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Xiaofang Feng, Qinghua Ding, Liguang Wu, Charles Jones, Ian Baxter, Robert Tardif, Samantha Stevenson, Julien Emile-Geay, Jonathan Mitchell, Leila M. V. Carvalho, Huijun Wang, and Eric J. Steig

western North America ( Fig. 10a ). PC2 from LMR2 (PC2-LMR2) is also significantly correlated with PC1-EKF400 in the overlapping period of 1603–2000 ( r = 0.37). Additionally, there is little sensitivity of our EOF analysis to differing periods from LMR2 spanning the last 1500, 1000, 500, and 200 years all ending in the year 2000, and the 1850 years before the industrial revolution. Correlations of PC2-LMR2 with LMR2 surface temperatures show that, like in the other reanalysis datasets, this mode

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Bradford S. Barrett, Gina R. Henderson, and Joshua S. Werling

affect the polarity of the Arctic Oscillation ( Zhou and Miller 2005 ; L’Heureux and Higgins 2008 ), the North Atlantic Oscillation ( Cassou 2008 ; Lin et al. 2009 ), and the Pacific–North America pattern ( Mori and Watanabe 2008 ; Lin et al. 2009 ; Johnson and Feldstein 2010 ; Adames and Wallace 2014 ; Bao and Hartmann 2014 ). Via its modulation of large-scale circulation, the MJO’s influence has already been found to extend to Arctic sea ice ( Henderson et al. 2014 ). The primary pathway for

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Changhyun Yoo, Sungsu Park, Daehyun Kim, Jin-Ho Yoon, and Hye-Mi Kim

global impact on weather and climate through its teleconnections ( Kim et al. 2006 ; Zhang 2013 ). For example, the MJO modulates the Northern Hemisphere climate modes, such as the Arctic Oscillation (AO; L’Heureux and Higgins 2008 ), the North Atlantic Oscillation (NAO; Cassou 2008 ; Lin et al. 2009 ; Riddle et al. 2013 ), and the Pacific–North American teleconnection pattern (PNA; Mori and Watanabe 2008 ; Johnson and Feldstein 2010 ; Riddle et al. 2013 ). Through changes in large

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Xiaojun Yuan, Michael R. Kaplan, and Mark A. Cane

circulation anomalies can be established at high latitudes in 3–6 days as the Pacific–North America (PNA) pattern. These MJO-induced circulation changes alter poleward heat transport. Together with adiabatic warming and downward infrared radiative fluxes, the anomalous poleward heat transport is capable of influencing the variability of winter surface temperature in the Arctic. This result is consistent with the results of Graversen (2006) . Yoo et al. (2011) further found in observations that MJO

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Michael Goss, Steven B. Feldstein, and Sukyoung Lee

autumn through spring. The constructive interference composite in those seasons is associated with large positive values over the northeastern North Pacific and western North America, over the northeastern North Atlantic through Scandinavia, and over the northwestern subtropical Pacific. Large negative values are found over northeastern North America, the northwestern North Pacific, the northeastern subtropical Pacific, and from the northeastern subtropical Atlantic through the Mediterranean

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Robert A. Tomas, Clara Deser, and Lantao Sun

in ΔICE_FOM ( Fig. 2e ). Both simulations show negative anomalies in the central Arctic and over most of North America, as well as the eastern North Atlantic extending into southern Europe and northern Africa, with larger magnitudes in ΔICE_SOM_Q20 compared to ΔICE_FOM. Zonally oriented high pressure extends over northern Europe across Siberia in both simulations. A notable difference between ΔICE_FOM and ΔICE_SOM_Q20 is the low pressure center response over the North Pacific in the former but

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N. Fauchereau, B. Pohl, and A. Lorrey

, leading to potential predictability of regional climate anomalies (temperature and precipitation) beyond meteorological time scales. Similarly, Riddle et al. (2012) showed that, over the North American region, several WRs resembled linear combinations of the Arctic Oscillation (AO) and the Pacific–North American (PNA) pattern, and these were significantly modulated by the MJO. In the Southern Hemisphere (SH), several studies have demonstrated that the MJO is related to significant regional impacts

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Lee J. Welhouse, Matthew A. Lazzara, Linda M. Keller, Gregory J. Tripoli, and Matthew H. Hitchman

smaller changes in tropical SSTs ( Held et al. 1989 ). Such wave trains are known as the Pacific–North American (PNA) pattern in the Northern Hemisphere and the Pacific–South American (PSA) pattern in the Southern Hemisphere ( Karoly 1989 ). Specifically for this work, the important PSA pattern is the PSA-1 pattern found in Karoly (1989) , which is largely associated with ENSO variability in tropical convection. Though there was initially less evidence to support this designation, further

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Bradley P. Goodwin, Ellen Mosley-Thompson, Aaron B. Wilson, Stacy E. Porter, and M. Roxana Sierra-Hernandez

South America ( Fogt 2007 ; Eichler and Gottschalck 2013 ). Thus, the combination of the SAM and ENSO and their associated modulation of SH storm tracks ( Fogt et al. 2011 ; Schneider et al. 2012 ) influence accumulation on the AP. In addition to the SAM and ENSO, the Pacific decadal oscillation (PDO) also influences the climate of the AP. Often described as “ENSO like” decadal-scale variability in the North Pacific ( Zhang et al. 1997 ), Mantua et al. (1997) coined the term “PDO” to describe an

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M. Nuncio and Xiaojun Yuan

by linear regression, the flux from the Pacific is absent, while the flux from the eastern Indian Ocean is strengthened south of Australia and the southwestern Pacific sea ice region ( Fig. 3d , vectors). One part of the wave energy is converged into the Ross Sea and another part is reflected north over South America. The response to these wave activity fluxes is manifested as positive and negative pressure centers as shown in Fig. 3d . This is the eastern Indian Ocean wave train described by

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