High-resolution inverse modelling of European CH4emissions using the novel FLEXPART-COSMO TM5 4DVAR inverse modelling system

Peter Bergamaschi*, Arjo Segers, Dominik Brunner, Jean Matthieu Haussaire, Stephan Henne, Michel Ramonet, Tim Arnold, Tobias Biermann, Huilin Chen, Sebastien Conil, Marc Delmotte, Grant Forster, Arnoud Frumau, Dagmar Kubistin, Xin Lan, Markus Leuenberger, Matthias Lindauer, Morgan Lopez, Giovanni Manca, Jennifer Müller-WilliamsSimon O'Doherty, Bert Scheeren, Martin Steinbacher, Pamela Trisolino, Gabriela Vítková, Camille Yver Kwok

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

9 Citations (Scopus)

Abstract

We present a novel high-resolution inverse modelling system ("FLEXVAR") based on FLEXPARTCOSMO back trajectories driven by COSMO meteorological fields at 7 km×7 km resolution over the European COSMO-7 domain and the four-dimensional variational (4DVAR) data assimilation technique. FLEXVAR is coupled offline with the global inverse modelling system TM5-4DVAR to provide background mole fractions ("baselines") consistent with the global observations assimilated in TM5-4DVAR. We have applied the FLEXVAR system for the inverse modelling of European CH4 emissions in 2018 using 24 stations with in situ measurements, complemented with data from five stations with discrete air sampling (and additional stations outside the European COSMO-7 domain used for the global TM5-4DVAR inversions). The sensitivity of the FLEXVAR inversions to different approaches to calculate the baselines, different parameterizations of the model representation error, different settings of the prior error covariance parameters, different prior inventories, and different observation data sets are investigated in detail. Furthermore, the FLEXVAR inversions are compared to inversions with the FLEXPART extended Kalman filter ("FLExKF") system and with TM5-4DVAR inversions at 1° × 1° resolution over Europe. The three inverse modelling systems show overall good consistency of the major spatial patterns of the derived inversion increments and in general only relatively small differences in the derived annual total emissions of larger country regions. At the same time, the FLEXVAR inversions at 7 km × 7 km resolution allow the observations to be better reproduced than the TM5-4DVAR simulations at 1° × 1°. The three inverse models derive higher annual total CH4 emissions in 2018 for Germany, France, and BENELUX compared to the sum of anthropogenic emissions reported to UNFCCC and natural emissions estimated from the Global Carbon Project CH4 inventory, but the uncertainty ranges of top-down and bottom-up total emission estimates overlap for all three country regions. In contrast, the top-down estimates for the sum of emissions from the UK and Ireland agree relatively well with the total of anthropogenic and natural bottom-up inventories.

Original languageEnglish
Pages (from-to)13243-13268
Number of pages26
JournalAtmospheric Chemistry and Physics
Volume22
Issue number20
DOIs
Publication statusPublished - 17 Oct 2022

Bibliographical note

Funding Information:
The VERIFY project has received funding from the European Union's Horizon 2020 Research and Innovation programme under grant agreement no. 776810. We are grateful to ECMWF for providing computing resources under the special projects “Improve European and global CH and NO flux inversions (2018–2020)” and “Extend and improve CH flux inversions at global and European scale (2021)”. Furthermore, we thank Bradley Matthews for the compilation of uncertainties of emissions reported to UNFCCC by EU member states. ICOS Switzerland was funded by the Swiss National Science Foundation, in-house contributions, and the State Secretariat for Education, Research and Innovation.

Funding Information:
This research has been supported by Horizon 2020 (grant no. VERIFY (776810)).

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