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@ARTICLE{Post:829874,
      author       = {Post, Hanna and Vrugt, Jasper A. and Fox, Andrew and
                      Vereecken, Harry and Hendricks Franssen, Harrie-Jan},
      title        = {{E}stimation of {C}ommunity {L}and {M}odel parameters for
                      an improved assessment of net carbon fluxes at {E}uropean
                      sites},
      journal      = {Journal of geophysical research / Biogeosciences},
      volume       = {122},
      number       = {3},
      issn         = {2169-8953},
      address      = {[Washington, DC]},
      reportid     = {FZJ-2017-03490},
      pages        = {661 - 689},
      year         = {2017},
      abstract     = {The Community Land Model (CLM) contains many parameters
                      whose values are uncertain and thus require careful
                      estimation for model application at individual sites. Here
                      we used Bayesian inference with the DiffeRential Evolution
                      Adaptive Metropolis (DREAM(zs)) algorithm to estimate eight
                      CLM v.4.5 ecosystem parameters using 1 year records of
                      half-hourly net ecosystem CO2 exchange (NEE) observations of
                      four central European sites with different plant functional
                      types (PFTs). The posterior CLM parameter distributions of
                      each site were estimated per individual season and on a
                      yearly basis. These estimates were then evaluated using NEE
                      data from an independent evaluation period and data from
                      “nearby” FLUXNET sites at ~600 km distance to the
                      original sites. Latent variables (multipliers) were used to
                      treat explicitly uncertainty in the initial carbon-nitrogen
                      pools. The posterior parameter estimates were superior to
                      their default values in their ability to track and explain
                      the measured NEE data of each site. The seasonal parameter
                      values reduced with more than $50\%$ (averaged over all
                      sites) the bias in the simulated NEE values. The most
                      consistent performance of CLM during the evaluation period
                      was found for the posterior parameter values of the forest
                      PFTs, and contrary to the C3-grass and C3-crop sites, the
                      latent variables of the initial pools further enhanced the
                      quality-of-fit. The carbon sink function of the forest PFTs
                      significantly increased with the posterior parameter
                      estimates. We thus conclude that land surface model
                      predictions of carbon stocks and fluxes require careful
                      consideration of uncertain ecological parameters and initial
                      states.},
      cin          = {IBG-3 / JARA-HPC},
      ddc          = {550},
      cid          = {I:(DE-Juel1)IBG-3-20101118 / $I:(DE-82)080012_20140620$},
      pnm          = {255 - Terrestrial Systems: From Observation to Prediction
                      (POF3-255) / Better predictions with environmental
                      simulation models: optimally integrating new data sources
                      $(jicg41_20100501)$},
      pid          = {G:(DE-HGF)POF3-255 / $G:(DE-Juel1)jicg41_20100501$},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:000398923300014},
      doi          = {10.1002/2015JG003297},
      url          = {https://juser.fz-juelich.de/record/829874},
}