Preprints
https://doi.org/10.5194/acp-2022-118
https://doi.org/10.5194/acp-2022-118
 
16 Mar 2022
16 Mar 2022
Status: this preprint is currently under review for the journal ACP.

High-resolution inverse modelling of European CH4 emissions using novel FLEXPART-COSMO TM5 4DVAR inverse modelling system

Peter Bergamaschi1,, Arjo Segers2, Dominik Brunner3, Jean-Matthieu Haussaire3, Stephan Henne3, Michel Ramonet4, Tim Arnold5,6, Tobias Biermann7, Huilin Chen8, Sebastien Conil9, Marc Delmotte4, Grant Forster10, Arnoud Frumau11, Dagmar Kubistin12, Xin Lan13,14, Markus Leuenberger15, Matthias Lindauer12, Morgan Lopez4, Giovanni Manca1, Jennifer Müller-Williams12, Simon O’Doherty16, Bert Scheeren8, Martin Steinbacher3, Pamela Trisolino17, Gabriela Vítková18, and Camille Yver Kwok4 Peter Bergamaschi et al.
  • 1European Commission Joint Research Centre (JRC), Ispra (Va), Italy
  • 2Netherlands Organisation for Applied Scientific Research (TNO), Utrecht, The Netherlands
  • 3Swiss Federal Laboratories for Materials Science and Technology (Empa), Dübendorf, Switzerland
  • 4Laboratoire des Sciences du Climat et de l’Environnement (LSCE-IPSL), CEA-CNRS-UVSQ, Université Paris-Saclay, 91191 Gif-sur-Yvette, France
  • 5National Physical Laboratory, Teddington, UK
  • 6School of GeoSciences, University of Edinburgh, Edinburgh, UK
  • 7Centre for Environmental and Climate Science (CEC) Lund University, Sweden
  • 8University of Groningen, Groningen, The Netherlands
  • 9Agence nationale pour la gestion des dechets radioactifs (Andra), DRD/OPE, Bure, France
  • 10University of East Anglia, Norwich, UK
  • 11Netherlands Organisation for Applied Scientific Research (TNO), Petten, The Netherlands
  • 12Deutscher Wetterdienst, Hohenpeissenberg Meteorological Observatory (MOHp), Germany
  • 13Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder, Boulder, CO, USA
  • 14NOAA Earth System Research Laboratory, Global Monitoring Laboratory, Boulder, CO, USA
  • 15University of Bern, Physics Institute, Climate and Environmental Division, and Oeschger Centre for Climate Change Research, Bern, Switzerland
  • 16Atmospheric Chemistry Research Group, University of Bristol, Bristol, UK
  • 17National Research Council of Italy, Institute of Atmospheric Sciences and Climate (CNR-ISAC), Bologna, Italy
  • 18Global Change Research Institute of the Czech Academy of Sciences, Brno, Czech Republic
  • retired

Abstract. We present a novel high-resolution inverse modelling system ("FLEXVAR") based on FLEXPART-COSMO 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 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 to better reproduce the observations 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 United Kingdom and Ireland agree relatively well with the total of anthropogenic and natural bottom-up inventories.

Peter Bergamaschi et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on acp-2022-118', Anonymous Referee #1, 05 Apr 2022
  • RC2: 'Comment on acp-2022-118', Anonymous Referee #2, 12 Apr 2022

Peter Bergamaschi et al.

Peter Bergamaschi et al.

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Short summary
We present a novel high-resolution inverse modelling system ("FLEXVAR") and its application for the inverse modelling of European CH4 emissions in 2018. The new FLEXVAR system combines high spatial resolution of 7 km x 7 km with a variational data assimilation technique, which allows to optimize CH4 emissions from individual model grid cells. The high resolution allows to better reproduce the observations, while the derived emissions show overall good consistency with two existing models.
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