Preprints
https://doi.org/10.5194/egusphere-2022-513
https://doi.org/10.5194/egusphere-2022-513
04 Jul 2022
 | 04 Jul 2022

Modelling the growth of atmospheric nitrous oxide using a global hierarchical inversion

Angharad C. Stell, Michael Bertolacci, Andrew Zammit-Mangion, Matthew Rigby, Paul J. Fraser, Christina M. Harth, Paul B. Krummel, Xin Lan, Manfredi Manizza, Jens Mühle, Simon O'Doherty, Ronald G. Prinn, Ray F. Weiss, Dickon Young, and Anita L. Ganesan

Abstract. Nitrous oxide is a potent greenhouse gas and ozone depleting substance, whose atmospheric abundance has risen throughout the contemporary record. In this work, we carry out the first global hierarchical Bayesian inversion to solve for nitrous oxide emissions, which includes prior emissions with non-Gaussian distributions and model errors, in order to examine the drivers of the atmospheric surface growth rate. We show that both meteorology and emissions are key drivers of variations in the surface nitrous oxide growth rate between 2011 and 2020. We derive increasing global nitrous oxide emissions, which are mainly driven by emissions between 0° and 30° N, with the highest emissions recorded in 2020. Our mean global total emissions for 2011–2020 of 17.2 (16.7–17.7 at the 95 % credible intervals) TgN yr-1, comprising of 12.0 (11.2–12.8) TgN yr-1 from land and 5.2 (4.5–5.9) TgN yr-1 from ocean, agrees well with previous studies, but we find that emissions are poorly constrained for some regions of the world, particularly for the oceans. The prior emissions used in this and other previous work exhibit a seasonal cycle in the Northern Hemisphere extra-tropics that is out of phase with the posterior solution, and there is a substantial zonal redistribution of emissions from the prior to the posterior. Correctly characterising the uncertainties in the system, for example in the prior emission fields, is crucial to be able to derive posterior fluxes that are consistent with observations. In this hierarchical inversion, the model-measurement discrepancy and the prior flux uncertainty are informed by the data, rather than solely through expert judgment. We show cases where this framework provides different plausible adjustments to the prior fluxes compared to inversions using widely adopted, fixed uncertainty constraints.

Journal article(s) based on this preprint

10 Oct 2022
Modelling the growth of atmospheric nitrous oxide using a global hierarchical inversion
Angharad C. Stell, Michael Bertolacci, Andrew Zammit-Mangion, Matthew Rigby, Paul J. Fraser, Christina M. Harth, Paul B. Krummel, Xin Lan, Manfredi Manizza, Jens Mühle, Simon O'Doherty, Ronald G. Prinn, Ray F. Weiss, Dickon Young, and Anita L. Ganesan
Atmos. Chem. Phys., 22, 12945–12960, https://doi.org/10.5194/acp-22-12945-2022,https://doi.org/10.5194/acp-22-12945-2022, 2022
Short summary

Angharad C. Stell et al.

Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2022-513', Anonymous Referee #1, 21 Jul 2022
    • AC1: 'Reply on RC1', Angharad Stell, 30 Aug 2022
  • RC2: 'Comment on egusphere-2022-513', Anonymous Referee #2, 29 Jul 2022
    • AC2: 'Reply on RC2', Angharad Stell, 30 Aug 2022

Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2022-513', Anonymous Referee #1, 21 Jul 2022
    • AC1: 'Reply on RC1', Angharad Stell, 30 Aug 2022
  • RC2: 'Comment on egusphere-2022-513', Anonymous Referee #2, 29 Jul 2022
    • AC2: 'Reply on RC2', Angharad Stell, 30 Aug 2022

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
AR by Angharad Stell on behalf of the Authors (30 Aug 2022)  Author's response   Manuscript 
EF by Mika Burghoff (31 Aug 2022)  Author's tracked changes 
ED: Publish subject to minor revisions (review by editor) (06 Sep 2022) by Andreas Hofzumahaus
AR by Angharad Stell on behalf of the Authors (15 Sep 2022)  Author's response   Author's tracked changes   Manuscript 
ED: Publish as is (16 Sep 2022) by Andreas Hofzumahaus
AR by Angharad Stell on behalf of the Authors (16 Sep 2022)

Journal article(s) based on this preprint

10 Oct 2022
Modelling the growth of atmospheric nitrous oxide using a global hierarchical inversion
Angharad C. Stell, Michael Bertolacci, Andrew Zammit-Mangion, Matthew Rigby, Paul J. Fraser, Christina M. Harth, Paul B. Krummel, Xin Lan, Manfredi Manizza, Jens Mühle, Simon O'Doherty, Ronald G. Prinn, Ray F. Weiss, Dickon Young, and Anita L. Ganesan
Atmos. Chem. Phys., 22, 12945–12960, https://doi.org/10.5194/acp-22-12945-2022,https://doi.org/10.5194/acp-22-12945-2022, 2022
Short summary

Angharad C. Stell et al.

Data sets

Data Angharad C. Stell https://doi.org/10.17605/OSF.IO/SN539

Model code and software

Code Angharad C. Stell https://doi.org/10.17605/OSF.IO/SN539

Angharad C. Stell et al.

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Short summary
Nitrous oxide is a potent greenhouse gas and ozone depleting substance, whose atmospheric abundance has risen throughout the contemporary record. In this work, we carry out the first global hierarchical Bayesian inversion to solve for nitrous oxide emissions. We derive increasing global nitrous oxide emissions, which are mainly driven by emissions between 0° and 30° N, with the highest emissions recorded in 2020.