Articles | Volume 14, issue 18
https://doi.org/10.5194/bg-14-4295-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/bg-14-4295-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
27 Sep 2017
Research article |
| 27 Sep 2017
Bayesian calibration of terrestrial ecosystem models: a study of advanced Markov chain Monte Carlo methods
Dan Lu
CORRESPONDING AUTHOR
Computational Sciences and Engineering Division, Climate Change
Science Institute, Oak Ridge National Laboratory, Oak Ridge, TN, USA
Daniel Ricciuto
Environmental Sciences Division, Climate Change Science Institute, Oak
Ridge National Laboratory, Oak Ridge, TN, USA
Anthony Walker
Environmental Sciences Division, Climate Change Science Institute, Oak
Ridge National Laboratory, Oak Ridge, TN, USA
Cosmin Safta
Sandia National Laboratories, Livermore, CA, USA
William Munger
School of Engineering and Applied Sciences, Harvard University,
Cambridge, MA, USA
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- A Bayesian inversion framework to evaluate parameter and predictive inference of a simple soil respiration model in a cool-temperate forest in western Japan M. Toda et al. 10.1016/j.ecolmodel.2019.108918
- An improved estimate of soil carbon pool and carbon fluxes in the Qinghai-Tibetan grasslands using data assimilation with an ecosystem biogeochemical model R. Zhao et al. 10.1016/j.geoderma.2022.116283
- An Integrative Model for Soil Biogeochemistry and Methane Processes: I. Model Structure and Sensitivity Analysis D. Ricciuto et al. 10.1029/2019JG005468
- A deep learning-based direct forecasting of CO2 plume migration M. Fan et al. 10.1016/j.geoen.2022.211363
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- Calibrating the soil organic carbon model Yasso20 with multiple datasets T. Viskari et al. 10.5194/gmd-15-1735-2022
- Biophysically Informed Imaging Acquisition of Plant Water Status D. Beverly et al. 10.3389/ffgc.2020.589493
- Improving probabilistic hydroclimatic projections through high-resolution convection-permitting climate modeling and Markov chain Monte Carlo simulations S. Wang & Y. Wang 10.1007/s00382-019-04702-7
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- Combining Eddy Covariance Towers, Field Measurements, and the MEMS 2 Ecosystem Model Improves Confidence in the Climate Impacts of Bioenergy With Carbon Capture and Storage G. Falvo et al. 10.1111/gcbb.70023
- Hyperspectral surface reflectance improves GPP estimation in terrestrial biosphere modeling using model-data fusion H. Liu et al. 10.1016/j.rse.2025.114989
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Latest update: 09 Oct 2025
Short summary
Calibration of terrestrial ecosystem models (TEMs) is important but challenging. This study applies an advanced sampling technique for parameter estimation of a TEM. The results improve the model fit and predictive performance.
Calibration of terrestrial ecosystem models (TEMs) is important but challenging. This study...
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