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?
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Henze, Daven K.
Turner, Alexander J.
Understanding methane emissions from the Arctic, a fast-warming carbon
reservoir, is important for projecting future changes in the global methane
cycle. Here we optimized methane emissions from north of 60° N
(pan-Arctic) regions using a nested-grid high-resolution inverse model that
assimilates both high-precision surface measurements and column-average
SCanning 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 transport
and inversion estimate, together with prior wetland emissions estimated with
six biogeochemical models. In our estimates, in 2005, global methane
emissions were in the range of 496.4–511.5 Tg yr<sup>−1</sup>, and pan-Arctic
methane emissions were in the range of 11.9–28.5 Tg yr<sup>−1</sup>. Methane
emissions from pan-Arctic wetlands and lakes were 5.5–14.2
and 2.4–14.2 Tg yr<sup>−1</sup>, respectively. Methane emissions from Siberian
wetlands and lakes are the largest and also have the largest uncertainty. Our
results indicate that the uncertainty introduced by different wetland models
could be much larger than the uncertainty of each inversion. We also show
that assimilating satellite retrievals can reduce the uncertainty of the
nested-grid inversions. The significance of lake emissions cannot be
identified across the pan-Arctic by high-resolution inversions, but it is
possible to identify high lake emissions from some specific regions. In
contrast to global inversions, high-resolution nested-grid inversions perform
better in estimating near-surface methane concentrations.