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Constraining predictions of the carbon cycle using data

  • Institut Pierre Simon Laplace, CNRS and CEA
  • University of Bristol
  • FastOpt GmbH

Research output: Contribution to journalArticlepeer-review

Abstract

We use a carbon-cycle data assimilation system to estimate the terrestrial biospheric CO2 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.

Original languageEnglish
Pages (from-to)1955-1966
Number of pages12
JournalPhilosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences
Volume369
Issue number1943
DOIs
Publication statusPublished - 28 May 2011

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 13 - Climate Action
    SDG 13 Climate Action

Keywords

  • Carbon cycle
  • Data assimilation
  • Terrestrial uptake

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