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

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Latest update: 20 Nov 2024
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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.
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