Beskrivning
Wetlands in the boreal zone are a significant source of atmospheric methane, and hence they have been intensively studied with mechanistic models for the assessment of methane dynamics. The arctic-enabled dynamic global vegetation model LPJ-GUESS is one of the models that allow quantification and understanding of the natural methane fluxes at various scales ranging from local to regional and global, but with several uncertainties. Complexity in the underlying environmental processes, warming driven alternative paths of meteorological phenomena and changes in hydrological and vegetation conditions are exigent for a calibrated and optimised LPJ-GUESS. In this PhD project, we use a Markov chain Monte Carlo (using Metropolis-Hastings formula) algorithm to optimise process parameters in the LPJ-GUESS using CH4 flux observations from boreal wetlands measured by the eddy-covariance technique.| Period | 2019 aug. 1 → … |
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| Examinerad/handledd person | Jalisha Theanutti |
| Examination/handledning vid | |
| Omfattning | Internationell |
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