Constraining predictions of the carbon cycle using data

P. J. Rayner (1) , E. Koffi (1) , M. Scholze (2) , T. Kaminski (3) , J. -L. Dufresne (4)

1 CEA - Commissariat à l'énergie atomique et aux énergies alternatives
2 School of Earth Sciences [Bristol]
3 Fastopt GmbH, D-20357 Hamburg, Germany
4 LMD - Laboratoire de Météorologie Dynamique (UMR 8539)

We use a carbon-cycle data assimilation system to estimate the terrestrial biospheric CO(2) flux until 2090. The terrestrial sink increases rapidly and the increase is stronger in the presence of climate change. Using a linearized model, we calculate the uncertainty in the flux owing to uncertainty in model parameters. The uncertainty is large and is dominated by the impact of soil moisture on heterotrophic respiration. We show that this uncertainty can be greatly reduced by constraining the model parameters with two decades of atmospheric measurements.

Domaines: Océan, Atmosphère

P. J. Rayner, E. Koffi, M. Scholze, T. Kaminski, J. -L. Dufresne. Constraining predictions of the carbon cycle using data. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 2011, 369 (1943), pp.1955-1966. ⟨10.1098/rsta.2010.0378⟩. ⟨hal-01117352⟩