Model–data fusion across ecosystems: from multisite optimizations to global simulations
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 att...
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doaj-6adcd94a6bb04a9a90b1831f7621e80c2020-11-24T22:51:32ZengCopernicus PublicationsGeoscientific Model Development1991-959X1991-96032014-11-01762581259710.5194/gmd-7-2581-2014Model–data fusion across ecosystems: from multisite optimizations to global simulationsS. Kuppel0P. Peylin1F. Maignan2F. Chevallier3G. Kiely4L. Montagnani5A. Cescatti6Laboratoire des Sciences du Climat et de l'Environnement, UMR 8212 CEA-CNRS-UVSQ, 91191 Gif-sur-Yvette CEDEX, FranceLaboratoire des Sciences du Climat et de l'Environnement, UMR 8212 CEA-CNRS-UVSQ, 91191 Gif-sur-Yvette CEDEX, FranceLaboratoire des Sciences du Climat et de l'Environnement, UMR 8212 CEA-CNRS-UVSQ, 91191 Gif-sur-Yvette CEDEX, FranceLaboratoire des Sciences du Climat et de l'Environnement, UMR 8212 CEA-CNRS-UVSQ, 91191 Gif-sur-Yvette CEDEX, FranceCivil and Environmental Engineering Department, and Environmental Research Institute, University College Cork, Cork, IrelandForest Services, Autonomous Province of Bolzano, 39100 Bolzano, ItalyEuropean Commission, Joint Research Center, Institute for Environment and Sustainability, Ispra, ItalyThis 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 PFT-averaged model–data root-mean-square difference (RMSD) and the associated daily output uncertainty, the optimization improves the simulated CO<sub>2</sub> 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 (<i>R</i><sub>eco</sub>) rates indicates distinctively improved simulations of both gross fluxes. The multisite parameter sets are then tested against CO<sub>2</sub> concentrations measured at 53 locations around the globe, showing significant adjustments of the modelled seasonality of atmospheric CO<sub>2</sub> concentration, whose relevance seems PFT-dependent, along with an improved interannual variability. Lastly, a global-scale 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.http://www.geosci-model-dev.net/7/2581/2014/gmd-7-2581-2014.pdf |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
S. Kuppel P. Peylin F. Maignan F. Chevallier G. Kiely L. Montagnani A. Cescatti |
spellingShingle |
S. Kuppel P. Peylin F. Maignan F. Chevallier G. Kiely L. Montagnani A. Cescatti Model–data fusion across ecosystems: from multisite optimizations to global simulations Geoscientific Model Development |
author_facet |
S. Kuppel P. Peylin F. Maignan F. Chevallier G. Kiely L. Montagnani A. Cescatti |
author_sort |
S. Kuppel |
title |
Model–data fusion across ecosystems: from multisite optimizations to global simulations |
title_short |
Model–data fusion across ecosystems: from multisite optimizations to global simulations |
title_full |
Model–data fusion across ecosystems: from multisite optimizations to global simulations |
title_fullStr |
Model–data fusion across ecosystems: from multisite optimizations to global simulations |
title_full_unstemmed |
Model–data fusion across ecosystems: from multisite optimizations to global simulations |
title_sort |
model–data fusion across ecosystems: from multisite optimizations to global simulations |
publisher |
Copernicus Publications |
series |
Geoscientific Model Development |
issn |
1991-959X 1991-9603 |
publishDate |
2014-11-01 |
description |
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 PFT-averaged model–data root-mean-square
difference (RMSD) and the associated daily output uncertainty, the
optimization improves the simulated CO<sub>2</sub> 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
(<i>R</i><sub>eco</sub>) rates indicates distinctively improved simulations of both gross
fluxes. The multisite parameter sets are then tested against CO<sub>2</sub>
concentrations measured at 53 locations around the globe, showing significant
adjustments of the modelled seasonality of atmospheric CO<sub>2</sub>
concentration, whose relevance seems PFT-dependent, along with an improved
interannual variability. Lastly, a global-scale 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. |
url |
http://www.geosci-model-dev.net/7/2581/2014/gmd-7-2581-2014.pdf |
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