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Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
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© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Development and technical paper 07 Feb 2019

Development and technical paper | 07 Feb 2019

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Geoscientific Model Development (GMD).

Identification of key parameters controlling demographicallystructured vegetation dynamics in a Land Surface Model [CLM4.5(ED)]

Elias C. Massoud1,2, Chonggang Xu3, Rosie Fisher4, Ryan Knox5, Anthony Walker6, Shawn Serbin7, Bradley Christoffersen8, Jennifer Holm5, Lara Kueppers5, Daniel M. Ricciuto6, Liang Wei3, Daniel Johnson3, Jeff Chambers5, Charlie Koven5, Nate McDowell9, and Jasper Vrugt2,10 Elias C. Massoud et al.
  • 1Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
  • 2Department of Civil and Environmental Engineering, University of California Irvine, Irvine, CA, USA
  • 3Earth and Environmental Sciences Division, Los Alamos National Laboratory, Los Alamos, NM, USA
  • 4Terrestrial Sciences Section, National Center for Atmospheric Research, Boulder, CO, USA
  • 5Climate and Ecosystems Devision, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
  • 6Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA
  • 7Environmental & Climate Sciences Department, Brokenhaven National Laboratory, Upton, NY, USA
  • 8Department of Biology, University of Texas Rio Grande Valley, Edinburg, TX, USA
  • 9Pacific Northwest National Laboratory, Richland, WA, USA
  • 10Department of Earth System Science, University of California Irvine, Irvine, CA, USA

Abstract. Vegetation plays a key role in regulating global carbon cycles and is a key component of the Earth System Models (ESMs) aimed to project Earth's future climates. In the last decade, the vegetation component within ESMs has witnessed great progresses from simple 'big-leaf' approaches to demographically-structured approaches, which has a better representation of plant size, canopy structure, and disturbances. The demographically-structured vegetation models are typically controlled by a large number of parameters, and sensitivity analysis is generally needed to quantify the impact of each parameter on the model outputs for a better understanding of model behaviors. In this study, we use the Fourier Amplitude Sensitivity Test (FAST) to diagnose the Community Land Model coupled to the Ecosystem Demography Model, or CLM4.5(ED). We investigate the first and second order sensitivities of the model parameters to outputs that represent simulated growth and mortality as well as carbon fluxes and stocks. While the photosynthetic capacity parameter Vc,max25 is found to be important for simulated carbon stocks and fluxes, we also show the importance of carbon storage and allometry parameters, which are shown here to determine vegetation demography and carbon stocks through their impacts on survival and growth strategies. The results of this study highlights the importance of understanding the dynamics of the next generation of demographically-enabled vegetation models within ESMs toward improved model parameterization and model structure for better model fidelity.

Elias C. Massoud et al.
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Status: final response (author comments only)
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Elias C. Massoud et al.
Elias C. Massoud et al.
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Publications Copernicus
Short summary
We conducted a comprehensive sensitivity analysis to understand behaviors of a demographic vegetation model within a land surface model. By running the model for 5000 times with changing input parameter values, we found that 1) the photosynthetic capacity controls carbon fluxes, 2) the allometry is important for tree growth, and 3) the targeted carbon storage is important for tree survival. These results can provide guidance on improved model parameterization for a better fit to observations.
We conducted a comprehensive sensitivity analysis to understand behaviors of a demographic...