Abstract
Abstract The simulation of atmospheric–land–ocean CO2 exchange for the 1850–2000 period offers the possibility of testing and calibrating the carbon budget in earth system models by comparing the simulated changes in atmospheric CO2 concentration and in land and ocean uptake with observation-based information. In particular, some of the uncertainties associated with the treatment of land use change (LUC) and the role of down regulation in affecting the strength of CO2 fertilization for terrestrial photosynthesis are assessed using the Canadian Centre for Climate Modelling and Analysis Earth System Model (CanESM1). LUC emissions may be specified as an external source of CO2 or calculated interactively based on estimated changes in crop area. The evidence for photosynthetic down regulation is reviewed and an empirically based representation is implemented and tested in the model. Four fully coupled simulations are performed: with and without terrestrial photosynthesis down regulation and with interactively determined or specified LUC emissions. Simulations without terrestrial photosynthesis down regulation yield 15–20 ppm lower atmospheric CO2 by the end of the twentieth century, compared to observations, regardless of the LUC approach used because of higher carbon uptake by land. Implementation of down regulation brings simulated values of atmospheric CO2 and land and ocean carbon uptake closer to observation-based values. The use of specified LUC emissions yields a large source in the tropics during the 1981–2000 period, which is inconsistent with studies suggesting the tropics to be near-neutral or small carbon sinks. The annual cycle of simulated global averaged CO2, dominated by the Northern Hemisphere terrestrial photosynthesis and respiration cycles, is reasonably well reproduced, as is the latitudinal distribution of CO2 and the dependence of interhemispheric CO2 gradient on fossil fuel emissions. The empirical approach used here offers a reasonable method of implementing down regulation in coupled carbon–climate models in the absence of a more explicit biogeochemical representation.
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