A top-down evaluation of bottom-up estimates to reduce uncertainty in methane emissions from Arctic wetlands

Abstract. Wetlands are a major natural source of atmospheric CH₄, however, accurately estimating their emissions is difficult due to the complex biogeochemical interactions and spatial heterogeneity of wetland environments. This study explores how a combination of atmospheric inverse and process-based modelling can reduce the discrepancy in Arctic wetland estimates between bottom-up and top-down approaches. We employed the Jena CarboScope global inversion system, incorporating prior wetland fluxes simulated by the JSBACH land surface model, which is part of the Max Planck Institute Earth System Model (MPI-ESM). We conducted a series of inversion experiments, each incorporating JSBACH-generated CH₄ fluxes based on different CH₄ production Q₁₀ values to test the temperature sensitivity of emissions. Additionally, we examined the impact of changing the baseline f_CH4 fraction value, which defines the fraction of anaerobically mineralized carbon converted to CH₄, while keeping all other JSBACH and inversion settings constant. Our findings show that, at a pan-Arctic scale, using a CH₄ Q₁₀ value of 1.8 produces the best agreement between the two approaches. However, no single Q₁₀ value yielded optimal agreement between the simulated fluxes and the fluxes inferred from atmospheric observations across all subregions. Instead, the best performance varied spatially, with different CH₄ production Q₁₀ values and baseline f_CH4 fraction leading to a better flux agreement in specific areas. These results highlight the importance of using regionally specific parameters to more accurately estimate wetland CH₄ emissions, and the potential of employing atmospheric inversions to guide bottom-up process models towards regionally representative parameter settings.