title: Constraining predictions of the carbon cycle using data.
abstract: 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.
authors.affiliation: Bat. 701 Cea/Saclay, Orme des Merisiers, Gif sur Yvette 91191, France. prayner@unimelb.edu.au
authors.forename: P J
authors.initials: PJ
authors.lastname: Rayner
authors.forename: E
authors.initials: E
authors.lastname: Koffi
authors.forename: M
authors.initials: M
authors.lastname: Scholze
authors.forename: T
authors.initials: T
authors.lastname: Kaminski
authors.forename: J-L
authors.initials: JL
authors.lastname: Dufresne
mesh_terms: D057486:Carbon Cycle; D002245:Carbon Dioxide / Q000378:metabolism; D057231:Climate Change; D003627:Data Interpretation, Statistical; D017753:Ecosystem; D005544:Forecasting; D049674:History, 21st Century; D016014:Linear Models; D008954:Models, Biological
chemical_list: D002245:Carbon Dioxide