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Optimising an inverse modelling system for local peatland methane emissions

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Title: Optimising an inverse modelling system for local peatland methane emissions
Author(s): Corner, Joona
Contributor: University of Helsinki, Faculty of Science
Degree program: Master's Programme in Atmospheric Sciences
Specialisation: Meteorology
Language: English
Acceptance year: 2023
The aim of this work is to develop and optimise an atmospheric inverse modelling system to estimate local methane (CH4) emissions in peatlands. Peatlands are a major source of CH4 regionally in boreal areas and they have significance on a global scale as a soil carbon storage. Data assimilation in the inverse modelling system is based on an ensemble Kalman filter (EnKF) which is widely used in global and regional atmospheric inverse models. The EnKF in this study is an implementation of the EnKF used in the global atmospheric inversion model CarbonTracker Europe-CH4 (CTE-CH4) applied to local setting in the peatland. Consistency of the methodology with regional and global models means that it is possible to expand the system in scale. Siikaneva fen in Southern Finland is used as a testbed for the optimisation of the system. Prior natural CH4 fluxes in Siikaneva are acquired from the HelsinkI Model of MEthane buiLd-up and emIssion for peatland (HIMMELI) which simulates exchange of gases in peatlands. In addition to the peatland fluxes, anthropogenic fluxes at the site are estimated as well in the inversion. For the assimilation of atmospheric CH4 concentration observations, the CH4 fluxes are transformed into atmospheric concentration with a simple one-dimensional box model. The optimisation of the system was done by changing parameters in the model which affect the data assimilation. In model optimisation tests it was discovered that the performance of the modelling system is unstable. There was large variability in the produced estimates between consecutive model runs. Model evaluation statistics did not indicate improvement of the estimates after the inversion. No exact reason for the unstability was able to be determined. Posterior estimates of CH4 fluxes for years 2012–2015 did not differ much from prior estimates and they had large uncertainty. However, evaluation against flux measurements showed reasonable agreement and posterior concentration estimates were within the uncertainty range of the observed concentration.
Keyword(s): methane CH4 peatland atmospheric inverse modelling ensemble Kalman filter optimisation

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