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Assessing parameter variability in a photosynthesis model within and between plant functional types using global Fluxnet eddy covariance data

Groenendijk, M. ; Dolman, A. J. ; van der Molen, M. K. ; Leuning, R. ; Arneth, Almut LU ; Delpierre, N. ; Gash, J. H. C. ; Lindroth, Anders LU ; Richardson, A. D. and Verbeeck, H. , et al. (2011) In Agricultural and Forest Meteorology 151(1). p.22-38
Abstract
The vegetation component in climate models has advanced since the late 1960s from a uniform prescription of surface parameters to plant functional types (PFTs) PFTs are used in global land-surface models to provide parameter values for every model grid cell With a simple photosynthesis model we derive parameters for all site years within the Fluxnet eddy covariance data set We compare the model parameters within and between PFTs and statistically group the sites Fluxnet data is used to validate the photosynthesis model parameter variation within a PFT classification Our major result is that model parameters appear more variable than assumed in PFTs Simulated fluxes are of higher quality when model parameters of individual sites or site... (More)
The vegetation component in climate models has advanced since the late 1960s from a uniform prescription of surface parameters to plant functional types (PFTs) PFTs are used in global land-surface models to provide parameter values for every model grid cell With a simple photosynthesis model we derive parameters for all site years within the Fluxnet eddy covariance data set We compare the model parameters within and between PFTs and statistically group the sites Fluxnet data is used to validate the photosynthesis model parameter variation within a PFT classification Our major result is that model parameters appear more variable than assumed in PFTs Simulated fluxes are of higher quality when model parameters of individual sites or site years are used A simplification with less variation in model parameters results in poorer simulations This indicates that a PFT classification Introduces uncertainty in the variation of the photosynthesis and transpiration fluxes Statistically derived groups of sites with comparable model parameters do not share common vegetation types or climates A simple PFT classification does not reflect the real photosynthesis and transpiration variation Although site year parameters give the best predictions the parameters are generally too specific to be used in a global study The site year parameters can be further used to explore the possibilities of alternative classification schemes (C) 2010 Elsevier B V All rights reserved (Less)
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organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Eddy covariance, Transpiration, Photosynthesis, Plant functional types, Model parameters, Fluxnet
in
Agricultural and Forest Meteorology
volume
151
issue
1
pages
22 - 38
publisher
Elsevier
external identifiers
  • wos:000285325400003
  • scopus:78649320657
ISSN
1873-2240
DOI
10.1016/j.agrformet.2010.08.013
language
English
LU publication?
yes
id
01436247-e9fa-4187-af5c-4d59eec0aa7b (old id 1774098)
date added to LUP
2016-04-01 12:51:10
date last changed
2022-04-21 18:22:12
@article{01436247-e9fa-4187-af5c-4d59eec0aa7b,
  abstract     = {{The vegetation component in climate models has advanced since the late 1960s from a uniform prescription of surface parameters to plant functional types (PFTs) PFTs are used in global land-surface models to provide parameter values for every model grid cell With a simple photosynthesis model we derive parameters for all site years within the Fluxnet eddy covariance data set We compare the model parameters within and between PFTs and statistically group the sites Fluxnet data is used to validate the photosynthesis model parameter variation within a PFT classification Our major result is that model parameters appear more variable than assumed in PFTs Simulated fluxes are of higher quality when model parameters of individual sites or site years are used A simplification with less variation in model parameters results in poorer simulations This indicates that a PFT classification Introduces uncertainty in the variation of the photosynthesis and transpiration fluxes Statistically derived groups of sites with comparable model parameters do not share common vegetation types or climates A simple PFT classification does not reflect the real photosynthesis and transpiration variation Although site year parameters give the best predictions the parameters are generally too specific to be used in a global study The site year parameters can be further used to explore the possibilities of alternative classification schemes (C) 2010 Elsevier B V All rights reserved}},
  author       = {{Groenendijk, M. and Dolman, A. J. and van der Molen, M. K. and Leuning, R. and Arneth, Almut and Delpierre, N. and Gash, J. H. C. and Lindroth, Anders and Richardson, A. D. and Verbeeck, H. and Wohlfahrt, G.}},
  issn         = {{1873-2240}},
  keywords     = {{Eddy covariance; Transpiration; Photosynthesis; Plant functional types; Model parameters; Fluxnet}},
  language     = {{eng}},
  number       = {{1}},
  pages        = {{22--38}},
  publisher    = {{Elsevier}},
  series       = {{Agricultural and Forest Meteorology}},
  title        = {{Assessing parameter variability in a photosynthesis model within and between plant functional types using global Fluxnet eddy covariance data}},
  url          = {{http://dx.doi.org/10.1016/j.agrformet.2010.08.013}},
  doi          = {{10.1016/j.agrformet.2010.08.013}},
  volume       = {{151}},
  year         = {{2011}},
}