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Kazuto Takemura, Hitoshi Mukougawa, and Shuhei Maeda

jet, and Enomoto et al. (2003) referred to it as the Silk Road pattern. Kosaka et al. (2009) showed using empirical orthogonal function (EOF) analysis that the Silk Road pattern is extracted as principal components of the upper-tropospheric atmospheric variability over southern Eurasia based on monthly dataset of the Japanese 25-Year Reanalysis (JRA-25; Onogi et al. 2007 ), indicating that the wave propagation along the Asian jet is one of the essential factors contributing to East Asian

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Courtenay Strong and Gudrun Magnusdottir

Abatzolglou , J. T. , and G. Magnusdottir , 2006 : Opposing effects of reflective and nonreflective planetary wave breaking on the NAO. J. Atmos. Sci. , 63 , 3448 – 3457 . Austin , P. C. , and J. V. Tu , 2004 : Bootstrap methods for developing predictive models. Amer. Stat. , 58 , 131 – 137 . Chen , G. , and P. Zurita-Gotor , 2008 : The tropospheric jet response to prescribed zonal forcing in an idealized atmospheric model. J. Atmos. Sci. , 65 , 2254 – 2271 . Chen , G. , I

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G. Wolf, A. Czaja, D. J. Brayshaw, and N. P. Klingaman

source (e.g., Smith et al. 2017 ). These discrepancies highlight the necessity to further investigate and understand the atmospheric wave response to variability in sea surface temperatures and sea ice. It is difficult to isolate the atmospheric response to changes in sea ice due to the many other influences on the atmospheric circulation, as well as a low signal-to-noise-ratio ( Screen et al. 2014 ). Regarding this aspect, Luo et al. (2019) highlighted the importance of the weakened north

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Xichen Li, David M. Holland, Edwin P. Gerber, and Changhyun Yoo

play a key role in channeling wave activity from the Atlantic and Pacific to West Antarctica. The outline of this paper is as follows: The tropical SST trend is estimated in section 2 , which is then used to force the atmospheric models. Results from the CAM4 comprehensive atmospheric model simulations are presented in section 3 , followed by results from the GFDL dry-dynamical core simulations in section 4 , and those from the theoretical model in section 5 . Conclusions are drawn in section

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Hyodae Seo, Markus Jochum, Raghu Murtugudde, Arthur J. Miller, and John O. Roads

-frequency atmospheric response to TIW-induced SST. 4. Summary and discussion Ocean–atmosphere covariability arising in the presence of tropical instability waves (TIWs) was examined using a regionally coupled high-resolution climate model in the tropical Atlantic Ocean. One of the goals of the present study was to study the impact of the atmospheric wind response on the TIWs. Two mechanisms by which atmospheric wind fields feed back onto TIWs are a direct exchange of momentum and through a modification of wind

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Mi-Kyung Sung, Seon-Hwa Kim, Baek-Min Kim, and Yong-Sang Choi

this, it is worth noticing the studies addressing the atmospheric energy transport from outside of the Arctic. While the direct impact of reduced sea ice tends to appear in the lowermost part of the atmosphere, the Arctic temperature change is observed above the surface layer as well ( Graversen et al. 2008 ). Recent studies identify a considerable contribution of the heat and moisture transport in the Arctic warming through atmospheric wave response, and it accounts for the observed Arctic thermal

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Gui-Ying Yang, Julia Slingo, and Brian Hoskins

present there is little understanding of how well they are treated in state-of-the-art models and our overall knowledge of these waves is very limited. Current large-scale models fail to simulate well-organized tropical phenomena in which convection interacts with dynamics and physics. Lin et al. (2006) showed that 14 atmospheric global circulation models (AGCMs) that participated in the Intergovernmental Panel on Climate Change (IPCC) have significant problems in simulating tropical subseasonal

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Stephanie Leroux, Nicholas M. J. Hall, and George N. Kiladis

1. Introduction On synoptic scales, African easterly waves (AEWs) are the dominant mode of atmospheric variability over West Africa in summer (June–September). AEWs are baroclinic westward-propagating disturbances observed in convective and dynamical fields, with wavelengths of about 3000–6000 km and periods of 3–5 days [see Kiladis et al. (2006) for a recent composite study]. They appear as intermittent wave packets on intraseasonal time scales. A large range of studies have already

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Kathleen D. Holman, David J. Lorenz, and Michael Notaro

of changes in the mean vorticity and divergence fields between the two months. Their results emphasize the importance of monthly, rather than seasonal, analyses in exploring and understanding Rossby wave propagation. In this paper, we expand on previous research by exploring the direct relationship between precipitation in the Great Lakes region and large-scale atmospheric circulation patterns, namely, atmospheric Rossby waves. Using reanalysis data, we explore how variability in the upper

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Evan Weller, Ming Feng, Harry Hendon, Jian Ma, Shang-Ping Xie, and Nick Caputi

tropical eastern IO, similar to observations ( Figs. 7a,d ), as well as atmospheric Rossby waves that then propagate into the extratropics and over the Australian continent ( Fig. 7 ). Overall, the response in the southern IO displays clear atmospheric wave train structures ( Hoskins and Karoly 1981 ; Gill 1982 ; Saji and Yamagata 2003a ; Cai et al. 2011b ) with a strong response over the Australian continent ( Fig. 7 ). The IOD experiment confirms that the positive sea level pressure anomalies

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