Bayesian integration of flux tower data into a process-based simulator for quantifying uncertainty in simulated output
Parameters of a process-based forest growth simulator are difficult or impossible to obtain from field observations. Reliable estimates can be obtained using calibration against observations of output and state variables. In this study, we present a Bayesian framework to calibrate the widely used pr...
| Main Authors: | , , , |
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| Format: | Article |
| Published: |
European Geosciences Union
2018
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| Online Access: | https://eprints.nottingham.ac.uk/53022/ |