• Archer, D., 1996: A data-driven model of the global calcite lysocline. Global Biogeochem. Cycles, 10, 511526, doi:10.1029/96GB01521.

  • Arora, V. K., , and G. J. Boer, 2010: Uncertainties in the 20th century carbon budget associated with land use change. Global Change Biol., 16, 33273348.

    • Search Google Scholar
    • Export Citation
  • Arora, V. K., and Coauthors, 2009: The effect of terrestrial photosynthesis down regulation on the twentieth-century carbon budget simulated with the CCCma Earth System Model. J. Climate, 22, 60666088.

    • Search Google Scholar
    • Export Citation
  • Arora, V. K., and Coauthors, 2011: Carbon emission limits required to satisfy future representative concentration pathways of greenhouse gases. Geophys. Res. Lett., 38, L05805, doi:10.1029/2010GL046270.

    • Search Google Scholar
    • Export Citation
  • Assmann, K. M., , M. Bentsen, , J. Segschneider, , and C. Heinze, 2010: An isopycnic ocean carbon cycle model. Geosci. Model Dev., 3, 143167, doi:10.5194/gmd-3-143-2010.

    • Search Google Scholar
    • Export Citation
  • Aumont, O., , and L. Bopp, 2006: Globalizing results from ocean in situ iron fertilization studies. Global Biogeochem. Cycles, 20, GB2017, doi:10.1029/2005GB002591.

    • Search Google Scholar
    • Export Citation
  • Bacastow, R., , and E. Maier-Reimer, 1990: Ocean-circulation model of the carbon cycle. Climate Dyn., 4, 95125.

  • Boer, G. J., , and V. Arora, 2009: Temperature and concentration feedbacks in the carbon cycle. Geophys. Res. Lett., 36, L02704, doi:10.1029/2008GL036220.

    • Search Google Scholar
    • Export Citation
  • Boer, G. J., , and V. Arora, 2010: Geographic aspects of temperature and concentration feedbacks in the carbon budget. J. Climate, 23, 775784.

    • Search Google Scholar
    • Export Citation
  • Boer, G. J., , and V. Arora, 2013: Feedbacks in emissions-driven and concentration-driven global carbon budgets. J. Climate, 26, 33263341.

    • Search Google Scholar
    • Export Citation
  • Bonan, G. B., , and S. Levis, 2010: Quantifying carbon-nitrogen feedbacks in the Community Land Model (CLM4). Geophys. Res. Lett., 37, L07401, doi:10.1029/2010GL042430.

    • Search Google Scholar
    • Export Citation
  • Boucher, O., , A. Jones, , and R. Betts, 2009: Climate response to the physiological impact of carbon dioxide on plants in the Met Office Unified Model HadCM3. Climate Dyn., 32, 237249.

    • Search Google Scholar
    • Export Citation
  • Broecker, W. S., , and T.-H. Peng, 1986: Carbon cycle: 1985—Glacial to interglacial changes in the operation of the global carbon cycle. Radiocarbon, 28, 309327.

    • Search Google Scholar
    • Export Citation
  • Brovkin, V., , T. Raddatz, , C. H. Reick, , M. Claussen, , and V. Gayler, 2009: Global biogeophysical interactions between forest and climate. Geophys. Res. Lett., 36, L07405, doi:10.1029/2009GL037543.

    • Search Google Scholar
    • Export Citation
  • Christian, J. R., and Coauthors, 2010: The global carbon cycle in the Canadian Earth System Model (CanESM1): Preindustrial control simulation. J. Geophys. Res., 115, G03014, doi:10.1029/2008JG000920.

    • Search Google Scholar
    • Export Citation
  • Coleman, K., , and D. S. Jenkinson, 1999: ROTHC-26.3: A model for the turnover of carbon in soil. IACR Rep., 43 pp [Available online at http://www.rothamsted.ac.uk/aen/carbon/mod26_3_dos.pdf.]

  • Collins, W. J., and Coauthors, 2011: Development and evaluation of an Earth-system model—HadGEM2. Geosci. Model Dev., 4, 10511075.

  • Cox, P. M., 2001: Description of the TRIFFID dynamic global vegetation model. Met Office Hadley Centre Tech. Note 24, 17 pp.

  • Dufresne, J.-L., and Coauthors, 2013: Climate change projections using the IPSL-CM5 Earth System Model: From CMIP3 to CMIP5. Climate Dyn., 40, 21232165, doi:10.1007/s00382-012-1636-1.

    • Search Google Scholar
    • Export Citation
  • Eby, M., and Coauthors, 2009: Lifetime of anthropogenic climate change: Millennial time scales of potential CO2 and surface temperature perturbations. J. Climate, 22, 25012511.

    • Search Google Scholar
    • Export Citation
  • Essery, R. L. H., , M. J. Best, , R. A. Betts, , P. M. Cox, , and C. M. Taylor, 2003: Explicit representation of subgrid heterogeneity in a GCM land-surface scheme. J. Hydrometeor., 4, 530543.

    • Search Google Scholar
    • Export Citation
  • Fichefet, T., , and M. A. Morales Maqueda, 1997: Sensitivity of a global sea ice model to the treatment of ice thermodynamics and dynamics. J. Geophys. Res., 102 (C6), 12 60912 646.

    • Search Google Scholar
    • Export Citation
  • Friedlingstein, P., , J.-L. Dufresne, , P. M. Cox, , and P. Rayner, 2003: How positive is the feedback between climate change and the carbon cycle? Tellus, 55B, 692700.

    • Search Google Scholar
    • Export Citation
  • Friedlingstein, P., and Coauthors, 2006: Climate–carbon cycle feedback analysis: Results from the C4MIP model intercomparison. J. Climate, 19, 33373353.

    • Search Google Scholar
    • Export Citation
  • Gent, P. R., and Coauthors, 2011: The Community Climate System Model version 4. J. Climate, 24, 49734991.

  • Goodwin, P., , and T. M. Lenton, 2009: Quantifying the feedback between ocean heating and CO2 solubility as an equivalent carbon emission. Geophys. Res. Lett., 36, L15609, doi:10.1029/2009GL039247.

    • Search Google Scholar
    • Export Citation
  • Gregory, J. M., , C. D. Jones, , P. Cadule, , and P. Friedlingstein, 2009: Quantifying carbon cycle feedbacks. J. Climate, 22, 52325250.

  • Griffies, S. M., and Coauthors, 2005: Formulation of an ocean model for global climate simulations. Ocean Sci.,1, 45–79.

  • Hasumi, H., 2007: CCSR Ocean Component Model (COCO) version 4.0. The University of Tokyo Center for Climate System Research Rep., 111 pp. [Available online at http://ccsr.aori.u-tokyo.ac.jp/~hasumi/COCO/coco4.pdf.]

  • Heinze, C., , A. Hupe, , E. Maier-Reimer, , N. Dittert, , and O. Ragueneau, 2003: Sensitivity of the marine biospheric Si cycle for biogeochemical parameter variations. Global Biogeochem. Cycles, 17, 1086, doi:10.1029/2002GB001943.

    • Search Google Scholar
    • Export Citation
  • Hourdin, F., and Coauthors, 2006: The LMDZ4 general circulation model: Climate performance and sensitivity to parametrized physics with emphasis on tropical convection. Climate Dyn.,27, 787–813, doi:10.1007/s00382-006-0158-0.

  • Ilyina, T., , K. D. Six, , J. Segschneider, , E. Maier-Reimer, , H. Li, , and I. Núñez-Riboni, 2013: The global ocean biogeochemistry model HAMOCC: Model architecture and performance as component of the MPI-Earth System Model in different CMIP5 experimental realizations. J. Adv. Model. Earth Syst., doi:10.1002/jame.20017, in press.

    • Search Google Scholar
    • Export Citation
  • Ito, A., , and T. Oikawa, 2002: A simulation model of the carbon cycle in land ecosystems (Sim-CYCLE): A description based on dry-matter production theory and plot-scale validation. Ecol. Modell., 151 (2–3), 143176.

    • Search Google Scholar
    • Export Citation
  • Ji, J., , M. Huang, , and K. Li, 2008: Prediction of carbon exchange between China terrestrial ecosystem and atmosphere in 21st century. Sci. China,51D, 885898.

    • Search Google Scholar
    • Export Citation
  • Johns, T. C., and Coauthors, 2006: The new Hadley Centre climate model (HadGEM1): Evaluation of coupled simulations. J. Climate, 19, 13271353.

    • Search Google Scholar
    • Export Citation
  • Jones, C., , C. McConnell, , K. Coleman, , P. Cox, , P. Falloon, , D. Jenkinson, , and D. Powlson, 2005: Global climate change and soil carbon stocks; predictions from two contrasting models for the turnover of organic carbon in soil. Global Change Biol., 11, 154166.

    • Search Google Scholar
    • Export Citation
  • Jones, C., and Coauthors, 2011: The HadGEM2-ES implementation of CMIP5 centennial simulations. Geosci. Model Dev., 4, 543570, doi:10.5194/gmd-4-543-2011.

    • Search Google Scholar
    • Export Citation
  • Jungclaus, J. H., and Coauthors, 2006: Ocean circulation and tropical variability in the coupled model ECHAM5/MPI-OM. J. Climate, 19, 39523972.

    • Search Google Scholar
    • Export Citation
  • Jungclaus, J. H., and Coauthors, 2013: Characteristics of the ocean simulations in MPIOM, the ocean component of the MPI-Earth System Model. J. Adv. Model. Earth Syst., doi:10.1002/jame.20023, in press.

    • Search Google Scholar
    • Export Citation
  • Kawamiya, M., M. J. Kishi, and N, . Suginohara, N., 2000: An ecosystem model for the North Pacific embedded in a general circulation model. Part II: Mechanisms forming seasonal variations of chlorophyll. J. Mar. Syst.,25, 159–178.

  • Krinner, G., and Coauthors, 2005: A dynamic global vegetation model for studies of the coupled atmosphere-biosphere system. Global Biogeochem. Cycles, 19, GB1015, doi:10.1029/2003GB002199.

    • Search Google Scholar
    • Export Citation
  • Lawrence, D. M., and Coauthors, 2011: Parameterization improvements and functional and structural advances in version 4 of the Community Land Model. J. Adv. Model. Earth Syst., 3, doi:10.1029/2011MS000045.

    • Search Google Scholar
    • Export Citation
  • Lawrence, D. M., , K. W. Oleson, , M. G. Flanner, , C. G. Fletcher, , P. J. Lawrence, , S. Levis, , S. C. Swenson, , and G. B. Bonan, 2012: The CCSM4 land simulation, 1850–2005: Assessment of surface climate and new capabilities. J. Climate, 25, 22402260.

    • Search Google Scholar
    • Export Citation
  • Luo, Y., , D. A. Sims, , R. B. Thomas, , D. T. Tissue, , and J. T. Ball, 1996: Sensitivity of leaf photosynthesis to CO2 concentration is an invariant function for C3 plants: A test with experimental data and global applications. Global Biogeochem. Cycles, 10, 209222.

    • Search Google Scholar
    • Export Citation
  • MacDougall, A. H., , C. A. Avis, , and A. J. Weaver, 2012: Significant contribution to climate warming from the permafrost carbon feedback. Nat. Geosci., 5, 719721, doi:10.1038/ngeo1573.

    • Search Google Scholar
    • Export Citation
  • Madec, G., 2008: NEMO ocean engine. IPSL Tech. Note, 332 pp.

  • Maier-Reimer, E., , I. Kriest, , J. Segschneider, , and P. Wetzel, 2005: The Hamburg Ocean Carbon Cycle Model HAMOCC5.1—Technical description release 1.1. MPI Earth System Science Rep. 14, 57 pp.

  • Marti, O., and Coauthors, 2010: Key features of the IPSL ocean atmosphere model and its sensitivity to atmospheric resolution. Climate Dyn., 34, 126, doi:10.1007/s00382-009-0640-6.

    • Search Google Scholar
    • Export Citation
  • Martin, G. M., and Coauthors, 2011: The HadGEM2 family of Met Office Unified Model Climate configurations. Geosci. Model Dev., 4, 723757.

    • Search Google Scholar
    • Export Citation
  • Matthews, H. D., , A. J. Weaver, , K. J. Meissner, , N. P. Gillett, , and M. Eby, 2004: Natural and anthropogenic climate change: Incorporating historical land cover change, vegetation dynamics and the global carbon cycle. Climate Dyn., 22, 461479, doi:10.1007/s00382-004-0392-2.

    • Search Google Scholar
    • Export Citation
  • Meissner, K. J., , A. J. Weaver, , H. D. Matthews, , and P. M. Cox, 2003: The role of land surface dynamics in glacial inception: A study with the UVic Earth System Model. Climate Dyn., 21, 515537, doi:10.1007/s00382-003-0352-2.

    • Search Google Scholar
    • Export Citation
  • Murray, R. J., 1996: Explicit generation of orthogonal grids for ocean models. J. Comput. Phys., 126, 251273.

  • Nozawa, T., , T. Nagashima, , T. Ogura, , T. Yokohata, , N. Okada, , and H. Shiogama, 2007: Climate Change Simulations with a Coupled Ocean-Atmosphere GCM Called the Model for Interdisciplinary Research on Climate: MIROC. Supercomputer Monogr. Rep., Vol. 12, Center for Global Environmental Research, 79 pp.

  • Oschlies, A., 2001: Model-derived estimates of new production: New results point towards lower values. Deep-Sea Res. II, 48, 21732197.

    • Search Google Scholar
    • Export Citation
  • Palmer, J. R., , and I. J. Totterdell, 2001: Production and export in a global ocean ecosystem model. Deep-Sea Res. I, 48, 11691198, doi:10.1016/S0967-0637(00)00080-7.

    • Search Google Scholar
    • Export Citation
  • Plattner, G.-K., and Coauthors, 2008: Long-term climate commitments projected with climate–carbon cycle models. J. Climate, 21, 27212751.

    • Search Google Scholar
    • Export Citation
  • Qian, H., , R. Joseph, , and N. Zeng, 2010: Enhanced terrestrial carbon uptake in the northern high latitudes in the 21st century from the Coupled Carbon Cycle Climate Model Intercomparison Project model projections. Global Change Biol., 16, 641656.

    • Search Google Scholar
    • Export Citation
  • Raddatz, T. J., and Coauthors, 2007: Will the tropical land biosphere dominate the climate–carbon cycle feedback during the twenty-first century? Climate Dyn., 29, 565574, doi:10.1007/s00382-007-0247-8.

    • Search Google Scholar
    • Export Citation
  • Roeckner, E., and Coauthors, 2003: The atmospheric general circulation model ECHAM5. Part I: Model description. Max Planck Institute for Meteorology Rep. 349, 127 pp.

  • Roy, T., and Coauthors, 2011: Regional impacts of climate change and atmospheric CO2 on future ocean carbon uptake: A multimodel linear feedback analysis. J. Climate, 24, 23002318.

    • Search Google Scholar
    • Export Citation
  • Sato, H., , A. Itoh, , and T. Kohyama, 2007: SEIB–DGVM: A new Dynamic Global Vegetation Model using a spatially explicit individual-based approach. Ecol. Modell., 200, 279307, doi:10.1016/j.ecolmodel.2006.09.006.

    • Search Google Scholar
    • Export Citation
  • Schmittner, A., , A. Oschlies, , H. D. Matthews, , and E. D. Galbraith, 2007: Future changes in climate, ocean circulation, ecosystems and biogeochemical cycling simulated for a business-as-usual CO2 emission scenario until year 4000 AD. Global Biogeochem. Cycles, 22, 10131034, doi:10.1029/2007GB002953.

    • Search Google Scholar
    • Export Citation
  • Seland, Ø., , T. Iversen, , A. Kirkevåg, , and T. Storelvmo, 2008: Aerosol-climate interactions in the CAM-Oslo atmospheric GCM and investigation of associated basic shortcomings. Tellus, 60A, 459491.

    • Search Google Scholar
    • Export Citation
  • Stevens, B., and Coauthors, 2013: The atmospheric component of the MPI-M Earth System Model: ECHAM6. J. Adv. Model. Earth Syst., doi:10.1002/jame.20015, in press.

    • Search Google Scholar
    • Export Citation
  • Sudo, K., , M. Takahashi, , J. Kurokawa, , and H. Akimoto, 2002: CHASER: A global chemical model of the troposphere 1. Model description. J. Geophys. Res., 107, 4339, doi:10.1029/2001JD001113.

    • Search Google Scholar
    • Export Citation
  • Takata, K., , S. Emori, , and T. Watanabe, 2003: Development of the minimal advanced treatments of surface interaction and runoff. Global Planet. Change,38, 209–222, doi:10.1016/S0921-8181(03)00030-4.

  • Takemura, T., , H. Okamoto, , Y. Maruyama, , A. Numaguti, , A. Higurashi, , and T. Nakajima, 2000: Global three-dimensional simulation of aerosol optical thickness distribution of various origins. J. Geophys. Res., 105 (D14), 17 85317 873.

    • Search Google Scholar
    • Export Citation
  • Taylor, K. E., , R. J. Stouffer, , and G. A. Meehl, 2012: An overview of CMIP5 and the experiment design. Bull. Amer. Meteor. Soc., 93, 485498.

    • Search Google Scholar
    • Export Citation
  • 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 CO2 fertilization and climate variability. Global Biogeochem. Cycles, 21, GB4018, doi:10.1029/2006GB002868.

    • Search Google Scholar
    • Export Citation
  • Thornton, P. E., and Coauthors, 2009: Carbon-nitrogen interactions regulate climate-carbon cycle feedbacks: Results from an atmosphere-ocean general circulation model. Biogeosciences, 6, 20992120, doi:10.5194/bg-6-2099-2009.

    • Search Google Scholar
    • Export Citation
  • Tjiputra, J. F., , C. Roelandt, , M. Bentsen, , D. M. Lawrence, , T. Lorentzen, , J. Schwinger, , Ø. Seland, , and C. Heinze, 2013: Evaluation of the carbon cycle components in the Norwegian Earth System Model (NorESM). Geosci. Model Dev., 6, 301325, doi:10.5194/gmd-6-301-2013.

    • Search Google Scholar
    • Export Citation
  • Wanninkhof, R., 1992: Relationship between wind speed and gas exchange over the ocean. J. Geophys. Res., 97 (C5), 73737382.

  • Watanabe, S., , H. Miura, , M. Sekiguchi, , T. Nagashima, , K. Sudo, , S. Emori, , and M. Kawamiya, 2008: Development of an atmospheric general circulation model for integrated Earth system modeling on the Earth Simulator. J. Earth Simul., 9, 2735.

    • Search Google Scholar
    • Export Citation
  • Watanabe, S., and Coauthors, 2011: MIROC-ESM 2010: Model description and basic results of CMIP5-20c3m experiments. Geosci. Model Dev., 4, 845872.

    • Search Google Scholar
    • Export Citation
  • Weaver, A. J., and Coauthors, 2001: The UVic earth system climate model: Model description, climatology, and applications to past, present and future climates. Atmos.–Ocean, 39, 361428, doi:10.1080/07055900.2001.9649686.

    • Search Google Scholar
    • Export Citation
  • Weiss, R. F., 1974: Carbon dioxide in water and seawater: The solubility of a non-ideal gas. Mar. Chem., 2, 203215.

  • Wu, T., 2012: A mass-flux cumulus parameterization scheme for large-scale models: Description and test with observations. Climate Dyn., 38, 725744, doi:10.1007/s00382-011-0995-3.

    • Search Google Scholar
    • Export Citation
  • Wu, T., , R. Yu, , and F. Zhang, 2008: A modified dynamic framework for atmospheric spectral model and its application. J. Atmos. Sci., 65, 22352253.

    • Search Google Scholar
    • Export Citation
  • Wu, T., and Coauthors, 2010: The Beijing Climate Center atmospheric general circulation model: Description and its performance for the present-day climate. Climate Dyn., 34, 123147.

    • Search Google Scholar
    • Export Citation
  • Wu, T., and Coauthors, 2013: Global carbon budgets simulated by the Beijing Climate Center Climate System Model for the last century. J. Geophys. Res., 118, 43264347, doi:10.1002/jgrd.50320.

    • Search Google Scholar
    • Export Citation
  • Yamanaka, Y., , and E. Tajika, 1996: The role of the vertical fluxes of particulate organic matter and calcite in the oceanic carbon cycle: Studies using an ocean biogeochemical general circulation model. Global Biogeochem. Cycles, 10, 361382.

    • Search Google Scholar
    • Export Citation
  • Zaehle, S., , P. Friedlingstein, , and A. D. Friend, 2010: Terrestrial nitrogen feedbacks may accelerate future climate change. Geophys. Res. Lett., 37, L01401, doi:10.1029/2009GL041345.

    • Search Google Scholar
    • Export Citation
  • Zahariev, K., , J. R. Christian, , and K. L. Denman, 2008: Preindustrial, historical, and fertilization simulations using a global ocean carbon model with new parameterizations of iron limitation, calcification, and N2 fixation. Prog. Oceanogr., 77, 5682.

    • Search Google Scholar
    • Export Citation
  • Zhang, Q., , Y. P. Wang, , A. J. Pitman, , and Y. J. Dai, 2011: Limitations of nitrogen and phosphorous on the terrestrial carbon uptake in the 20th century. Geophys. Res. Lett., 38, L22701, doi:10.1029/2011GL049244.

    • Search Google Scholar
    • Export Citation
  • Zickfeld, K., , M. Eby, , H. D. Matthews, , A. Schmittner, , and A. J. Weaver, 2011: Nonlinearity of carbon cycle feedbacks. J. Climate, 24, 42544274.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 409 409 145
PDF Downloads 260 260 103

Carbon–Concentration and Carbon–Climate Feedbacks in CMIP5 Earth System Models

View More View Less
  • 1 Canadian Centre for Climate Modelling and Analysis, Environment Canada, University of Victoria, Victoria, British Columbia, Canada
  • 2 College of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter, United Kingdom
  • 3 School of Earth and Ocean Sciences, University of Victoria, Victoria, British Columbia, Canada
  • 4 Met Office Hadley Centre, Exeter, United Kingdom
  • 5 National Center for Atmospheric Research, Boulder, Colorado
  • 6 LSCE, IPSL, CEA, UVSQ, CNRS, Gif-sur-Yvette, France
  • 7 Max Planck Institute for Meteorology, Hamburg, Germany
  • 8 Research Institute for Global Change, Japan Agency for Marine-Earth Science and Technology, Yokohama, Japan
  • 9 Uni Klima, Uni Research, Bergen, Norway
  • 10 Beijing Climate Center, China Meteorological Administration, Beijing, China
© Get Permissions
Restricted access

Abstract

The magnitude and evolution of parameters that characterize feedbacks in the coupled carbon–climate system are compared across nine Earth system models (ESMs). The analysis is based on results from biogeochemically, radiatively, and fully coupled simulations in which CO2 increases at a rate of 1% yr−1. These simulations are part of phase 5 of the Coupled Model Intercomparison Project (CMIP5). The CO2 fluxes between the atmosphere and underlying land and ocean respond to changes in atmospheric CO2 concentration and to changes in temperature and other climate variables. The carbon–concentration and carbon–climate feedback parameters characterize the response of the CO2 flux between the atmosphere and the underlying surface to these changes. Feedback parameters are calculated using two different approaches. The two approaches are equivalent and either may be used to calculate the contribution of the feedback terms to diagnosed cumulative emissions. The contribution of carbon–concentration feedback to diagnosed cumulative emissions that are consistent with the 1% increasing CO2 concentration scenario is about 4.5 times larger than the carbon–climate feedback. Differences in the modeled responses of the carbon budget to changes in CO2 and temperature are seen to be 3–4 times larger for the land components compared to the ocean components of participating models. The feedback parameters depend on the state of the system as well the forcing scenario but nevertheless provide insight into the behavior of the coupled carbon–climate system and a useful common framework for comparing models.

The National Center for Atmospheric Research is sponsored by the National Science Foundation.

Corresponding author address: Vivek K. Arora, Canadian Centre for Climate Modelling and Analysis, Environment Canada, University of Victoria, Victoria BC V8W 2Y2, Canada. E-mail: vivek.arora@ec.gc.ca

This article is included in the (C4MIP) Climate–Carbon Interactions in the CMIP5 Earth System Models special collection.

Abstract

The magnitude and evolution of parameters that characterize feedbacks in the coupled carbon–climate system are compared across nine Earth system models (ESMs). The analysis is based on results from biogeochemically, radiatively, and fully coupled simulations in which CO2 increases at a rate of 1% yr−1. These simulations are part of phase 5 of the Coupled Model Intercomparison Project (CMIP5). The CO2 fluxes between the atmosphere and underlying land and ocean respond to changes in atmospheric CO2 concentration and to changes in temperature and other climate variables. The carbon–concentration and carbon–climate feedback parameters characterize the response of the CO2 flux between the atmosphere and the underlying surface to these changes. Feedback parameters are calculated using two different approaches. The two approaches are equivalent and either may be used to calculate the contribution of the feedback terms to diagnosed cumulative emissions. The contribution of carbon–concentration feedback to diagnosed cumulative emissions that are consistent with the 1% increasing CO2 concentration scenario is about 4.5 times larger than the carbon–climate feedback. Differences in the modeled responses of the carbon budget to changes in CO2 and temperature are seen to be 3–4 times larger for the land components compared to the ocean components of participating models. The feedback parameters depend on the state of the system as well the forcing scenario but nevertheless provide insight into the behavior of the coupled carbon–climate system and a useful common framework for comparing models.

The National Center for Atmospheric Research is sponsored by the National Science Foundation.

Corresponding author address: Vivek K. Arora, Canadian Centre for Climate Modelling and Analysis, Environment Canada, University of Victoria, Victoria BC V8W 2Y2, Canada. E-mail: vivek.arora@ec.gc.ca

This article is included in the (C4MIP) Climate–Carbon Interactions in the CMIP5 Earth System Models special collection.

Save