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Gwendal Rivière, Alexandre Laîné, Guillaume Lapeyre, David Salas-Mélia, and Masa Kageyama

on the long-term average, respectively. The aim of our study is not only to investigate the nature of Rossby upper-tropospheric wave-breaking processes at the LGM in comparison with the present climate, but also to use this approach to better understand the extratropical low-frequency atmospheric variability such as the Arctic Oscillation (AO) or NAO at the LGM. Most of the LGM numerical studies have focused on the climatological means of the atmospheric circulation and the storm tracks, but much

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Hainan Gong, Lin Wang, Wen Chen, Renguang Wu, Wen Zhou, Lin Liu, Debashis Nath, and Xiaoqing Lan

1. Introduction The Arctic Oscillation (AO) is the most dominant low-frequency mode of atmospheric variability in the extratropical Northern Hemisphere ( Thompson and Wallace 1998 ). It is also known as the northern annular mode because of its annular structure in the sea level pressure (SLP) field ( Thompson and Wallace 2000 ). Meanwhile, since the North Atlantic Oscillation (NAO; Hurrell 1995 ) index has high consistency with the AO index, the AO and NAO are generally accepted as the same

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Shangfeng Chen, Wen Chen, and Renguang Wu

–Southern Oscillation (ENSO) cycle ( Wang et al. 2000 ; Wu et al. 2003 ; Huang et al. 2004 ; Chen et al. 2013 ), western Pacific warm pool ( Nitta 1987 ; Huang and Li 1987 ; Huang and Sun 1992 ), Indian summer monsoon ( Wu 2002 ), and spring Arctic sea ice concentration ( Wu et al. 2009b ). Several recent studies have found that the spring Arctic Oscillation (AO) is a very important precursory factor that could significantly influence the interannual variability of the following EASM (e.g., Gong et al. 2002

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James E. Overland and Muyin Wang

1. Introduction Several authors have commented on major individual negative Arctic Oscillation (AO) events in recent years that were associated with severe cold temperatures in midlatitudes over North America and parts of Europe ( Cattiaux et al. 2010 ; L’Heureux et al. 2010 ). Single large January negative AO in 2010 and positive AO in 2012 events were discussed by Santos et al. (2013) . L’Heureux et al. (2010) note the largest negative AO event during 2009 in a 60-yr record. Although by

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G. I. Belchansky, D. C. Douglas, and N. G. Platonov

motion vectors) and subtracting the volume of all pixels that moved out of the study area. Results of these calculations are shown in Fig. 5 . Annually, ice volume increased during the winter with peak monthly accumulations reaching upward of 1000 km 3 in the early winter (October and November) and commensurate peak volume losses during in May and June ( Fig. 5a ). The seasonal oscillation of ice volume in the Arctic Ocean ranged from average lows that prevailed in August (10.76 ± 1.15 × 10 3 km 3

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Maarten H. P. Ambaum, Brian J. Hoskins, and David B. Stephenson

1. Introduction Following the earlier studies of Lorenz (1950) and Kutzbach (1970) , Thompson and Wallace (1998, 2000) and Thompson et al. (2000) have given impressive evidence for the importance of the pattern of variability they refer to as the Arctic oscillation (AO). This pattern is highly correlated with the North Atlantic oscillation (NAO) pattern ( Walker and Bliss 1932 ), which has also been subject of much interest in recent years (e.g., Wallace and Gutzler 1981 ; Hurrell 1995

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Karen L. Smith, Lorenzo M. Polvani, and L. Bruno Tremblay

( Petty et al. 2017 ; Bushuk et al. 2017 ; Chen et al. 2017 ; Schröder et al. 2014 ; Stroeve et al. 2014b ; Tietsche et al. 2013 ). Among other factors, tropospheric circulation anomalies have been shown to be predictive of interannual variability in Arctic sea ice ( Rigor et al. 2002 ; Ogi et al. 2010 ). Specifically, studies have demonstrated an anticorrelation between the leading modes of extratropical atmospheric variability, the Arctic Oscillation (AO) and the North Atlantic Oscillation

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Alan Condron, Peter Winsor, Chris Hill, and Dimitris Menemenlis

Gerdes 2007 ). The atmospheric circulation of the Arctic is dominated by the North Atlantic Oscillation(NAO)/Arctic Oscillation (AO) ( Hurrell 1995 ; Thompson and Wallace 1998 ), which switched from its most extreme negative state in the 1960s to its most extreme prolonged positive state in the early 1990s ( Fig. 1a ). 1 Häkkinen and Proshutinsky (2004) and Köberle and Gerdes (2007) both simulated the Arctic freshwater budget from the 1950s to the early 2000s using two different coupled ocean

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Lei Cai, Vladimir A. Alexeev, John E. Walsh, and Uma S. Bhatt

1. Introduction Two leading modes—the Arctic Oscillation (AO) and the Arctic dipole (AD)—contribute the most to the large-scale atmospheric circulation over the Arctic in summer [June–August (JJA)]. By definition, both modes of variability are derived from applying empirical orthogonal function (EOF) analysis to the sea level pressure (SLP) anomaly field. The first EOF mode represents the AO that dominates the atmospheric circulation over the Arctic ( Thompson and Wallace 1998 ; Wu et al. 2006

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Ian Simmonds, Craig Burke, and Kevin Keay

of temporal variability with oscillations with periods of up to 60–80 yr (often superimposed on trends) showing up in many of the variables. A number of conceptual models based on the range of feedbacks that are present in the complex Arctic atmospheric, oceanic, and cryospheric domain have been proposed to account for the spectrum of variabilities (e.g., Mysak and Venegas 1998 ; Gudkovich and Kovalev 2002 ; Wang et al. 2005 ; Overland and Wang 2005 ). Notwithstanding the difficulties and

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