Journal article

A new stepwise carbon cycle data assimilation system using multiple data streams to constrain the simulated land surface carbon cycle

Philippe Peylin, Cedric Bacour, Natasha MacBean, Sebastien Leonard, Peter Rayner, Sylvain Kuppel, Ernest Koffi, Abdou Kane, Fabienne Maignan, Frederic Chevallier, Philippe Ciais, Pascal Prunet

Geoscientific Model Development | COPERNICUS GESELLSCHAFT MBH | Published : 2016


Large uncertainties in land surface models (LSMs) simulations still arise from inaccurate forcing, poor description of land surface heterogeneity (soil and vegetation properties), incorrect model parameter values and incomplete representation of biogeochemical processes. The recent increase in the number and type of carbon cycle-related observations, including both in situ and remote sensing measurements, has opened a new road to optimize model parameters via robust statistical model-data integration techniques, in order to reduce the uncertainties of simulated carbon fluxes and stocks. In this study we present a carbon cycle data assimilation system that assimilates three major data streams..

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University of Melbourne Researchers


Awarded by EU FP7 CARBONES project

Awarded by GEOCARBON project

Awarded by U.S. Department of Energy, Biological and Environmental Research, Terrestrial Carbon Program

Awarded by European Research Council

Funding Acknowledgements

This work was mainly funded by the EU FP7 CARBONES project (contracts FP7-SPACE-2009-1-242316), with also a small contribution from GEOCARBON project (ENV.2011.4.1.1-1-283080). This work used eddy covariance data acquired by the FLUXNET community and in particular by the following networks: AmeriFlux (U.S. Department of Energy, Biological and Environmental Research, Terrestrial Carbon Program; DE-FG02-04ER63917 and DE-FG02-04ER63911), AfriFlux, AsiaFlux, CarboAfrica, CarboEuropeIP, CarboItaly, CarboMont, ChinaFlux, Fluxnet-Canada (supported by CFCAS, NSERC, BIOCAP, Environment Canada, and NRCan), Green-Grass, KoFlux, LBA, NECC, OzFlux, TCOS-Siberia, USCCC. We acknowledge the financial support to the eddy covariance data harmonization provided by CarboEuropeIP, FAO-GTOS-TCO, iLEAPS, Max Planck Institute for Biogeochemistry, National Science Foundation, University of Tuscia, Universite Laval and Environment Canada and US Department of Energy and the database development and technical support from Berkeley Water Center, Lawrence Berkeley National Laboratory, Microsoft Research eScience, Oak Ridge National Laboratory, University of California-Berkeley, University of Virginia. Philippe Ciais acknowledges support from the European Research Council through Synergy grant ERC-2013-SyG-610028 "IMBALANCE-P". The authors wish to thank M. Jung for providing access to the GPP MTE data, which were downloaded from the GEOCARBON data portal ( The authors are also grateful to computing support and resources provided at LSCE and to the overall ORCHIDEE project that coordinate the development of the code (