Optimising CH4 simulations from the LPJ-GUESS model v4.1 using an adaptive Markov chain Monte Carlo algorithm

• Published in: Geoscientific Model Development
• Main Authors: Kallingal, Jalisha T., Lindström, Johan, Miller, Paul A., Rinne, Janne, Raivonen, Maarit, Scholze, Marko
• Format: Article in Journal/Newspaper
• Language: English
• Published: Copernicus GmbH 2024
• Subjects: Probability Theory and Statistics; Arctic; Hastings
• Online Access: https://lup.lub.lu.se/record/4f607883-1ee9-4e25-ad6d-59d66768ff31; https://doi.org/10.5194/gmd-17-2299-2024

The processes responsible for methane (CH4) emissions from boreal wetlands are complex; hence, their model representation is complicated by a large number of parameters and parameter uncertainties. The arctic-enabled dynamic global vegetation model LPJ-GUESS (Lund-Potsdam-Jena General Ecosystem Simu...