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Original Articles

Are response function representations of the global carbon cycle ever interpretable?

, &
Pages 361-371 | Received 07 May 2008, Accepted 22 Sep 2008, Published online: 18 Jan 2017

References

  • Caldeira, K., Hoffert, M. I. and Jain, A. 2000. Simple ocean carbon models. In: The Carbon Cycle (eds T. M. L. Wigley and D. S. Schimel).Cambridge University Press, Cambridge, 199–211.
  • Dowell, E. H. 1996. Eigenmode analysis in unsteady aerodynamics: reduced order models. AIAA J. 34, 1578–1588.
  • den Elzen, M. G. J. and Lucas, P. 2005. The FAIR model: a tool to analyse environmental and costs implications of regimes of future commitments. Environ. Modell. Assess. 10, 115–134.
  • Enting, I. G. 1990. Ambiguities in the calibration of carbon cycle models. Inverse Problems 6, L39–L46.
  • Enting, I. G. 2007. Laplace transform analysis of the carbon cycle. Environ. Modell. Software 22, 1488–1497.
  • Enting, I. G. and Trudinger, C. M. 2002. Modelling earth system change: I. Validating parameterisations for attribution calculations. CSIRO Atmospheric Research Technical Paper 56.
  • Gamier, H., Mensler, M. and Richard, A. 2003. Continuous-time model identification from sampled data: implementation issues and perfor-mance evaluation. Int. J. Contr 76, 1337–1357.
  • Godfrey, K. 1982. Compartmental Models and Their Application. Aca-demic Press, London.
  • Harvey, L. D. D. 2000. Response of the carbon cycle and other bio-geochemical cycles: translating emissions of GHGs and aerosols into concentrations and radiative forcing. In: Climate and Global Environmental Change (ed. L. D. D. Harvey). Pearson Education Ltd, Essex.
  • Hasselmann, K., Sausen, R., Maier-Reimer, E. and Voss, R. 1993. On the cold start problem in transient simulations with coupled atmosphere-ocean models. Clim. Dyn. 9, 53–61.
  • Hasselmann, K., Hasselmann, S., Giering, R., Ocana, V. and Storch, H. V. 1997. Sensitivity study of optimal CO2 emission paths using a sim-plied structural integrated assessment model (SIAM). Clim. Change 37, 345–386.
  • Hooss, G. 2001. Aggregate Models of Climate Change Development and Applications. PhD Thesis. Max-Planck-Institut fiir Meteorologie, Hamburg, Germany.
  • Hooss, G., Voss, R., Hasselman, K., Maier-Reimer, E. and co-authors. 2001. A nonlinear impulse response model of the cou-pled carbon cycle-climate system (NICCS). Clim. Dyn. 18, 189–202.
  • Jarvis, A. J., Young, P. C., Leedal, D. L. and Chotai, A. 2008. A robust sequential CO2 emissions strategy based on optimal con-trol of atmospheric CO2 concentrations. Clim. Change 86, 357–373
  • Joos, F., Bruno, M., Fink, R., Siegenthaler, U., Stocker, T. F and co-authors. 1996. An efficient and accurate representation of complex oceanic and biospheric models of anthropogenic carbon uptake. Tellus 48B, 397–417.
  • Kwon, O.Y. and Schnoor, J. L. 1994. Simple global carbon model: the atmosphere-terrestrial biosphere-ocean interaction. Global Bio-geochem. Cycles 8, 295–305.
  • Leedal, D. T. 2007. Sequential Decision Making in Climate Change Mit-igation: A Control System Perspective. PhD Thesis.Lancaster Univer-sity, Lancaster, UK.
  • Lenton, T. M. 2000. Land and ocean carbon cycle feedback effects on global warming in a simple Earth system model. Tellus 52B, 1159–1188.
  • Lowe, J. 2003. Parameters for tuning a simple climate model. (accessed from http://unfccc.int/resource/brazil/climate.html).
  • Maier-Reimer, E. and Hasselmann, K. 1987. Transport and storage of CO2 in the ocean - an inorganic ocean-circulation carbon cycle model. Clim. Dyn. 2, 63–90.
  • Maier-Reimer, E., Mikolajewicz, U. and Winguth, A. 1996. Future ocean uptake of CO2: interaction between ocean circulation and biology. Clim. Dyn. 12,711–721.
  • Meinshausen, M., Raper, S. C. B. and Wigley, T. M. L. 2008. Emulating IPCC AR4 atmosphere-ocean and carbon cycle models for projecting global-mean, hemispheric and land/ocean temperatures: MAGICC 6.0. Atmos. Chem. Phys. Discuss. 8, 6153–6272.
  • Meyer, R., Joos, F., Esser, G., Heimann, M., Hooss, G. and co-authors. 1999. The substitution of high-resolution terrestrial biosphere models and carbon sequestration in response to changing CO2 and climate. Global Biogeochem. Cycles 13, 785–802.
  • Moore, B. 1981. Principle component analysis in linear systems: con-trollability, observability, and model reduction. IEEE Trans. Auto. Contr 26, 17–32.
  • Nordaus, W. D. and Boyer, J. 2000. Warming the World: Economic Models of Global Warming. MIT Press, Cambridge, MA.
  • Orr, J. C., Maier-Reimer, E., Mikolajewicz, U., Monfray, P., Sarmiento, J. L., and co-authors. 2001. Estimates of anthropogenic carbon up-take from four three-dimensional global ocean models. Global Bio-geochem. Cycles 15,43–60.
  • Raper, S. C.B., Gregory, J. M. and Osborn, T. J. 2001. Use of an upwelling-diffusion energy balance climate model to simulate and diagnose A/OGCM results. Clim. Dyn. 17, 601–613.
  • Sarmiento, J., Hughes, T., Stouffer, R. and Manabe, S. 1998. Simulated response of the ocean carbon cycle to anthropogenic climate warming. Nature 393, 245–252.
  • Tang, D., Kholodar, D., Juang, J.N. and Dowell, E. H. 2001. System identification and proper orthogonal decomposi-tion applied to unsteady aerodynamics. AIAA J. 39, 1569–1576.
  • Thompson, M. V. and Randerson, J. T. 1999. Impulse response functions of terrestrial carbon cycle models: method and application. Global Change Biol. 5, 371–394.
  • Wigley, T. M. L. 1991. A simple inverse carbon cycle model. Global Biogeochem. Cycles 5, 373–382.
  • Wigley, T. M.L, Richels, R. and Edmonds, J. A. 1996. Economic and environmental choices in the stabilization of atmospheric CO2 con-centrations. Nature 379, 242–245.
  • Young, P. C. 1999. Data-based mechanistic modeling, generalized sen-sitivity and dominant mode analysis. Comput. Phys. Commun. 117, 113–129.
  • Young, P. C. 2000. Stochastic, dynamic modeling and signal processing: time variable and state dependent parameter estimation. In: Nonlinear and Nonstationaty Signal Processing (eds W. J. Fitzgerald, A. Walden, R. Smith and P. C. Young). Cambridge University Press, Cambridge, 74–114.
  • Young, P. C. and Beven, K. J. 1994. Data-based mechanistic mod-eling and the rainfall-flow nonlinearity. Environmetrics 5, 335–363.
  • Young, P. C. and Gamier, H. 2006. Identification and estimation of continuous-time, data-based mechanistic models for environmental systems. Environ. Model Software 21, 1055–1072.
  • Young, P. C., Parkinson, S. and Lees, M. J. 1996. Simplicity out of complexity: Occam's razor revisited. J. AppL Stat. 23, 165–210.