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Peter R. Gent, Gokhan Danabasoglu, Leo J. Donner, Marika M. Holland, Elizabeth C. Hunke, Steve R. Jayne, David M. Lawrence, Richard B. Neale, Philip J. Rasch, Mariana Vertenstein, Patrick H. Worley, Zong-Liang Yang, and Minghua Zhang

was the first climate model that could maintain a stable present-day simulation without the use of flux corrections. The CCSM2 was released in 2002 ( Kiehl and Gent 2004 ), and CCSM3 was released in June 2004 ( Collins et al. 2006 ). One of the worst aspects of the CCSM3 climate was the El Niño–Southern Oscillation (ENSO) period, which was dominated by variability at 2 yr, rather than the 3–7-yr period from observations. Improving ENSO was the highest priority in CCSM4 development, and a

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Stephen J. Vavrus, Marika M. Holland, Alexandra Jahn, David A. Bailey, and Benjamin A. Blazey

during the rest of the century. Although we have discussed the role of decadal variability and extreme cyclones, we have not explored major modes of variability such as the Arctic Oscillation and how these might change under greenhouse forcing. While such questions are important and bear on the precise trajectory of future Arctic climatic conditions, we leave this topic for future studies with CCSM4. Acknowledgments This work has been supported by the National Science Foundation (ARC-0652838, ARC

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Alexandra Jahn, Kara Sterling, Marika M. Holland, Jennifer E. Kay, James A. Maslanik, Cecilia M. Bitz, David A. Bailey, Julienne Stroeve, Elizabeth C. Hunke, William H. Lipscomb, and Daniel A. Pollak

–2005 record. If we take the Arctic Oscillation index for DJFM from the National Oceanic and Atmospheric Administration as proxy for the atmospheric conditions that affect sea ice motion, we find that 16% of the winters between 1981 and 2005 had a DJFM Arctic Oscillation (AO) index that is larger than one standard deviation of the mean, and 12% of the years had a DJFM AO index that is one standard deviation smaller than the mean. Applying the same one standard deviation cutoff for the 150 yr from the six

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Gijs de Boer, William Chapman, Jennifer E. Kay, Brian Medeiros, Matthew D. Shupe, Steve Vavrus, and John Walsh

, winter, and spring. Together, these SLP features influence modes of variability like the Arctic and North Atlantic Oscillations (AO and NAO, respectively). Evaluation of the model’s ability to simulate these modes is reviewed in J. Hurrell et al. (2011, personal communication). c. Clouds As discussed earlier, we present a wide range of methods and measurements for cloud evaluation. Arctic-wide, CCSM4 appears to underestimate total cloud cover for much of the year compared to satellite and ground

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Laura Landrum, Bette L. Otto-Bliesner, Eugene R. Wahl, Andrew Conley, Peter J. Lawrence, Nan Rosenbloom, and Haiyan Teng

. Madsen, and D. R. Currey, Eds., Smithsonian Contributions to the Earth Sciences, Vol. 33, Smithsonian Institution Press, 295–307 . Delworth , T. L. , and M. E. Mann , 2000 : Observed and simulated multidecadal variability in the Northern Hemisphere . Climate Dyn. , 16 , 661 – 676 . Deser , C. , 2000 : On the teleconnectivity of the “Arctic Oscillation.” Geophys. Res. Lett. , 27 , 779 – 782 , doi:10.1029/1999GL010945 . Deser , C. , and Coauthors , 2012 : ENSO and Pacific decadal

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David M. Lawrence, Andrew G. Slater, and Sean C. Swenson

1. Introduction Permafrost and seasonally frozen ground are key components of the Arctic and global climate system because of their influence on energy, water, and carbon cycles. The freeze–thaw status of the ground is a critical threshold in the terrestrial system that is closely linked to the timing and length of the vegetation growing season ( Black et al. 2000 ), boreal plant productivity ( Kimball et al. 2006 ), the seasonal evolution of land–atmosphere carbon dioxide ( Goulden et al. 1998

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Christine A. Shields, David A. Bailey, Gokhan Danabasoglu, Markus Jochum, Jeffrey T. Kiehl, Samuel Levis, and Sungsu Park

. This paper presents a low-resolution CCSM4 as an alternative to the higher resolution versions and highlights both its strengths and weaknesses in comparison with observations and other CCSM4 resolution versions. CCSM4 contains several notable improvements spanning all model components, which include a much improved El Niño–Southern Oscillation (ENSO) representation, improved ocean mixing, a new land carbon–nitrogen (CN) component, more realistic ice albedos, and new coupling infrastructure. The

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Laura Landrum, Marika M. Holland, David P. Schneider, and Elizabeth Hunke

recent increase of Antarctic sea ice extent . Geophys. Res. Lett. , 36 , L08502 , doi:10.1029/2009GL037524 . van Loon , H. , 1967 : The half-yearly oscillations in middle and high southern latitudes and the coreless winter . J. Atmos. Sci. , 24 , 472 – 486 . Vavrus , S. , and D. Waliser , 2008 : An improved parameterization for simulating Arctic cloud amount in the CCSM3 climate model . J. Climate , 21 , 5673 – 5687 . Wang , Y.-M. , J. L. Lean , and N. R. Sheeley Jr

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Richard B. Neale, Jadwiga Richter, Sungsu Park, Peter H. Lauritzen, Stephen J. Vavrus, Philip J. Rasch, and Minghua Zhang

3. This article summarizes the improvements seen in the seasonally varying mean atmospheric climate of prescribed-SST and fully coupled simulations. The dominant changes made to the model configuration involve the parameterization of deep convection. These changes have a significant impact on improving the pattern of long-standard tropical errors such as El Niño–Southern Oscillation (ENSO; Deser et al. 2012 ) and the Madden–Julian oscillation (MJO; Subramanian et al. 2011 ). A further change

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Gokhan Danabasoglu, Steve G. Yeager, Young-Oh Kwon, Joseph J. Tribbia, Adam S. Phillips, and James W. Hurrell

resolution was presented in Bryan et al. (2006) , which showed that AMOC variability amplitude increases with increasing overall resolution. With its largest AMOC amplitude, T85 × 1 had two distinct AMOC variability regimes: a 300-yr-long oscillatory regime with a period of 21 yr followed by much weaker irregular variability regime with a broad variance maximum at a period of about 40 yr. The first regime was analyzed in Danabasoglu (2008) and the North Atlantic Oscillation (NAO) was found to play a

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