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C. Kendra Gotangco Castillo, Samuel Levis, and Peter Thornton

1. Introduction The Community Land Model, version 4.0 (CLM4) was released as a component of the Community Climate System Model, version 4.0 (CCSM4), which was updated to become the Community Earth System Model, version 1.0 (CESM1) with the option to run with interactive atmosphere–ocean–land carbon cycles. CLM4 contains several notable improvements over previous releases (e.g., Lawrence et al. 2011 ; Kluzek 2011 ; Oleson et al. 2010 ). Earlier versions of the CLM (since CLM2) included

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

, they found increased net radiation and evapotranspiration, mainly in response to reduced surface albedo. Again, such studies do not account for possible two-way climate–crop interactions. Only Osborne et al. (2007 , 2009 ) performed global coupled atmosphere–land simulations with an interactive crop model. Osborne et al. used the crop model GLAM (a groundnut, i.e., warm climate crop, model) in the land component of the Hadley Centre Atmosphere Model, version 3 (HadAM3). Osborne et al. (2009

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Peter J. Lawrence, Johannes J. Feddema, Gordon B. Bonan, Gerald A. Meehl, Brian C. O’Neill, Keith W. Oleson, Samuel Levis, David M. Lawrence, Erik Kluzek, Keith Lindsay, and Peter E. Thornton

1. Introduction Recent studies have shown that historical human land use and land cover change have significantly impacted the earth’s climate through changes in the carbon cycle, through altered biogeochemical processes ( Houghton 2003 ; Canadell et al. 2007 ; Bonan 2008 ; Shevliakova et al. 2009 ) and through changes in energy and moisture fluxes to the atmosphere, by altering biogeophysical processes ( Betts et al. 2001 ; Feddema et al. 2005 ; Findell et al. 2007 ; Bala et al. 2007

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David M. Lawrence, Keith W. Oleson, Mark G. Flanner, Christopher G. Fletcher, Peter J. Lawrence, Samuel Levis, Sean C. Swenson, and Gordon B. Bonan

than transpiration ( Lawrence et al. 2007 ; Oleson et al. 2008b ). In CLM4 and CCSM4, the partitioning of ET into transpiration, ground evaporation, and canopy evaporation is much improved ( Lawrence et al. 2011 ), which leads to more realistic land–atmosphere interactions such as, for example, a more realistic temporal response of ET to a precipitation event. River discharge is calculated via the CLM River Transport Model (RTM, Branstetter and Famiglietti 1999 ), which transports gridcell runoff

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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

margins, floating ice shelves are vulnerable to warming of subshelf ocean waters ( Pritchard et al. 2012 ), but these interactions are only beginning to be modeled ( Hellmer et al. 2012 ). Also, changes in ice sheet topography and surface runoff could alter atmospheric and oceanic circulation patterns ( Ridley et al. 2005 ; Hu et al. 2009 ). Coupling ice sheet models to climate models is a long-term effort requiring major software engineering changes (e.g., to allow the land–atmosphere and land

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Gretchen Keppel-Aleks, James T. Randerson, Keith Lindsay, Britton B. Stephens, J. Keith Moore, Scott C. Doney, Peter E. Thornton, Natalie M. Mahowald, Forrest M. Hoffman, Colm Sweeney, Pieter P. Tans, Paul O. Wennberg, and Steven C. Wofsy

1. Introduction Carbon dioxide is a dominant anthropogenic greenhouse gas in the earth's atmosphere. Its atmospheric concentration has risen from 280 ppm preindustrially to 390 ppm in 2011 because of fossil fuel combustion and land use change ( R. F. Keeling et al. 1996 ; Prentice et al. 2000 ). The extent to which CO 2 levels in the atmosphere continue increasing will be the primary determinant of future climate change ( Solomon et al. 2007 ). The trajectory of atmospheric CO 2 depends not

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Keith Oleson

et al. 2010 ). Climate change scientists working at global scales are now beginning to apply lessons learned from these observational and modeling efforts and devote significant modeling and computing resources to develop an understanding of urban climate and its possible interactions with climate change. Global climate modeling groups at the Hadley Centre and the National Center for Atmospheric Research have implemented urban models within the land surface model components of their respective

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

, and conclusions are in section 7 . 2. Methodology We apply radiative kernels calculated offline to the climate response in doubled CO 2 experiments with atmospheric GCMs coupled to slab ocean models (SOMs). In CESM, SOM experiments yield results very similar to atmospheric models coupled to a full dynamic ocean ( Bitz et al. 2012 ). For feedbacks attributed to atmospheric physical parameterizations, the same feedbacks found in the SOM runs can be diagnosed with stand-alone atmosphere model SST

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

., Vol. 147, Amer. Geophys. Union, 121–142 . Zebiak , S. E. , 1993 : Air–sea interaction in the equatorial Atlantic region . J. Climate , 6 , 1567 – 1586 . Zuidema , P. , P. Chang , C. R. Mechoso , and L. Terray , 2011 : Coupled ocean-atmosphere-land processes in the tropical Atlantic. CLIVAR Exchanges, No. 1, International CLIVAR Project Office, Southampton, United Kingdom, 12–14 .

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

surface wind speed and direction, temperature, and precipitation. Wind speed and direction are particularly important in the Arctic for advection of simulated sea ice ( DeWeaver and Bitz 2006 ) and governance of heat fluxes between the ocean–land surface and atmosphere. Chapman and Walsh (2007) also evaluated simulated Arctic SLP. In general, ESM-simulated storm tracks were demonstrated to be shorter than those observed, with observed storms often reaching the Kara Sea and simulated storm tracks

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