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Stephen Baxter and Sumant Nigam

PNA events. Additionally, intraseasonal tropical convection related to the Madden–Julian oscillation (MJO; Madden and Julian 1971 , 1972 ) has been shown to contribute to both PNA development ( Higgins and Mo 1997 ) and the North Atlantic Oscillation (NAO; Lin et al. 2009 ). The aforementioned studies would suggest that weakened convection in the eastern Indian Ocean and enhanced convection in the western tropical Pacific [a high real-time multivariate MJO (RMM) 2 index] would lead to a

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Clara Deser, Robert A. Tomas, and Lantao Sun

1. Introduction Perennial Arctic sea ice is projected to disappear by the mid-to-late twenty-first century in response to anthropogenically driven increases in greenhouse gas (GHG) concentrations ( Stroeve et al. 2012 ; Stocker et al. 2013 ). The anticipated loss of Arctic sea ice is expected to impact climate at northern high and middle latitudes through a variety of mechanisms (e.g., Serreze and Barry 2011 ). The most robust impacts include thermodynamically driven warming and moistening of

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Shuyu Zhang, Thian Yew Gan, and Andrew B. G. Bush

and into the North Atlantic ( Serreze and Barrett 2011 ), is largely controlled by the surface wind field ( Thorndike and Colony 1982 ). The local atmospheric circulation is strongly teleconnected to the climate of remote regions through climate patterns, such as the Arctic Oscillation (AO), the North Atlantic Oscillation (NAO), the Pacific–North American pattern (PNA), and El Niño–Southern Oscillation (ENSO). The AO is the first mode of wintertime sea level pressure (SLP) variability for regions

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Hugues Goosse and Marika M. Holland

different processes reviewed in section 2 . The CCSM2 model is presented in section 3 . In section 4 , the mechanisms driving the simulated large-scale Arctic climate variability are analyzed, before some concluding remarks are given ( section 5 ). 2. A review of mechanisms driving Arctic variability a. Processes related to North Atlantic Oscillation/Arctic Oscillation The most widely studied mode of variability in the Arctic is associated with the North Atlantic Oscillation or the closely related

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Gary Grunseich and Bin Wang

ice reduction in the Arctic Ocean is widely attributed to anthropogenic climate change and dynamical and radiative feedbacks ( IPCC 2013 ; Screen and Simmonds 2010 ; Hall 2004 ). Recently, the long-term trends in remote tropical variability and its impacts on anomalous Arctic atmospheric circulations are receiving extensive attention. The prominent warming over Canada and Greenland since 1979 is found to be strongly associated with a negative trend in the North Atlantic Oscillation, which is a

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Le Chang, Jing-Jia Luo, Jiaqing Xue, Haiming Xu, and Nick Dunstone

not shown). c. ENSO impact on the Arctic internal variations in winter Previous studies suggested that internal modes of climate variability, such as the North Atlantic Oscillation (NAO)–Arctic Oscillation (AO) ( Mysak and Venegas 1998 ; Kwok 2000 ; Rigor et al. 2002 ; Krahmann and Visbeck 2003 ; Zhang et al. 2004 ) and the Madden–Julian oscillation ( Yoo et al. 2011 ), play important roles in the Arctic climate variations. Tropical sea surface temperature (SST) also has important

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Jennifer Miletta Adams, Nicholas A. Bond, and James E. Overland

Oscillation The 20-yr time period we have selected spans an important and unprecedented climate shift that occurred around 1989 in association with the Arctic oscillation (AO) ( Thompson and Wallace 1998 ). The AO is characterized by latitudinal shifts of atmospheric mass that modulate the strength of the polar vortex. The spatial signature of the AO was noted earlier by van Loon and Williams (1980) who made a connection between sea level pressure in the North Atlantic–European area and the meridional

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Jinlun Zhang, Drew Rothrock, and Michael Steele

1. Introduction Significant changes in the Arctic climate have been detected in the late 1980s and 1990s. During that period, there has been a substantial decrease in sea level pressure in the Arctic, characterized by a weakening of the Beaufort high pressure cell and a strengthening of the European subarctic low pressure cell and thus an altered wind circulation pattern ( Walsh et al. 1996 ). This atmospheric state is described as a positive phase of the North Atlantic oscillation (NAO

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Alexey Yu. Karpechko and Elisa Manzini

). If the BD circulation strengthening extends to the poles (i.e., it encompasses the deep branch of the BD circulation) an equatorward shift of the tropospheric eddy-driven jet streams during Northern Hemisphere (NH) winter is also often simulated ( Scaife et al. 2012 ; Karpechko and Manzini 2012 ), although it is not a robust response across the models. Butchart et al. (2000) reported that the forced response of the Arctic stratosphere to global warming is small compared to internal variability

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Gabriele Villarini and Gabriel A. Vecchi


This study focuses on the statistical modeling of the power dissipation index (PDI) and accumulated cyclone energy (ACE) for the North Atlantic basin over the period 1949–2008, which are metrics routinely used to assess tropical storm activity, and their sensitivity to sea surface temperature (SST) changes. To describe the variability exhibited by the data, four different statistical distributions are considered (gamma, Gumbel, lognormal, and Weibull), and tropical Atlantic and tropical mean SSTs are used as predictors. Model selection, both in terms of significant covariates and their functional relation to the parameters of the statistical distribution, is performed using two penalty criteria. Two different SST datasets are considered [the Met Office’s Global Sea Ice and Sea Surface Temperature dataset (HadISSTv1) and NOAA’s extended reconstructed SST dataset (ERSSTv3b)] to examine the sensitivity of the results to the input data.

The statistical models presented in this study are able to well describe the variability in the observations according to several goodness-of-fit diagnostics. Both tropical Atlantic and tropical mean SSTs are significant predictors, independently of the SST input data, penalty criterion, and tropical storm activity metric. The application of these models to centennial reconstructions and seasonal forecasting is illustrated.

The sensitivity of North Atlantic tropical cyclone frequency, duration, and intensity is examined for both uniform and nonuniform SST changes. Under uniform SST warming, these results indicate that there is a modest sensitivity of intensity, and a decrease in tropical storm and hurricane frequencies. On the other hand, increases in tropical Atlantic SST relative to the tropical mean SST suggest an increase in the intensity and frequency of North Atlantic tropical storms and hurricanes.

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