Global distribution of methane emissions: a comparative inverse analysis of 2019 observations from the TROPOMI and GOSAT satellite instruments

Zhen Qu,  Harvard University,  zhenqu@g.harvard.edu (Presenter)
Daniel J. Jacob,  Harvard University,  djacob@fas.harvard.edu
Lu Shen,  Harvard University,  lshen@fas.harvard.edu
Xiao Lu,  Harvard University,  xiaolu@g.harvard.edu
Yuzhong Zhang,  Westlake University,  zhangyuzhong@westlake.edu.cn
Tia R. Scarpelli,  Harvard University,  tscarpelli@g.harvard.edu
Hannah O. Nesser,  Harvard University,  hnesser@g.harvard.edu
Melissa P. Sulprizio,  Harvard University,  mpayer@seas.harvard.edu
Joannes D. Maasakkers,  SRON,  j.d.maasakkers@sron.nl
A. Anthony Bloom,  JPL,  alexis.a.bloom@jpl.nasa.gov
John R. Worden,  JPL,  john.r.worden@jpl.nasa.gov
Robert J. Parker,  University of Leicester,  rjp23@leicester.ac.uk
Alba L. Delgado,  SRON,  a.lorente.delgado@sron.nl

The recent launch of TROPOMI offers unprecedent opportunity to more accurately quantify global methane sources from a top-down perspective. We evaluate the global atmospheric methane column retrievals from the new TROPOMI satellite instrument and apply them to a global inversion of methane sources for 2019 at 2°?2.5° horizontal resolution. We compare the results to an inversion using the sparser but more mature GOSAT satellite retrievals, as well as a joint inversion using both TROPOMI and GOSAT. Validation of TROPOMI and GOSAT with TCCON ground-based measurements of methane columns, after correcting for retrieval differences in prior vertical profiles and averaging kernels using the GEOS-Chem chemical transport model, shows global biases of -3 ppbv for TROPOMI and -1 ppbv for GOSAT, and regional biases of 7 ppbv for TROPOMI and 3 ppbv for GOSAT. Intercomparison of TROPOMI and GOSAT shows larger regional discrepancies exceeding 20 ppbv, mostly over regions with low surface albedo in the shortwave infrared. We use for the inversion an analytical solution to the Bayesian optimization of methane sources, thus providing an explicit characterization of error statistics and information content together with the solution. TROPOMI has ~100 times more observations than GOSAT but error correlation on the 2°?2.5° scale of the inversion makes it less useful than GOSAT for quantifying emissions at that resolution. Finer-scale regional inversions would take better advantage of the TROPOMI data density. The TROPOMI and GOSAT inversions show consistent downward adjustments of global oil/gas emissions relative to a prior estimate based on national inventory reports to the United Nations Framework Convention on Climate Change, but consistent increases in the south-central US and in Venezuela. We find large artifacts in the TROPOMI inversion over Southeast China, where seasonal rice emissions are particularly high, due to extensive cloudiness in seasonal phase with the emissions. Future improvements in the TROPOMI retrieval together with finer-scale inversions and improved accounting of error correlations should enable improved exploitation of TROPOMI observations to quantify and attribute methane emissions on the global scale.

Poster: Poster_Qu__10_25.pdf 

Presentation Type: Poster

Session: 3.2b Flux estimates and atmospheric inversions from space-based GHG measurements

Session Date: Wednesday (6/16) 9:45 AM