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Carbon cycle, vegetation, and climate dynamics in the Holocene: Experiments with the CLIMBER-2 model

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Brovkin, V., Bendtsen, J., Claussen, M., Ganopolski, A., Kubatzki, C., Petoukhov, V., et al. (2002). Carbon cycle, vegetation, and climate dynamics in the Holocene: Experiments with the CLIMBER-2 model. Global Biogeochemical Cycles, 16(4). doi:10.1029/2001GB001662.

Cite as: https://hdl.handle.net/11858/00-001M-0000-0013-A874-1
Multiple proxy data reveal that the early to middle Holocene (ca. 8-6 kyr B. P.) was warmer than the preindustrial period in most regions of the Northern Hemisphere. This warming is presumably explained by the higher summer insolation in the Northern Hemisphere, owing to changes in the orbital parameters. Subsequent cooling in the late Holocene was accompanied by significant changes in vegetation cover and an increase in atmospheric CO2 concentration. The essential question is whether it is possible to explain these changes in a consistent way, accounting for the orbital parameters as the main external forcing for the climate system. We investigate this problem using the computationally efficient model of climate system, CLIMBER-2, which includes models for oceanic and terrestrial biogeochemistry. We found that changes in climate and vegetation cover in the northern subtropical and circumpolar regions can be attributed to the changes in the orbital forcing. Explanation of the atmospheric CO2 record requires an additional assumption of excessive CaCO3 sedimentation in the ocean. The modeled decrease in the carbonate ion concentration in the deep ocean is similar to that inferred from CaCO3 sediment data [Broecker et al., 1999]. For 8 kyr B. P., the model estimates the terrestrial carbon pool ca. 90 Pg higher than its preindustrial value. Simulated atmospheric delta(13)C declines during the course of the Holocene, similar to delta(13)C data from the Taylor Dome ice core [Indermuhle et al., 1999]. Amplitude of simulated changes in delta(13)C is smaller than in the data, while a difference between the model and the data is comparable with the range of data uncertainty.