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Semyon A. Grodsky, James A. Carton, Sumant Nigam, and Yuko M. Okumura

Danabasoglu (2006) and Chang et al. (2007) pointed out that major atmospheric pressure centers and all global-scale surface wind systems are stronger than observed. In the northern tropics, this excess wind forcing results in excess surface heat loss. Despite the excess winds, the SST in the southeastern tropics is too warm. In CCSM3, the SST warm bias in the southeast has been attributed to the remote impact of erroneously weak zonal surface winds along the equator because of a deficit of rainfall

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Peter R. Gent and Gokhan Danabasoglu

that the ACC is in an “eddy saturated state,” defined as when the stronger mean flow MOC due to the increased winds is balanced by the stronger MOC due to increased eddy activity, defined as deviations from the time mean. It is difficult to determine from some of these papers the extent to which the two components balance, because they do not show the MOC and concentrate instead on the eddy heat transport. Farneti et al. (2010) force the ocean very strongly with a zonal wind stress perturbation

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Keith Oleson

column and water is removed from each soil layer. Heat emissions produced by anthropogenic activities (wasteheat) are a contributor to the UHI. Globally this flux is small compared to greenhouse gas forcing, one estimate is that it is on the order of 0.03 W m −2 ( Flanner 2009 ), however, within cities it can be a significant and even dominant component of the local urban energy budget ( Ichinose et al. 1999 ). Sources of wasteheat include human metabolism, vehicles, commercial and residential

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

Antarctic sea ice variability and mean state in the absence of transient forcings, we analyze model output for 500 yr of a 1300-yr preindustrial integration (simulation years 701–1200 of the 1850 control run). The 1850 control run is a fully coupled land–ocean–ice–atmosphere run that is forced at constant 1850 conditions (constant trace gases, land use and plant functional types, orbital parameters and solar irradiance, and aerosols), and described in more detail by Gent et al. (2011) . Output from the

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

multicentennial spinup period when subject to preindustrial (circa 1850) major climate forcings. b. Observational data Comparisons are made to standard observational satellite, in situ and reanalysis datasets including the 15-yr European Center for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-15; Gibson et al. 1997 ), 40-yr ECMWF Re-Analysis (ERA-40; Uppala et al. 2005 ), ECMWF Interim Re-Analysis (ERA-Interim; Dee et al. 2011 ), the NASA Modern-Era Retrospective Analysis for Research and

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Matthew C. Long, Keith Lindsay, Synte Peacock, J. Keith Moore, and Scott C. Doney

-induced advection coefficient varies in space and time according to Danabasoglu and Marshall (2007) . A variable coefficient provides a better representation of changes in eddy activity resulting from variable surface momentum forcing than a constant value; this is a key feature, allowing the model to more realistically capture the circulation response to changing winds, particularly in the Southern Ocean ( Danabasoglu and Marshall 2007 ; Gent and Danabasoglu 2011 ; Gent 2011 ; Farneti and Gent 2011

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Alicia R. Karspeck, Steve Yeager, Gokhan Danabasoglu, Tim Hoar, Nancy Collins, Kevin Raeder, Jeffrey Anderson, and Joseph Tribbia

assimilation system has been run over an 8-yr period from 1 January 1998 to 31 December 2005 with boundary forcing provided by an ensemble atmospheric analysis based on the atmospheric component of CCSM4. Because the period of assimilation is too short to evaluate interannual variability, we focus on the time-mean state. Insights from this short-term assimilation experiment will form the backbone of our understanding of how the assimilation system can be improved in future iterations. The CCSM4 ocean model

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Samantha Stevenson, Baylor Fox-Kemper, Markus Jochum, Richard Neale, Clara Deser, and Gerald Meehl

-amplified stochastic anomalies ( Thompson and Battisti 2001 ; Gebbie et al. 2007 ; Jin et al. 2006 ). Approaching the problem from a different direction, there have been numerous studies of ENSO-relevant dynamics that are likely to be affected by global warming ( Bony and Dufresne 2005 ; Liu and Philander 1995 ; McPhaden and Zhang 2002 ; Sun 2003 ). It is possible that external forcing might lead to a change in the types of El Niño–La Niña events that could be expected in the future, and much attention has

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

described and assessed in Gent et al. (2011) . For the twenty-first-century simulation, ensembles were completed for four different representative concentration projections (RCPs; Moss et al. 2010 ): RCP2.6, RCP4.5, RCP6.0, and RCP8.5, where the numerical value of each RCP indicates the approximate radiative forcing in the year 2100 (i.e., RCP8.5 has specified greenhouse gases and aerosol trajectories consistent with a radiative forcing of 8.5 W m −2 in the year 2100). The atmosphere and land

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A. Gettelman, J. E. Kay, and J. T. Fasullo

1. Introduction Global climate change is often described with a simple metric of the temperature response to a given radiative forcing of the climate system, the climate sensitivity γ . The range of climate sensitivity to a doubling of carbon dioxide (CO 2 ) simulated by general circulation models (GCMs) of 2.1–4.4 K has changed only slightly in 30 years ( Charney 1979 ; Solomon et al. 2007 ), with a most likely value of ~3 K ( Meehl et al. 2007b ), recently updated to 3.3 K ( Huber et al

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