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Alan J. Hewitt, Ben B. B. Booth, Chris D. Jones, Eddy S. Robertson, Andy J. Wiltshire, Philip G. Sansom, David B. Stephenson, and Stan Yip

Project (C 4 MIP; Friedlingstein et al. 2006 ) and is now a mainstream component of coordinated climate simulations like phase 5 of the Coupled Model Intercomparison Project (CMIP5; Taylor et al. 2012 ). Such coupled climate–carbon cycle ESMs simulate the natural exchange of carbon by the land and ocean with the atmosphere and thus provide a predictive link between emissions and atmospheric concentrations of CO 2 . They can be used to compute the emissions required to follow a prescribed

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Spencer Liddicoat, Chris Jones, and Eddy Robertson

offline, by comparison of the land–atmosphere flux of LUC and no-LUC simulations, are within the observed range of historical LUC emissions. They provide a better estimate than the online diagnosed flux, because as well as emissions from deforestation they account for the impacts of LUC on the biophysical and biogeochemical land–atmosphere fluxes and therefore on carbon exchange. Interactions between the carbon and nitrogen cycles are not included in HadGEM2-ES. Recent studies ( Zaehle et al. 2010

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V. Brovkin, L. Boysen, V. K. Arora, J. P. Boisier, P. Cadule, L. Chini, M. Claussen, P. Friedlingstein, V. Gayler, B. J. J. M. van den Hurk, G. C. Hurtt, C. D. Jones, E. Kato, N. de Noblet-Ducoudré, F. Pacifico, J. Pongratz, and M. Weiss

sea ice, putting emphasis on land–atmosphere interactions. This approach allows isolation of the direct effects of LULCC on the atmosphere from the indirect effects caused by interactions with the other components of climate system (e.g., sea ice). However, neglecting these feedbacks may reduce the magnitude of effects of LULCC on climate (e.g., Davin and de Noblet-Ducoudré 2010 ). On decadal to centennial time scales, the feedbacks through interactive SSTs and sea ice have the potential to

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Chris Jones, Eddy Robertson, Vivek Arora, Pierre Friedlingstein, Elena Shevliakova, Laurent Bopp, Victor Brovkin, Tomohiro Hajima, Etsushi Kato, Michio Kawamiya, Spencer Liddicoat, Keith Lindsay, Christian H. Reick, Caroline Roelandt, Joachim Segschneider, and Jerry Tjiputra

models ( Booth et al. 2012 ). Such coupled climate–carbon cycle models simulate the natural exchange of carbon by the land and ocean with the atmosphere and thus provide a predictive link between emissions and atmospheric concentrations of CO 2 . In emissions-driven simulations such as in C 4 MIP, these models calculate changes in atmospheric CO 2 concentration given a scenario of emissions. They can also be used to compute the emissions required to follow a prescribed concentration pathway ( Jones

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Pierre Friedlingstein, Malte Meinshausen, Vivek K. Arora, Chris D. Jones, Alessandro Anav, Spencer K. Liddicoat, and Reto Knutti

global carbon cycle ( Hibbard et al. 2007 ; Taylor et al. 2012 ). Most of the proposed experiments are performed using prescribed globally averaged CO 2 concentration, not CO 2 emissions, allowing participation of both AOGCMs and ESMs. For a given model, the projected climate change is then independent of the strength of its feedbacks associated with the carbon cycle. Concentration–carbon and climate–carbon feedbacks would affect the carbon fluxes between the atmosphere and the underlying land and

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Vivek K. Arora, George J. Boer, Pierre Friedlingstein, Michael Eby, Chris D. Jones, James R. Christian, Gordon Bonan, Laurent Bopp, Victor Brovkin, Patricia Cadule, Tomohiro Hajima, Tatiana Ilyina, Keith Lindsay, Jerry F. Tjiputra, and Tongwen Wu

1. Introduction Earth system models (ESMs) incorporate terrestrial and ocean carbon cycle processes into coupled atmosphere–ocean general circulation models (AOGCMs) in order to represent the interactions between the carbon cycle and the physical climate system. Changes in the physical climate affect the exchange of CO 2 between the atmosphere and the underlying land and ocean, and the resulting changes in atmospheric concentration of CO 2 in turn affect the physical climate. Aspects of the

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G. J. Boer and V. K. Arora

functional types (PFTs), namely, needleleaf evergreen and deciduous trees, broadleaf evergreen and cold and dry deciduous trees, and C3 and C4 crops and grasses ( Arora and Boer 2010 ). CTEM treats land use change interactively as a contribution to the flux between land and ocean, rather than as an external emission component. The Canadian Model of Ocean Carbon (CMOC) simulates the ocean carbon budget and its interaction with the atmosphere. CMOC includes an inorganic chemistry module (solubility pump

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Lifen Jiang, Yaner Yan, Oleksandra Hararuk, Nathaniel Mikle, Jianyang Xia, Zheng Shi, Jerry Tjiputra, Tongwen Wu, and Yiqi Luo

.1 . Thornton , P. E. , J.-F. Lamarque , N. A. Rosenbloom , and N. M. Mahowald , 2007 : Influence of carbon–nitrogen cycle coupling on land model response to CO 2 fertilization and climate variability . Global Biogeochem. Cycles , 21 , GB4018 , doi: 10.1029/2006GB002868 . Thornton , P. E. , and Coauthors , 2009 : Carbon–nitrogen interactions regulate climate–carbon cycle feedbacks: Results from an atmosphere–ocean general circulation model . Biogeosciences , 6 , 2099 – 2120 , doi: 10

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Pu Shao, Xubin Zeng, Koichi Sakaguchi, Russell K. Monson, and Xiaodong Zeng

1. Introduction The global carbon cycle consists of the combined interactions among a series of carbon reservoirs in the earth system (such as CO 2 in the atmosphere, soil organic carbon and vegetation, and carbonate and phytoplankton in the ocean) and all the fluxes and feedbacks that regulate dynamics in the sizes of these reservoirs. Most of the sensitivity and uncertainty in coupled carbon–climate projections lie in the terrestrial (rather than oceanic) carbon cycle (e.g., Zeng et al

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A. Anav, P. Friedlingstein, M. Kidston, L. Bopp, P. Ciais, P. Cox, C. Jones, M. Jung, R. Myneni, and Z. Zhu

1. Introduction Earth system models (ESMs) are complex numerical tools designed to simulate physical, chemical, and biological processes taking place on Earth between the atmosphere, the land, and the ocean. Worldwide, only a few research institutions have developed such models and used them to carry out historical and future simulations in order to project future climate change. ESMs, and numerical models in general, are never perfect. Consequently, before using their results to make future

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