Comment on acp-2021-309

Abstract

Abstract. 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 and to 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 −2.7 ppbv for TROPOMI and −1.0 ppbv for GOSAT and regional biases of 6.7 ppbv for TROPOMI and 2.9 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 where the TROPOMI retrieval may be biased. Our inversion uses an analytical solution to the Bayesian inference 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 and large spatial inhomogeneity in the number of observations make it less useful than GOSAT for quantifying emissions at that scale. 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. Global emissions from livestock (the largest anthropogenic source) are adjusted upward by TROPOMI and GOSAT relative to the EDGAR v4.3.2 prior estimate. We find large artifacts in the TROPOMI inversion over southeast China, where seasonal rice emissions are particularly high but in phase with extensive cloudiness and where coal emissions may be misallocated. Future advances 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.

Authors 12

1. Zhen Qu

   Harvard University

   Affiliation as printed

   School of Engineering and Applied Science, Harvard University, Cambridge, MA, USA

2. Daniel J. Jacob

   Harvard University

   Affiliation as printed

   School of Engineering and Applied Science, Harvard University, Cambridge, MA, USA

3. Lu Shen

   Harvard University

   Affiliation as printed

   School of Engineering and Applied Science, Harvard University, Cambridge, MA, USA

4. Xiao Hui Lu

   Harvard University

   Affiliation as printed

   School of Engineering and Applied Science, Harvard University, Cambridge, MA, USA

5. Yuzhong Zhang

   Westlake University

   Affiliation as printed

   Institute of Advanced Technology, Westlake Institute for Advanced Study, Hangzhou, Zhejiang, China

   Key Laboratory of Coastal Environment and Resources of Zhejiang Province (KLaCER), School of Engineering, Westlake University, Hangzhou, Zhejiang, China

6. Tia R. Scarpelli

   Harvard University

   Affiliation as printed

   School of Engineering and Applied Science, Harvard University, Cambridge, MA, USA

7. Hannah O. Nesser

   Harvard University

   Affiliation as printed

   School of Engineering and Applied Science, Harvard University, Cambridge, MA, USA

8. Melissa Payer Sulprizio

   Harvard University

   Affiliation as printed

   School of Engineering and Applied Science, Harvard University, Cambridge, MA, USA

9. Joannes D. Maasakkers Aachen SRON Netherlands Institute for Space Research

   Space Research Organisation Netherlands

   Affiliation as printed

   SRON Netherlands Institute for Space Research, Utrecht, the Netherlands

10. A. Anthony Bloom

    Jet Propulsion Laboratory

    Affiliation as printed

    Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA

11. John R. Worden

    Jet Propulsion Laboratory

    Affiliation as printed

    Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA

12. Robert J. Parker

    University of Leicester · National Centre for Earth Observation

    Affiliation as printed

    Earth Observation Science, School of Physics and Astronomy, University of Leicester, Leicester, UK

    National Centre for Earth Observation, University of Leicester, Leicester, UK