labs_title

Evaluation of wetland methane emissions across North America using atmospheric data and inverse modeling

S.M. Miller, R. Commane, J.R. Melton, A.E. Andrews, J. Benmergui, E.J. Dlugokencky, G. Janssens-Maenhout, A.M. Michalak, C. Sweeney and D.E. J. Worthy

Methane is a potent greenhouse gas, and wetlands are one of the largest methane sources worldwide. Existing knowledge of methane emissions at national and continental scales is highly uncertain. Existing estimates disagree both on the location of these emissions and on their magnitude. This paper explores wetland methane emissions from two perspectives. First, we examine whether methane observations collected in the atmosphere across North America can be used to evaluate wetland methane emissions at the earth's surface. This task is non-trivial; numerous human activities also lead to methane emissions (e.g., agriculture, natural gas), and methane from these different emissions sources mix together in the atmosphere. Second, we evaluate several wetland methane emissions estimates that were generated from process-based models. Our comparison using atmospheric observations suggests that these estimate are too high and disproportionately place emissions in regions with many lakes.


Figure: This figure compares observed methane concentrations (in black) against methane concentrations modeled using a number of process-based methane flux estimates. The model result (in blue) can be compared directly against the observations (in black).

Abstract

Existing estimates of methane (CH4) fluxes from North American wetlands vary widely in both magnitude and distribution. In light of these differences, this study uses atmospheric CH4 observations from the US and Canada to analyze seven different bottom-up, wetland CH4 estimates reported in a recent model comparison project. We first use synthetic data to explore whether wetland CH4 fluxes are detectable at atmospheric observation sites. We find that the observation network can detect aggregate wetland fluxes from both eastern and western Canada but generally not from the US. Based upon these results, we then use real data and inverse modeling results to analyze the magnitude, seasonality, and spatial distribution of each model estimate. The magnitude of Canadian fluxes in many models is larger than indicated by atmospheric observations. Many models predict a seasonality that is narrower than implied by inverse modeling results, possibly indicating an oversensitivity to air or soil temperatures. The LPJ-Bern and SDGVM models have a geographic distribution that is most consistent with atmospheric observations, depending upon the region and season. These models utilize land cover maps or dynamic modeling to estimate wetland coverage while most other models rely primarily on remote sensing inundation data.

Miller, S.M., R. Commane, J.R. Melton, A.E. Andrews, J. Benmergui, E.J. Dlugokencky, G. Janssens-Maenhout, A.M. Michalak, , C. Sweeney, D.E.J. Worthy (2016) "Evaluation of wetland methane emissions across North America using atmospheric data and inverse modeling", Biogeosciences, 13 (4), 1329-1339, doi:10.5194/bg-13-1329-2016.