Model-data fusion across ecosystems

From multisite optimizations to global simulations

Sylvain Kuppel*, P. Peylin, F. Maignan, F. Chevallier, G. Kiely, L. Montagnani, A. Cescatti

*Corresponding author for this work

Research output: Contribution to journalArticle

21 Citations (Scopus)
4 Downloads (Pure)

Abstract

This study uses a variational data assimilation framework to simultaneously constrain a global ecosystem model with eddy covariance measurements of daily net ecosystem exchange (NEE) and latent heat (LE) fluxes from a large number of sites grouped in seven plant functional types (PFTs). It is an attempt to bridge the gap between the numerous site-specific parameter optimization works found in the literature and the generic parameterization used by most land surface models within each PFT. The present multisite approach allows deriving PFT-generic sets of optimized parameters enhancing the agreement between measured and simulated fluxes at most of the sites considered, with performances often comparable to those of the corresponding site-specific optimizations. Besides reducing the PFTaveraged model-data root-mean-square difference (RMSD) and the associated daily output uncertainty, the optimization improves the simulated CO2 balance at tropical and temperate forests sites. The major site-level NEE adjustments at the seasonal scale are reduced amplitude in C3 grasslands and boreal forests, increased seasonality in temperate evergreen forests, and better model-data phasing in temperate deciduous broadleaf forests. Conversely, the poorer performances in tropical evergreen broadleaf forests points to deficiencies regarding the modelling of phenology and soil water stress for this PFT. An evaluation with data-oriented estimates of photosynthesis (GPP - gross primary productivity) and ecosystem respiration (Reco) rates indicates distinctively improved simulations of both gross fluxes. The multisite parameter sets are then tested against CO2 concentrations measured at 53 locations around the globe, showing significant adjustments of the modelled seasonality of atmospheric CO2 concentration, whose relevance seems PFT-dependent, along with an improved interannual variability. Lastly, a globalscale evaluation with remote sensing NDVI (normalized difference vegetation index) measurements indicates an improvement of the simulated seasonal variations of the foliar cover for all considered PFTs.

Original languageEnglish
Pages (from-to)2581-2597
Number of pages17
JournalGeoscientific Model Development
Volume7
Issue number6
DOIs
Publication statusPublished - 10 Nov 2014

Fingerprint

Data Fusion
Data fusion
Ecosystem
Ecosystems
Optimization
ecosystem
temperate forest
Seasonality
simulation
net ecosystem exchange
Simulation
Gross
Data Model
evergreen forest
Fluxes
Adjustment
tropical forest
seasonality
Photosynthesis
Latent heat

ASJC Scopus subject areas

  • Earth and Planetary Sciences(all)
  • Modelling and Simulation

Cite this

Kuppel, S., Peylin, P., Maignan, F., Chevallier, F., Kiely, G., Montagnani, L., & Cescatti, A. (2014). Model-data fusion across ecosystems: From multisite optimizations to global simulations. Geoscientific Model Development, 7(6), 2581-2597. https://doi.org/10.5194/gmd-7-2581-2014

Model-data fusion across ecosystems : From multisite optimizations to global simulations. / Kuppel, Sylvain; Peylin, P.; Maignan, F.; Chevallier, F.; Kiely, G.; Montagnani, L.; Cescatti, A.

In: Geoscientific Model Development, Vol. 7, No. 6, 10.11.2014, p. 2581-2597.

Research output: Contribution to journalArticle

Kuppel, S, Peylin, P, Maignan, F, Chevallier, F, Kiely, G, Montagnani, L & Cescatti, A 2014, 'Model-data fusion across ecosystems: From multisite optimizations to global simulations', Geoscientific Model Development, vol. 7, no. 6, pp. 2581-2597. https://doi.org/10.5194/gmd-7-2581-2014
Kuppel, Sylvain ; Peylin, P. ; Maignan, F. ; Chevallier, F. ; Kiely, G. ; Montagnani, L. ; Cescatti, A. / Model-data fusion across ecosystems : From multisite optimizations to global simulations. In: Geoscientific Model Development. 2014 ; Vol. 7, No. 6. pp. 2581-2597.
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