Preprints
https://doi.org/10.5194/gmd-2021-339
https://doi.org/10.5194/gmd-2021-339
Submitted as: development and technical paper
02 Nov 2021
Submitted as: development and technical paper | 02 Nov 2021
Status: a revised version of this preprint was accepted for the journal GMD and is expected to appear here in due course.

Order of magnitude wall time improvement of variational methane inversions by physical parallelization: a demonstration using TM5-4DVAR

Sudhanshu Pandey1, Sander Houweling2, and Arjo Segers3 Sudhanshu Pandey et al.
  • 1SRON Netherlands Institute for Space Research, Utrecht, the Netherlands
  • 2Department of Earth Sciences, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
  • 3TNO Department of Climate, Air and Sustainability, Utrecht, The Netherlands

Abstract. Atmospheric inversions are used to constrain the emissions of trace gases from atmospheric mole fraction measurements. The variational (4DVAR) inversion approach allows optimization of the emissions at a much higher temporal and spatial resolution than the ensemble or analytical approaches but provides limited opportunities for scalable parallelization as the optimization is performed iteratively. Multidecadal variational inversions are used to optimally extract information from the long measurement records of long-lived atmospheric trace gases like carbon dioxide and methane. However, the wall clock time needed—up to months— complicates these multidecadal inversions. The physical parallelization method introduced by Chevallier (2013) addresses this problem for CO2 inversions by splitting the time period of the chemical transport model into blocks that are run in parallel. Here we present a new implementation of the physical parallelization for variational inversion (PPVI) approach that is suitable for methane inversions as it accounts for methane’s atmospheric lifetime. The performance of PPVI is tested in an 11-year inversion using a TM5-4DVAR inversion setup that assimilates surface observations to optimize methane emissions at grid-scale. We find that the PPVI inversion approach improves the wall clock time performance by a factor of 5 and shows excellent agreement with the posterior emissions of a full serial inversion with identical configuration (global mean emissions difference = 0.06 % with an interannual variation correlation R = 99 %; regional mean emission difference < 5 % and interannual variation R > 0.95). The wall clock time improvement using the PPVI method increases with the size of the inversion period. The PPVI approach is planned to be used in future releases of the CAMS (Copernicus Atmosphere Monitoring Service) multidecadal methane reanalysis.

Sudhanshu Pandey et al.

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • CEC1: 'Comment on gmd-2021-339', Juan Antonio Añel, 19 Nov 2021
    • AC1: 'Reply on CEC1', Sudhanshu Pandey, 06 Mar 2022
  • RC1: 'Comment on gmd-2021-339', Anonymous Referee #1, 02 Dec 2021
    • AC2: 'Author response to the reviewer comments', Sudhanshu Pandey, 06 Mar 2022
  • RC2: 'Comment on gmd-2021-339', Anonymous Referee #2, 07 Dec 2021
  • RC3: 'Comment on gmd-2021-339', Anonymous Referee #3, 12 Dec 2021
    • AC2: 'Author response to the reviewer comments', Sudhanshu Pandey, 06 Mar 2022
  • AC2: 'Author response to the reviewer comments', Sudhanshu Pandey, 06 Mar 2022

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • CEC1: 'Comment on gmd-2021-339', Juan Antonio Añel, 19 Nov 2021
    • AC1: 'Reply on CEC1', Sudhanshu Pandey, 06 Mar 2022
  • RC1: 'Comment on gmd-2021-339', Anonymous Referee #1, 02 Dec 2021
    • AC2: 'Author response to the reviewer comments', Sudhanshu Pandey, 06 Mar 2022
  • RC2: 'Comment on gmd-2021-339', Anonymous Referee #2, 07 Dec 2021
  • RC3: 'Comment on gmd-2021-339', Anonymous Referee #3, 12 Dec 2021
    • AC2: 'Author response to the reviewer comments', Sudhanshu Pandey, 06 Mar 2022
  • AC2: 'Author response to the reviewer comments', Sudhanshu Pandey, 06 Mar 2022

Sudhanshu Pandey et al.

Sudhanshu Pandey et al.

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Short summary
Inverse models are used to calculate surface emissions of methane from atmospheric mole fraction measurements. However the model calculation when performed on multidecadal timescales can take months to finish. Here we show an order of magnitude wall clock time improvement in such calculations by physical parallelization of atmospheric chemical transport model.