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

the CORE-forced runs and the use of observationally based forcing data lead to smaller biases in sea surface temperature and salinity in this integration relative to the coupled model ( Table 2 ). Since CO 2 solubility increases with decreasing temperature, biases in DIC eq are negatively correlated with biases in SST (Fig. S1). For instance, the coupled model SST tends to be too warm in subtropical eastern boundary currents and too cold at high latitudes and in the Gulf Stream and Kuroshio

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William H. Lipscomb, Jeremy G. Fyke, Miren Vizcaíno, William J. Sacks, Jon Wolfe, Mariana Vertenstein, Anthony Craig, Erik Kluzek, and David M. Lawrence

linear interpolation between the values at the two neighboring elevations. For example, the SMB at 1000 m could be found by averaging the values sent by CLM at 800 and 1200 m. The SMB is applied during the ice sheet thickness calculation, and the surface temperature is used as an upper boundary condition for the vertical temperature calculation. Communication between the land and ice sheet models is currently one way: Glimmer-CISM receives surface forcing from CLM, but the surface topography and

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

Danabasoglu et al. (2012) . The CCSM4 POP2 includes several new features that are particularly relevant for the present study: i) the representation of the Denmark Strait (DS) and Faroe Bank Channel (FBC) overflows has been significantly improved by incorporating an overflow parameterization ( Danabasoglu et al. 2010 ) based on the marginal sea boundary condition scheme of Price and Yang (1998) , ii) the effects of diabatic mesoscale fluxes within the surface diabatic layer are included using a near

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

; http://www.cesm.ucar.edu/working_groups/WACCM/ ) and CAM chemistry (e.g., Lamarque et al. 2012 ). For CAM4 the default number of levels remains at 26 as a result of an undesirable nonconvergent response from boundary layer and shallow convection interactions when levels were significantly increased ( Williamson 2013 ). Because of the presence of grid-scale noise and excessive polar night jets, two new filtering/diffusion operators have been implemented in CAM4-FV ( Lauritzen et al. 2011 ). First

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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

et al. 2004 ) and follows the bathymetry of the Arctic Ocean, keeping shallow regions to the right. Specifically, the CCSM4 accurately depicts (i) the inflow of AW from the Fram Strait and the Barents and Kara Seas, (ii) the cyclonic boundary current around the marginal seas, (iii) the topographically steered cyclonic gyre in the Canadian Basin, (iv) the return flow of AW along the Lomonosov Ridge, and (v) the return Atlantic Current west and north of Svalbard (see Fig. 12 ). In contrast to the

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Ernesto Muñoz, Wilbert Weijer, Semyon A. Grodsky, Susan C. Bates, and Ilana Wainer

that the magnitude of the SST bias is related to differences in the convection parameterization in atmospheric models. In addition to remote mechanisms, the impact of local meridional winds and upwelling on the Benguela SST has been discussed by Large and Danabasoglu (2006) . They show that the warm bias in eastern boundary upwelling regions in the Community Climate System Model (CCSM) is due to a combination of weak ocean currents, weak upwelling, weak alongshore wind, too little stratus cloud

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A. Gettelman, J. E. Kay, and K. M. Shell

particle sizes and a prescribed distribution of aerosol mass. CAM5 includes a substantially revised physical parameterization suite over CAM4 ( Gettelman et al. 2010 ; Neale et al. 2010 ). The only major moist physics parameterization remaining constant between CAM4 and CAM5 is the deep convective parameterization ( Neale et al. 2008 ). CAM5 contains an updated moist boundary layer ( Bretherton and Park 2009 ) and shallow cumulus convection scheme ( Park and Bretherton 2009 ) that improves the

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

compared to Southern Hemisphere sea ice is due to different processes. In the Northern Hemisphere it is accomplished by coastal boundary currents, which are neither resolved nor parameterized. This leads to a too small poleward heat transport in the Arctic. With higher resolution, resolving these coastal currents leads to a redistribution of heat and a reduced sea ice bias in the Northern Hemisphere ( Jochum et al. 2008 ). In the Southern Hemisphere the sea ice distribution becomes worse with higher

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

-tropospheric stability. To provide a basis for comparison for current results, a brief overview of recent studies involving these properties is included below. Among the most important atmospheric characteristics, T sfc represents a fundamental near-surface thermal measure of climate. It acts as a governing force in modulation of surface properties including sea ice and land cover. Chapman and Walsh (2007) compared Arctic T sfc as simulated in 14 climate models used in IPCC AR4 and demonstrated them to feature

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Samuel Levis, Gordon B. Bonan, Erik Kluzek, Peter E. Thornton, Andrew Jones, William J. Sacks, and Christopher J. Kucharik

CROP minus CTRL simulations in June in North America, and (d) the same but for LateP minus CTRL. (b)–(d) Also shown are the 700-hPa winds in vector form and the 700-hPa specific humidity ( q ) in grayscale, to assess moisture advection above the boundary layer. In June CROP simulates surface cooling northwest of the U. S. Midwest and little change or drying of 700-hPa specific humidity ( q ) in the Midwest due to minor changes in the advection of q ( Fig. 5c ). LateP simulates large surface

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