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Abstract:
Methane emissions to the atmosphere from natural wetlands are estimated to be about 25 % of the total global CH4 emissions. In the Arctic, these areas are highly vulnerable to the effects of global warming due to atmospheric warming amplification, leading to soil hydrologic changes involving permafrost thaw, formation of deeper active layers, and rising topsoil temperatures. As a result, projected increase in the degradation of permafrost carbon will likely lead to higher CO2 and CH4 emissions from these areas. Here we evaluate year-round model-simulated CH4 emissions to the atmosphere (for 2014 and 2015) from a region of northeastern Siberia in the Russian Far East. Four CH4 transport pathways are modeled with a revisit-ed version of the process-based JSBACH-methane model: plant-mediated transport, ebullition and molecular diffusion in the presence or absence of snow. This model also simulates the extent of wetlands as the fraction of inundated area in a model grid cell using a TOP-MODEL approach, and these are evaluated against a highly resolved wetland product from remote sensing data. The model CH4 emissions are compared against ground-based CH4 flux measurements using the eddy covariance technique and flux chambers in the same area of study. The magnitude of the summertime modeled CH4 emissions is comparable to those from eddy covariance and flux chamber measurements. However, wintertime modeled CH4 emissions are underestimated by one order of magnitude. The annual CH4 emissions are dominated by plant-mediated transport (61 %), followed by ebullition (~ 35 %). Molecular diffusion of CH4 from the soil into the atmosphere during summer is negligible (0.02 %) compared to the diffusion through the snow during the non-growing season (~ 4 %). We investigate the relationship between temporal changes in the CH4 fluxes, soil temperature, and soil moisture content. Our results highlight the heterogeneity in CH4 emissions at a landscape scale and suggest that further improvements to the representation of large-scale hydrological conditions in the model, especially at regional scales in Arctic ecosystems influenced by permafrost thaw, will allow us to arrive at a more process-oriented land surface scheme and better simulate CH4 emissions under climate change.
