Preprints
https://doi.org/10.5194/gmd-2020-407
https://doi.org/10.5194/gmd-2020-407

Submitted as: model description paper 18 Dec 2020

Submitted as: model description paper | 18 Dec 2020

Review status: this preprint is currently under review for the journal GMD.

The Community Inversion Framework v1.0: a unified system for atmospheric inversion studies

Antoine Berchet1, Espen Sollum2, Rona L. Thompson2, Isabelle Pison1, Joël Thanwerdas1, Grégoire Broquet1, Frédéric Chevallier1, Tuula Aalto3, Peter Bergamaschi4, Dominik Brunner5, Richard Engelen6, Audrey Fortems-Cheiney1, Christoph Gerbig7, Christine Groot Zwaaftink2, Jean-Matthieu Haussaire5, Stephan Henne5, Sander Houweling8, Ute Karstens9, Werner L. Kutsch10, Ingrid T. Luijkx11, Guillaume Monteil9, Paul I. Palmer12, Jacob C. A. van Peet8, Wouter Peters11,13, Philippe Peylin1, Elise Potier1, Christian Rödenbeck7, Marielle Saunois1, Marko Scholze9, Aki Tsuruta3, and Yuanhong Zhao1 Antoine Berchet et al.
  • 1Laboratoire des Sciences du Climat et de l’Environnement, CEA-CNRS-UVSQ, Gif-sur-Yvette, France
  • 2Norwegian Institute for Air Research (NILU), Kjeller, Norway
  • 3Finnish Meteorological Institute (FMI), Helsinki, Finland
  • 4European Commission Joint Research Centre, Ispra (Va), Italy
  • 5Swiss Federal Laboratories for Materials Science and Technology (Empa), Dübendorf, Switzerland
  • 6European Centre for Medium-Range Weather Forecasts, Reading, RG2 9AX, UK
  • 7Max Planck Institute for Biogeochemistry, Jena, Germany
  • 8Vrije Universiteit Amsterdam, Department of Earth Sciences, Earth and Climate Cluster, Amsterdam, the Netherlands
  • 9Dep. of Physical Geography and Ecosystem Science, Lund University, Sweden
  • 10Integrated Carbon Observation System (ICOS-ERIC), Helsinki, Finland
  • 11Meteorology and Air Quality Group, Wageningen University and Research, Wageningen, the Netherlands
  • 12School of GeoSciences, University of Edinburgh, Edinburgh, EH9 3FF, UK
  • 13Centre for Isotope Research, University of Groningen, Groningen, the Netherlands

Abstract. Atmospheric inversion approaches are expected to play a critical role in future observation-based monitoring systems for surface greenhouse gas (GHG) fluxes. In the past decade, the research community has developed various inversion softwares, mainly using variational or ensemble Bayesian optimization methods, with various assumptions on uncertainty structures and prior information and with various atmospheric chemistry-transport models. Each of them can assimilate some or all of the available observation streams for its domain area of interest: flask samples, in-situ measurements or satellite observations. Although referenced in peer-reviewed publications and usually accessible across the research community, most systems are not at the level of transparency, flexibility and accessibility needed to provide the scientific community and policy makers with a comprehensive and robust view of the uncertainties associated with the inverse estimation of GHG fluxes. Furthermore, their development, usually carried out by individual research institutes, may in the future not keep pace with the increasing scientific needs and technical possibilities. We present here a Community Inversion Framework (CIF) to help rationalize development efforts and leverage the strengths of individual inversion systems into a comprehensive framework. The CIF is primarily a programming protocol to allow various inversion bricks to be exchanged among researchers. In practice, the ensemble of bricks makes a flexible, transparent and open-source python-based tool to estimate the fluxes of various GHGs both at global and regional scales. It will allow running different atmospheric transport models, different observation streams and different data assimilation approaches. This adaptability will allow a comprehensively assessment of uncertainty in a fully consistent framework. We present here the main structure and functionalities of the system, and demonstrate how it operates in a simple academic case.

Antoine Berchet et al.

 
Status: open (until 12 Feb 2021)
Status: open (until 12 Feb 2021)
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Antoine Berchet et al.

Model code and software

The Community Inversion Framework: codes and documentation Antoine Berchet, Espen Sollum, Isabelle Pison, Rona L. Thompson, Joël Thanwerdas, Audrey Fortems-Cheiney, Jacob C. A. van Peet, Elise Potier, Frédéric Chevallier, and Grégoire Broquet https://doi.org/10.5281/zenodo.4322372

Antoine Berchet et al.

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Short summary
We present here a Community Inversion Framework (CIF) to help rationalize development efforts and leverage the strengths of individual inversion systems into a comprehensive framework. The CIF is a programming protocol to allow various inversion bricks to be exchanged among researchers. The ensemble of bricks makes a flexible, transparent and open-source python-based tool. We describe the main structure and functionalities and demonstrate it in a simple academic case.