Chapter Nineteen Model-Data Fusion in Studies of the Terrestrial Carbon Sink

G. A. Alexandrov, D. Chan, M. Chen, K. Gurney, K. Higuchi, A. Ito, C. D. Jones, A. Komarov, K. Mabuchi, D. M. Matross, F. Veroustraete, W. W. Verstraeten

Research output: Chapter in Book/Report/Conference proceedingChapter


Current uncertainty in quantifying the global carbon budget remains a major contributing source of uncertainty in reliably projecting future climate change. Furthermore, quantifying the global carbon budget and characterising uncertainties have emerged as critical to a successful implementation of the United Nations Framework Convention on Climate Change and its Kyoto Protocol. Beyond fundamental quantification, attribution of the processes responsible for the so-called 'residual terrestrial uptake' is important to the carbon cycle communities' ability to simulate the future response of the terrestrial biosphere to climate change and intentional sequestration activities. The objective of this chapter is to describe the approaches to model-data fusion enabling continued advances in quantifying carbon cycling and the terrestrial mechanisms at work. The major impediments to advances in this field include accounting for climate variability and uncertainties in model outcomes. One proposed solution to overcome these obstacles is the use of data from the FLUXNET network to characterise the relative strength of climate impact on plant productivity and respiration. Other solutions involve the use of atmospheric CO2 concentration measurements for model validation and the use of remote sensing data.

Original languageEnglish (US)
Title of host publicationEnvironmental Modelling, Software and Decision Support
Number of pages16
ISBN (Print)9780080568867
StatePublished - Jan 1 2008
Externally publishedYes

Publication series

NameDevelopments in Integrated Environmental Assessment
ISSN (Print)1574-101X


  • Kalman filtering
  • carbon cycle
  • model-data fusion
  • residual terrestrial uptake

ASJC Scopus subject areas

  • General Environmental Science


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