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    A model-based constraint on CO2 fertilisation
    (München : European Geopyhsical Union, 2013) Holden, P.B.; Edwards, N.R.; Gerten, D.; Schaphoff, S.
    We derive a constraint on the strength of CO2 fertilisation of the terrestrial biosphere through a "top-down" approach, calibrating Earth system model parameters constrained by the post-industrial increase of atmospheric CO2 concentration. We derive a probabilistic prediction for the globally averaged strength of CO2 fertilisation in nature, for the period 1850 to 2000 AD, implicitly net of other limiting factors such as nutrient availability. The approach yields an estimate that is independent of CO2 enrichment experiments. To achieve this, an essential requirement was the incorporation of a land use change (LUC) scheme into the GENIE Earth system model. Using output from a 671-member ensemble of transient GENIE simulations, we build an emulator of the change in atmospheric CO2 concentration change since the preindustrial period. We use this emulator to sample the 28-dimensional input parameter space. A Bayesian calibration of the emulator output suggests that the increase in gross primary productivity (GPP) in response to a doubling of CO2 from preindustrial values is very likely (90% confidence) to exceed 20%, with a most likely value of 40–60%. It is important to note that we do not represent all of the possible contributing mechanisms to the terrestrial sink. The missing processes are subsumed into our calibration of CO2 fertilisation, which therefore represents the combined effect of CO2 fertilisation and additional missing processes. If the missing processes are a net sink then our estimate represents an upper bound. We derive calibrated estimates of carbon fluxes that are consistent with existing estimates. The present-day land–atmosphere flux (1990–2000) is estimated at −0.7 GTC yr−1 (likely, 66% confidence, in the range 0.4 to −1.7 GTC yr−1). The present-day ocean–atmosphere flux (1990–2000) is estimated to be −2.3 GTC yr−1 (likely in the range −1.8 to −2.7 GTC yr−1). We estimate cumulative net land emissions over the post-industrial period (land use change emissions net of the CO2 fertilisation and climate sinks) to be 66 GTC, likely to lie in the range 0 to 128 GTC.
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    Evaluation of biospheric components in earth system models using modern and palaeo-observations: The state-of-the-art
    (München : European Geopyhsical Union, 2013) Foley, A.M.; Dalmonech, D.; Friend, A.D.; Aires, F.; Archibald, A.T.; Bartlein, P.; Bopp, L.; Chappellaz, J.; Cox, P.; Edwards, N.R.; Feulner, G.; Friedlingstein, P.; Harrison, S.P.; Hopcroft, P.O.; Jones, C.D.; Kolassa, J.; Levine, J.G.; Prentice, I.C.; Pyle, J.; Vázquez Riveiros, N.; Wolff, E.W.; Zaehle, S.
    Earth system models (ESMs) are increasing in complexity by incorporating more processes than their predecessors, making them potentially important tools for studying the evolution of climate and associated biogeochemical cycles. However, their coupled behaviour has only recently been examined in any detail, and has yielded a very wide range of outcomes. For example, coupled climate–carbon cycle models that represent land-use change simulate total land carbon stores at 2100 that vary by as much as 600 Pg C, given the same emissions scenario. This large uncertainty is associated with differences in how key processes are simulated in different models, and illustrates the necessity of determining which models are most realistic using rigorous methods of model evaluation. Here we assess the state-of-the-art in evaluation of ESMs, with a particular emphasis on the simulation of the carbon cycle and associated biospheric processes. We examine some of the new advances and remaining uncertainties relating to (i) modern and palaeodata and (ii) metrics for evaluation. We note that the practice of averaging results from many models is unreliable and no substitute for proper evaluation of individual models. We discuss a range of strategies, such as the inclusion of pre-calibration, combined process- and system-level evaluation, and the use of emergent constraints, that can contribute to the development of more robust evaluation schemes. An increasingly data-rich environment offers more opportunities for model evaluation, but also presents a challenge. Improved knowledge of data uncertainties is still necessary to move the field of ESM evaluation away from a "beauty contest" towards the development of useful constraints on model outcomes.