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Optimising the CH4 simulations from the LPJ-GUESS model using Adaptive MCMC

Authors :
Theanutti Kallingal Jalisha
Scholze Marko
A. Miller Paul
Lindstrom Johan
Rinne Janne
Raivonen Maarit
Publication Year :
2022
Publisher :
Zenodo, 2022.

Abstract

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 ofAdaptive 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.

Details

Language :
English
Database :
OpenAIRE
Accession number :
edsair.doi.dedup.....4bf542b47ba7a18c472447440d2721fd
Full Text :
https://doi.org/10.5281/zenodo.7339240