Attribution of the 2010-2017 trend in atmospheric methane by improved inverse analysis of GOSAT satellite observations
Abstract
We present a global inverse analysis of 2010-2017 GOSAT satellite observations using the GEOS-Chem chemical transport model. The inversion optimizes 2010-2017 anthropogenic methane emissions and their trends on a 4ox5o grid, regional wetland emissions on a monthly basis, and annual-mean hemispheric OH concentrations (the main sink of methane). It uses an analytical solution to the Bayesian optimization problem with closed-form characterization of the error statistics on the results. A number of improvements are introduced relative to previous inversions including (1) optimization of seasonal and inter-annual emissions from wetlands with spatial error covariance; (2) a new bottom-up emission inventory for oil/gas/coal based on national reports to the United Nations Framework Convention on Climate Change; (3) correction of stratospheric methane model bias using a parameterization based on ACE-FTS satellite data; (4) better optimization of OH concentrations and their inter-annual variability. Results show that the 2010-2017 trend of atmospheric methane can be attributed to a combination of wetlands, tropical livestock, Chinese emissions, and OH concentrations. The inversion points out large errors in the seasonality of wetland emissions from current bottom-up models.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2019
- Bibcode:
- 2019AGUFM.B33A..05Z
- Keywords:
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- 0428 Carbon cycling;
- BIOGEOSCIENCES;
- 1615 Biogeochemical cycles;
- processes;
- and modeling;
- GLOBAL CHANGE;
- 6309 Decision making under uncertainty;
- POLICY SCIENCES;
- 6620 Science policy;
- POLICY SCIENCES & PUBLIC ISSUES