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Jie Zhang, Zhiheng Chen, Haishan Chen, Qianrong Ma, and Asaminew Teshome

North Atlantic (NA) jet ( Trouet et al. 2018 ), the North Pacific jet ( Strong and Davis 2008 ; Belmecheri et al. 2017 ), and the Afro-Asian jet ( Branstator 2002 ); however, all of them show inconsistent variability at interannual to decadal time scales. Therefore, considering their different impacts, the jet effects on summer extremes should be discussed separately. The NA jet has been identified to result in extratropical extremes such as heatwaves and droughts in Europe ( Trouet et al. 2018

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Hanna Na, Kwang-Yul Kim, Shoshiro Minobe, and Yoshi N. Sasaki

variability in the NP, partly because of its better availability in both time and space. The most dominant mode of the NP variability [i.e., the Pacific decadal oscillation (PDO); Mantua et al. (1997) ] is derived from empirical orthogonal function (EOF) analysis of SST in the NP (north of 20°N) and has been widely used to understand the long-term changes in the physical and biological conditions in the NP. However, the different vertical structures of the KE and SAFZ have raised the importance of

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Amélie Desmarais and L. Bruno Tremblay

the Atlantic multidecadal variability are significantly correlated with long-term variability in SIE in global climate models ( Day et al. 2012 ; Zhang et al. 2019 ; Zhang 2015 ; Yu et al. 2017 ), and the associated poleward ocean transport anomalies drive decadal changes (dominant time scale of 14 years) in sea ice extent in the Barents Sea ( Årthun et al. 2012 ; Årthun and Schrum 2010 ). The strength of the AMOC however is still underestimated across climate models ( Yan et al. 2018

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Yong-Jhih Chen, Yen-Ting Hwang, Mark D. Zelinka, and Chen Zhou

the absence of forcing are described in section 3 . The estimated contributions of the decadal variability to the observed cloud cover trends, along with the estimated contributions of GHG forcing, are described in section 4 . In section 5 we summarize our findings. 2. Data and methodology a. Data The SST data used in this study were obtained from the Hadley Centre Global Sea Ice and Sea Surface Temperature dataset (HadISST; Rayner et al. 2003 ) and the Extended Reconstructed Sea Surface

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Marius Årthun, Robert C. J. Wills, Helen L. Johnson, Léon Chafik, and Helene R. Langehaug

1. Introduction The North Atlantic Ocean displays pronounced decadal variability ( Fig. 1 ; Deser and Blackmon 1993 ; Czaja and Marshall 2001 ). Decadal variations in North Atlantic sea surface temperature (SST) influence climate over adjacent continents and are a major source of skill in climate predictions ( Hermanson et al. 2014 ; Msadek et al. 2014 ; Årthun et al. 2017 ; Yeager and Robson 2017 ). Understanding the physical mechanisms responsible is thus important for attributing

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Bo Qiu, Shuiming Chen, Niklas Schneider, Eitarou Oka, and Shusaku Sugimoto

during 1995–2001, 2006–09, and 2016–17. This decadal modulation of the KE system has persisted after the 1976–77 “climate shift” in the North Pacific ( Qiu et al. 2014 ) and the basinwide wind stress curl variability associated with the Pacific decadal oscillations (PDOs; Mantua et al. 1997 ), or the North Pacific gyre oscillations (NPGOs; Di Lorenzo et al. 2008 ), has been identified as the external forcing that controls the phase change between the stable/unstable dynamic states. Fig . 2. Yearly

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Yushi Morioka, Francois Engelbrecht, and Swadhin K. Behera

1. Introduction Climate variability at a decadal or longer time scale is a key issue for the society to mitigate climate-related risks and establish long-term adaptation plans for agriculture, fisheries, water management, city design, etc. A growing number of studies have to date elaborated on decadal or multidecadal climate variability, mainly in the Northern Hemisphere [e.g., Pacific decadal variability ( Mantua et al. 1997 ) and Atlantic meridional oscillation ( Schlesinger and Ramankutty

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Bo Qiu, Shuiming Chen, and Niklas Schneider

extensive exploration of the impact of OE variability upon the overlying atmosphere, our understanding about the causes that generate the OE variability remains limited. Using both ship and satellite SST measurements of 1982–96, Nakamura and Kazmin (2003) detected a decadal intensification of the OE front during the period of 1988–94. They attributed this frontal intensification to the combined surface net heat flux and Ekman flux convergence forcing. Based on lead–lag regression analysis, Nonaka et

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Kewei Lyu, Xuebin Zhang, John A. Church, Jianyu Hu, and Jin-Yi Yu

the Pacific ( Fig. 1a ). It has been increasingly recognized that regional sea level trend patterns calculated over such a short time period (~2 decades) are at least partly related to the low-frequency climate variability with periods longer than interannual time scales (e.g., Zhang and Church 2012 ; Palanisamy et al. 2015a ). It remains unclear if there is any detectable anthropogenic climate change signal in the altimeter-observed sea level trend pattern ( Meyssignac et al. 2012 ; Han et al

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Matthew B. Menary, Daniel L. R. Hodson, Jon I. Robson, Rowan T. Sutton, and Richard A. Wood

1. Introduction The North Atlantic Ocean has been shown to be a key region for the initialization of decadal forecasts ( Dunstone et al. 2011 ), and sea surface temperatures (SSTs) in this region are likely important for the climates of the nearby continents of North America and Europe ( Rodwell et al. 1999 ). SSTs in the North Atlantic show large multidecadal variability ( Knight et al. 2005 ), which has been linked to drought in the Sahel region ( Folland et al. 1986 ; Zhang and Delworth

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