Optimising the CH4 simulations from the LPJ-GUESS model using Adaptive MCMC
Authors/Creators
- 1. Lund University
- 2. University of Helsinki
Description
CH4 simulations from the LPJ-GUESS, a process-based dynamic global vegetation model, was calibrated using the daily CH4 flux observations collected at Siikaneva wetlands ( Finland) from 2005 to 2014. Rao-Blackwellised modification of Adaptive Metropolis MCMC sampling algorithm was used to calibrate the model. The code, data used to input the model and the data used to optimise the model are uploaded.
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