Using a GCM analogue model to investigate the potential for Amazonian forest dieback
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A combined GCM analogue model and GCM land surface representation is used to investigate the influences of climatology and land surface parameterisation on modelled Amazonian vegetation change. This modelling structure (called IMOGEN) captures the main features of the changes in surface climate as estimated by a GCM with enhanced atmospheric greenhouse gas concentrations. Advantage is taken of IMOGEN’s computational speed which allows multiple simulations to be carried out to assess the robustness of the GCM results.
The timing of forest dieback is found to be sensitive to the initial “pre-industrial” climate, as well as uncertainties in the representation of land-atmosphere CO2 exchange. Changing from a Q 10 form for plant dark and maintanence respiration (as used in the coupled GCM runs) to a respiration proportional to maximum photosynthesis, reduces the biomass lost from Amazonia in the 21st century. Replacing the GCM control climate (which has about 25% too little rain in the annual mean over Amazonia) with an observed climatology increases the CO2 concentration at which rainfall drops to critical levels, and thereby further delays the dieback. On the other hand, calibration of the canopy photosynthesis model against Amazonian flux data tends to lead to earlier forest dieback. Further advances are required in both GCM rainfall simulation and land-surface process representation before a clearer picture will emerge on the timing of possible Amazonian forest dieback. However, it seems likely that these advances will overall lead to projections of later forest dieback as GCM control climates become more realistic.
KeywordsPhotosynthesis Land Surface Rainfall Simulation Canopy Photosynthesis Land Surface Parameterisation
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