of the strong internal

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Russell Blackport and Paul J. Kushner

1. Introduction The rapid retreat of Arctic sea ice ( Stroeve et al. 2012 ) has motivated a number of studies examining how sea ice loss in isolation might impact the atmospheric general circulation. Model simulations can be used to address this fundamental research question in light of the short observational record, internal climate variability, and the difficulty of isolating sea ice variability from other processes (e.g., Magnusdottir et al. 2004 ; Deser et al. 2004 ; Chiang and Bitz

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E. C. van der Linden, R. Bintanja, W. Hazeleger, and C. A. Katsman

2003 ; Cai 2006 ; Ridley et al. 2007 ; Mahlstein and Knutti 2011 ) have all been shown to contribute to Arctic warming, but there is no consensus on their relative magnitude ( Kay et al. 2012 ). The physical processes that contribute most to Arctic warming are not necessarily the same that cause the intermodel spread. In high northern latitudes, sea ice is thought to play a crucial role in amplifying local temperature changes ( Screen and Simmonds 2010 ). Global climate models underestimate the

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Hyo-Seok Park, Andrew L. Stewart, and Jun-Hyeok Son

1. Introduction The Arctic sea ice extent and thickness have been rapidly decreasing in recent decades ( Kwok and Rothrock 2009 ; Laxon et al. 2013 ; Renner et al. 2014 ), but also exhibit substantial interannual variability. In the past few decades, there were several years that marked record lows in the summer sea ice extent: the summers of 2007, 2012, and 2016 highlight the rapidly diminishing Arctic sea ice associated with climate change ( Döscher et al. 2014 ; Cullather et al. 2016

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Evelien Dekker, Richard Bintanja, and Camiel Severijns

1. Introduction The Arctic is one of the regions most affected by climate change ( Collins et al. 2013 ). Observations and modeling studies show that in the Arctic, temperature changes 2–3 times faster than the global mean ( Holland and Bitz 2003 ; Serreze and Barry 2011 ). This phenomenon, called Arctic amplification, is driven by climate feedbacks, in which sea ice plays a crucial role ( Screen and Simmonds 2010 ). Sea ice is the primary driver of Arctic climate variability and change ( van

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