Identification of key parameters controlling demographically structured vegetation dynamics in a Land Surface Model
- JPL
- Los Alamos National Lab
- National Ctr for Atmospheric Res
- Lawrence Berkeley National Lab
- Oak Ridge National Lab
- Brookhaven National Lab
- LBNL
- Pacific Northwest National Lab
- Department of Civil and Environmental Engineering, University of California Irvine
This dataset includes outputs of 5000 simulations of CLM4.5(ED) to quantify the sensitivity of the model outputs to changes in model parameters using the Fourier Amplitude Sensitivity Test (FAST). Each simulation is generated by simultaneously sampling from 15% deviations of the default values of >80 vegetation parameters. This dataset includes 1) model codes of CLM4.5(ED) used for the sensitivity analysis; 2) the parameter samples; and 3) the corresponding model outputs of vegetation status (e.g., Gross Primary Production, Leaf Area Index and Biomass) and demography (e.g., diameter growth and mortality rates). The outputs are organized to the format of the FAST toolbox (https://sites.google.com/site/xuchongang/uasatoolbox).
- Research Organization:
- Next-Generation Ecosystem Experiments Tropics; Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
- Sponsoring Organization:
- NGEE tropics
- OSTI ID:
- 1497413
- Report Number(s):
- NGT0091
- Resource Relation:
- Related Information: Massoud, E. C., Xu, C., Fisher, R., Knox, R., Walker, A., Serbin, S., Christoffersen, B., Holm, J., Kueppers, L., Ricciuto, D. M., Wei, L., Johnson, D., Chambers, J., Koven, C., McDowell, N., and Vrugt, J.: Identification of key parameters controlling demographically structured vegetation dynamics in a Land Surface Model [CLM4.5(ED)], Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2019-6, in review, 2019.
- Country of Publication:
- United States
- Language:
- English
Identification of key parameters controlling demographically structured vegetation dynamics in a Land Surface Model
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dataset | January 2019 |
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