Timescales
Martin Heimann (Jena)
With 2 Figures
The climate system and the global carbon cycle constitute a tightly coupled system: changes in atmospheric carbon dioxide concentration (CO2) modify the radiative balance of the atmos-phere which impact the climate at the surface of the Earth, while changes in climate impact the major sources and sinks of CO2 on land and in the ocean which control the atmospheric CO2 concentration level. Figure 1 shows a conceptual view of this system, whereby only the
“fast” components are considered, i.e. CO2 in the atmosphere, dissolved carbon in the ocean in inorganic and organic forms, carbon stored in terrestrial vegetation and soil. The “slow”
carbon cycle, i.e. carbon cycling with the lithosphere through volcanism, erosion and sedi-mentation on timescales of 100,000 years and more are neglected.
Currently, this system is massively perturbed by the anthropogenic inputs of CO2 from the burning of fossil fuels and changes in land use (a. o. deforestation). In the past, however, this system was primarily perturbed by natural changes in radiative forcing, such as the ice-age
Fig. 1 Schematic of the coupled global climate – global carbon cycle system
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cycles. Which sign has and how strong is the feedback loop in this system? i. e. how strongly is a perturbation of the system amplified or damped if the feedback loop is included or not? This question has been addressed in Friedlingstein et al. (2003), who defined the terrestrial gL and oceanic gO climate sensitivity as the amount of carbon gained or lost from these reservoirs for a global average temperature increase of 1K in the absence of any other perturbation. Likewise, the geochemical carbon cycle sensitivities bL and bO were defined as the land and oceanic carbon reservoir changes to an atmospheric change in CO2 concentration of 1 ppm. Using this concept, a simple mathematical representation of the coupled system feedback loop is readily derived. This concept has been extensively used to analyse comprehensive global coupled car-bon cycle – climate model simulations over the industrial period until the year 2100; e.g. for the C4MIP models (Friedlingstein et al. 2006) and the more recent CMIP5 models (Arora et al. 2013, Friedlingstein et al. 2014). In general, these models show overall a positive feedback, however, with a large variability of responses mostly with respect to the response of the terrestrial carbon system. It is therefore of critical importance to explore the range of possible constraints provided by observations of carbon cycle – climate variations in the past.
Fig. 2 Apparent carbon cycle – climate sensitivity (change in atmospheric CO2 per 1 K change in global temperature) estimated from different climate records and models. Upper part: observational estimates as a function of time scale;
lower part: calculated sensitivity from C4MIP and CMIP5 models.
Using a simple theoretical perturbation analysis framework, it is easy to show that the mag-nitudes of the climate (gL, gO) and the carbon cycle (bL, gO) sensitivities and the combined feedback factor are strongly dependent on the timescale of the perturbation. While these
sensi-Constraints on Global Climate-Carbon Cycle Feedbacks
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tivities are not directly observable (however they can be determined of models by perturbation simulation experiments), observations of past variations of atmospheric CO2 and concurrent estimates of global average temperature changes provide a constraint on the “apparent carbon cycle – climate sensitivity” S, which is defined here as the change in global CO2 per change in temperature for a given climate variation. S can be derived from the individual carbon reservoir sensitivities (gL, gO, bL, bO) defined above and is also a function of timescale of the perturba-tion. Figure 2 shows in the upper part a summary of observational evidence from the literature of S as a function of time scale (indicated on the y-axis), from interannual variations to gla-cial-interglacial cycles. In the lower part of Figure 2 are shown the distributions of estimates of S from the C4MIP and CMIP5 model simulations, which pertain to a 50 –100 year timescale.
The observational estimates of the apparent carbon cycle – climate system sensitivity exhibit higher values for longer timescales. This is evident given that the dynamics of the more inert carbon pools on land (e. g. deeper soils, permafrost) and in the ocean (e.g. deeper waters, sur-face sediments) can only be excited if a perturbation last longer. For the current climate change problem, this analysis indicates that observational evidence on the carbon cycle – climate sensi-tivity is at the lower end of the C4MIP and the CMIP5 models. On the other hand, in the present framework the estimates from the observed estimates of the glacial – interglacial changes in CO2 and temperature provide an upper bound on the carbon cycle – climate sensitivity. Explor-ing further observational constraints on S and its underlyExplor-ing terrestrial and oceanic sensitivities as a function of time scale constitutes an important goal for carbon cycle – climate research.
References
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Frank, D. C., Esper, J., Raible, C. C., Buentgen, U., Trouet, V., Stocker, B., and Joos, F.: Ensemble recon-struction constraints on the global carbon cycle sensitivity to climate. Nature 463, 527–530 (2010)
Friedlingstein, P., Cox, P., Betts, R. A., Bopp, L., Bloh, W. von, Brovkin, V., Cadule, P., Doney, S., Eby, M., and Fung, I.: Climate–carbon cycle feedback analysis: Results from the C4MIP model intercomparison. J.
Climate 19, 3337–3353 (2006)
Friedlingstein, P., Dufresne, J. L., Cox, P. M., and Rayner, P. J.: How positive is the feedback between climate change and the carbon cycle. Tellus 55, 692–700 (2003)
Friedlingstein, P., Meinshausen, M., Arora, V. K., Jones, C. D., Anav, A., Liddicoat, S. K., and Knutti, R.:
Uncertainties in CMIP5 climate projections due to carbon cycle feedbacks. J. Climate 27, 511–526 (2014) Rafelski, L. E., Piper, S. C., and Keeling, R. F.: Climate effects on atmospheric carbon dioxide over the last
cen-tury. Tellus B 61, 718 –731 (2009)
Shakun, J. D., Clark, P. U., He, F., Marcott, S. A., Mix, A. C., Liu, Z., Otto-Bliesner, B., Schmittner, A., and Bard, E.: Global warming preceded by increasing carbon dioxide concentrations during the last deglaciation.
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Torn, M. S., and Harte, J.: Missing feedbacks, asymmetric uncertainties, and the underestimation of future warm-ing. Geophys. Res. Lett. 33, L10703; doi:10.1029/2005GL025540 (2006)
Prof. Dr. Martin Heimann
Max Planck Institute for Biogeochemistry
Postfach 100164 Phone: +49 3641 576350
07701 Jena Fax: +49 3641 577300
Germany E-Mail: martin.heimann@bgc-jena.mpg.de
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