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Understanding methane emissions from the Arctic, a fast-warming carbonreservoir, is important for projecting future changes in the global methanecycle. Here we optimized methane emissions from north of 60° N(pan-Arctic) regions using a nested-grid high-resolution inverse model thatassimilates both high-precision surface measurements and column-averageSCanning Imaging Absorption spectroMeter for Atmospheric CHartogrphY (SCIAMACHY)satellite retrievals of methane mole fraction. For the first time,methane emissions from lakes were integrated into an atmospheric transportand inversion estimate, together with prior wetland emissions estimated withsix biogeochemical models. In our estimates, in 2005, global methaneemissions were in the range of 496.4–511.5 Tg yr−1, and pan-Arcticmethane emissions were in the range of 11.9–28.5 Tg yr−1. Methaneemissions from pan-Arctic wetlands and lakes were 5.5–14.2and 2.4–14.2 Tg yr−1, respectively. Methane emissions from Siberianwetlands and lakes are the largest and also have the largest uncertainty. Ourresults indicate that the uncertainty introduced by different wetland modelscould be much larger than the uncertainty of each inversion. We also showthat assimilating satellite retrievals can reduce the uncertainty of thenested-grid inversions. The significance of lake emissions cannot beidentified across the pan-Arctic by high-resolution inversions, but it ispossible to identify high lake emissions from some specific regions. Incontrast to global inversions, high-resolution nested-grid inversions performbetter in estimating near-surface methane concentrations

atmospheric chemistry and physics

Inverse modeling of pan-Arctic methane emissions at high spatial resolution: what can we learn from assimilating satellite retrievals and using different process-based wetland and lake biogeochemical models?