A33C-0172
Multi-year Estimates of Methane Fluxes in Alaska from an Atmospheric Inverse Model
Wednesday, 16 December 2015
Poster Hall (Moscone South)
Scot M Miller1, Roisin Commane2, Rachel Ying-Wen Chang3, Charles E Miller4, Anna M Michalak5, Steven J Dinardo4, Edward J Dlugokencky6, Sean Hartery3, Anna Karion7, Jakob Lindaas2, Colm Sweeney7 and Steven C Wofsy2, (1)Carnegie Institution for Science - Stanford, Department of Global Ecology, Stanford, CA, United States, (2)Harvard University, Cambridge, MA, United States, (3)Dalhousie University, Halifax, NS, Canada, (4)NASA Jet Propulsion Laboratory, Pasadena, CA, United States, (5)Carnegie Institution for Science Washington, Washington, DC, United States, (6)NOAA Boulder, Boulder, CO, United States, (7)NOAA Boulder, ESRL, Boulder, CO, United States
Abstract:
We estimate methane fluxes across Alaska over a multi-year period using observations from a three-year aircraft campaign, the Carbon Arctic Reservoirs Vulnerability Experiment (CARVE). Existing estimates of methane from Alaska and other Arctic regions disagree in both magnitude and distribution, and before the CARVE campaign, atmospheric observations in the region were sparse. We combine these observations with an atmospheric particle trajectory model and a geostatistical inversion to estimate surface fluxes at the model grid scale. We first use this framework to estimate the spatial distribution of methane fluxes across the state. We find the largest fluxes in the south-east and North Slope regions of Alaska. This distribution is consistent with several estimates of wetland extent but contrasts with the distribution in most existing flux models. These flux models concentrate methane in warmer or more southerly regions of Alaska compared to the estimate presented here. This result suggests a discrepancy in how existing bottom-up models translate wetland area into methane fluxes across the state. We next use the inversion framework to explore inter-annual variability in regional-scale methane fluxes for 2012-2014. We examine the extent to which this variability correlates with weather or other environmental conditions. These results indicate the possible sensitivity of wetland fluxes to near-term variability in climate.
