We investigated the role of biomass burning in simulating the seasonal signal in both prognostic and diagnostic analyses. The prognostic anaysis involved the High-Resolution Biosphere Model, a prognostic terrestrial biosphere model, and the coupled vegetation fire module, which together produce a prognostic data set of biomass burning. The diagnostic analysis invovled the Simple Diagnostic Biosphere Model (SDBM) and the Hao and Liu  diagnostic data set of bimass burning, which have been scaled to global 2 and 4 Pg C yr-1, respectively. The monthly carbon exchange fields between the atmosphere and the biosphere with a spatial resolution of 0.5?? ?? 0.5??, the seasonal atmosphere-ocean exchange fields, and the emissions from fossil fuels have been coupled to the three-dimensional atmospheric transport model TM2. We have chosen eight monitoring stations of the National Oceanic and Atmospheric Administration network to compare the predicted seasonal atmospheric CO2 signals with those deduced from atmosphere-biosphere carbon exchange fluxes without any contribution from biomass burning. The prognostic analysis and the diagnostic analysis with global burning emissions of 4 Pg C yr-1 agree with respect to the change in the amplitude of the seasonal CO2 concentration introduced through biomass burning. We find that the seasonal CO2 signal at stations in higher northern latitudes (north of 30??N) is marginally influenced by biomass burning. For stations in tropical regions an increase in the CO2 amplitude of more an 1 oppmv (up to 50% with respect to the observed trough to peak amplitude) has been calculated. Biomass burning at stations farther south accounts for an increase in the CO2 amplitude of up to 59% (0.6 ppmv). A change in the phase of the seasonal CO2 signal at tropical and southern stations has been shown to be strongly influenced by the onset of biomass burning in southern tropical Africa and America. Comparing simulated and observed seasonal CO2 signals, we find higher discrepancies at southern troical stations if biomass burning emissions are included. This is caused by the additional increase in the amplitude in the prognostic analysis and a phase shift in a diagnostic analysis. In contrast, at the northern tropical stations biomass burning tends to improve the estimates of the seasonal CO2 signal in the prognostic analysis because of strengthening of the amplitude. Since the SDCM predicts the seasonal CO2 signal resonably well for the northern hemisphere tropical stations, no general improvement of the fit occurs if biomass burning emissions are considered.
Additional publication details
On the influence of biomass burning on the seasonal CO2 signal as observed at monitoring stations