Abstract
Calibration of terrestrial ecosystem models is important but challenging. Bayesian inference implemented by Markov chain Monte Carlo (MCMC) sampling provides a comprehensive framework to estimate model parameters and associated uncertainties using their posterior distributions. The effectiveness and efficiency of the method strongly depend on the MCMC algorithm used. In this work, a differential evolution adaptive Metropolis (DREAM) algorithm is used to estimate posterior distributions of 21 parameters for the data assimilation linked ecosystem carbon (DALEC) model using 14 years of daily net ecosystem exchange data collected at the Harvard Forest Environmental Measurement Site eddy-flux tower. The calibration of DREAM results in a better model fit and predictive performance compared to the popular adaptive Metropolis (AM) scheme. Moreover, DREAM indicates that two parameters controlling autumn phenology have multiple modes in their posterior distributions while AM only identifies one mode. The application suggests that DREAM is very suitable to calibrate complex terrestrial ecosystem models, where the uncertain parameter size is usually large and existence of local optima is always a concern. In addition, this effort justifies the assumptions of the error model used in Bayesian calibration according to the residual analysis. The result indicates that a heteroscedastic, correlated, Gaussian error model is appropriate for the problem, and the consequent constructed likelihood function can alleviate the underestimation of parameter uncertainty that is usually caused by using uncorrelated error models.
| Original language | English |
|---|---|
| Pages (from-to) | 4295-4314 |
| Number of pages | 20 |
| Journal | Biogeosciences |
| Volume | 14 |
| Issue number | 18 |
| DOIs | |
| State | Published - Sep 27 2017 |
Bibliographical note
Publisher Copyright:© 2017 Author(s).
Funding
Acknowledgements. This research was conducted by the Terrestrial Ecosystem Science – Science Focus Area (TES-SFA) project, supported by the Office of Biological and Environmental Research in the DOE Office of Science. The Harvard Forest flux tower is part of the AmeriFlux network supported by the Office of Biological and Environmental Research in the DOE Office of Science and is additionally supported by National Science Foundation as part of the Harvard Forest Long-Term Ecological Research site. The NACP site-synthesis activity supported assembling the data set. Oak Ridge National Laboratory is managed by UT-BATTELLE for DOE under contract DE-AC05-00OR22725. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the DOE’s National Nuclear Security Administration under contract DE-AC04-94-AL85000.
| Funders | Funder number |
|---|---|
| DOE Office of Science | |
| Harvard Forest Long-Term Ecological Research | |
| Office of Biological and Environmental Research | |
| Sandia Corporation | |
| Terrestrial Ecosystem Science | |
| National Science Foundation | 1237491 |
| Lockheed Martin Corporation | |
| Harvard Forest, Harvard University | |
| National Nuclear Security Administration | DE-AC04-94-AL85000 |
| Sandia National Laboratories |