Articles | Volume 14, issue 18
https://doi.org/10.5194/bg-14-4295-2017
https://doi.org/10.5194/bg-14-4295-2017
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, Daniel Ricciuto, Anthony Walker, Cosmin Safta, and William Munger

Related authors

A model-independent data assimilation (MIDA) module and its applications in ecology
Xin Huang, Dan Lu, Daniel M. Ricciuto, Paul J. Hanson, Andrew D. Richardson, Xuehe Lu, Ensheng Weng, Sheng Nie, Lifen Jiang, Enqing Hou, Igor F. Steinmacher, and Yiqi Luo
Geosci. Model Dev., 14, 5217–5238, https://doi.org/10.5194/gmd-14-5217-2021,https://doi.org/10.5194/gmd-14-5217-2021, 2021
Short summary
Efficient surrogate modeling methods for large-scale Earth system models based on machine-learning techniques
Dan Lu and Daniel Ricciuto
Geosci. Model Dev., 12, 1791–1807, https://doi.org/10.5194/gmd-12-1791-2019,https://doi.org/10.5194/gmd-12-1791-2019, 2019
Short summary
LIVVkit 2.1: automated and extensible ice sheet model validation
Katherine J. Evans, Joseph H. Kennedy, Dan Lu, Mary M. Forrester, Stephen Price, Jeremy Fyke, Andrew R. Bennett, Matthew J. Hoffman, Irina Tezaur, Charles S. Zender, and Miren Vizcaíno
Geosci. Model Dev., 12, 1067–1086, https://doi.org/10.5194/gmd-12-1067-2019,https://doi.org/10.5194/gmd-12-1067-2019, 2019
Short summary
The multi-assumption architecture and testbed (MAAT v1.0): R code for generating ensembles with dynamic model structure and analysis of epistemic uncertainty from multiple sources
Anthony P. Walker, Ming Ye, Dan Lu, Martin G. De Kauwe, Lianhong Gu, Belinda E. Medlyn, Alistair Rogers, and Shawn P. Serbin
Geosci. Model Dev., 11, 3159–3185, https://doi.org/10.5194/gmd-11-3159-2018,https://doi.org/10.5194/gmd-11-3159-2018, 2018
Short summary

Related subject area

Biogeochemistry: Modelling, Terrestrial
Modelled forest ecosystem carbon–nitrogen dynamics with integrated mycorrhizal processes under elevated CO2
Melanie A. Thurner, Silvia Caldararu, Jan Engel, Anja Rammig, and Sönke Zaehle
Biogeosciences, 21, 1391–1410, https://doi.org/10.5194/bg-21-1391-2024,https://doi.org/10.5194/bg-21-1391-2024, 2024
Short summary
A chemical kinetics theory for interpreting the non-monotonic temperature dependence of enzymatic reactions
Jinyun Tang and William J. Riley
Biogeosciences, 21, 1061–1070, https://doi.org/10.5194/bg-21-1061-2024,https://doi.org/10.5194/bg-21-1061-2024, 2024
Short summary
Using Free Air CO2 Enrichment data to constrain land surface model projections of the terrestrial carbon cycle
Nina Raoult, Louis-Axel Edouard-Rambaut, Nicolas Vuichard, Vladislav Bastrikov, Anne Sofie Lansø, Bertrand Guenet, and Philippe Peylin
Biogeosciences, 21, 1017–1036, https://doi.org/10.5194/bg-21-1017-2024,https://doi.org/10.5194/bg-21-1017-2024, 2024
Short summary
Multiscale assessment of North American terrestrial carbon balance
Kelsey T. Foster, Wu Sun, Yoichi P. Shiga, Jiafu Mao, and Anna M. Michalak
Biogeosciences, 21, 869–891, https://doi.org/10.5194/bg-21-869-2024,https://doi.org/10.5194/bg-21-869-2024, 2024
Short summary
Simulating net ecosystem exchange under seasonal snow cover at an Arctic tundra site
Victoria R. Dutch, Nick Rutter, Leanne Wake, Oliver Sonnentag, Gabriel Hould Gosselin, Melody Sandells, Chris Derksen, Branden Walker, Gesa Meyer, Richard Essery, Richard Kelly, Phillip Marsh, Julia Boike, and Matteo Detto
Biogeosciences, 21, 825–841, https://doi.org/10.5194/bg-21-825-2024,https://doi.org/10.5194/bg-21-825-2024, 2024
Short summary

Cited articles

Barr, A., Hollinger, D., and Richardson, A. D.: CO2 flux measurement uncertainty estimates for NACP, AGU Fall Meeting, December 2009, abstract number B54A-04B, 2009.
Box, E. P. and Tiao, G. C.: Bayesian inference in statistical analysis, Wiley, New York, 588 pp., 1992.
Braswell, B. H., William, J. S., Linder, E., and Scheimel, D. S.: Estimating diurnal to annual ecosystem parameters by synthesis of a carbon flux model with eddy covariance net ecosystem exchange observations, Glob. Change Biol., 11, 335–355, 2005.
Brooks, S. P. and Gelman, A.: General methods for monitoring convergence of iterative simulations, J. Comput. Graph. Stat., 7, 434–455, 1998.
Download
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.
Altmetrics
Final-revised paper
Preprint