Journal cover Journal topic
Atmospheric Chemistry and Physics An interactive open-access journal of the European Geosciences Union
Journal topic

Journal metrics

IF value: 5.414
IF5.414
IF 5-year value: 5.958
IF 5-year
5.958
CiteScore value: 9.7
CiteScore
9.7
SNIP value: 1.517
SNIP1.517
IPP value: 5.61
IPP5.61
SJR value: 2.601
SJR2.601
Scimago H <br class='widget-line-break'>index value: 191
Scimago H
index
191
h5-index value: 89
h5-index89
Download
Short summary
Although it is the second most important greenhouse gas, our understanding of the atmospheric methane budget is limited. The uncertainty highlights the need for new tools to investigate sources and sinks. Here, we use a Gaussian process emulator to efficiently approximate the response of atmospheric methane observations to changes in the most uncertain emission or loss processes. With this new method, we rigorously quantify the sensitivity of atmospheric observations to budget uncertainties.
Altmetrics
Preprints
https://doi.org/10.5194/acp-2020-871
https://doi.org/10.5194/acp-2020-871

  24 Aug 2020

24 Aug 2020

Review status: a revised version of this preprint was accepted for the journal ACP and is expected to appear here in due course.

Atmospheric methane source and sink sensitivity analysis using Gaussian process emulation

Angharad C. Stell, Luke M. Western, and Matthew Rigby Angharad C. Stell et al.
  • School of Chemistry, University of Bristol, Bristol, BS8 1TS, UK

Abstract. We present a method to efficiently approximate the response of atmospheric methane mole fraction and δ13C-CH4 to changes in uncertain emission and loss parameters in a three-dimensional global chemical transport model. Our approach, based on Gaussian process emulation, allows relationships between inputs and outputs in the model to be efficiently explored. The presented emulator successfully reproduces the chemical transport model output with a root-mean-square error of 1.2 ppb and 0.06 ‰ for hemispheric methane mole fraction and δ13C-CH4, respectively, for 28 uncertain model inputs. The method is shown to outperform multiple linear regression, because it captures non-linear relationships between inputs and outputs, as well as the interaction between model input parameters. The emulator was used to determine how sensitive methane mole fraction and δ13C-CH4 are to the major source and sink components of the atmospheric budget, given current estimates of their uncertainty. We find that our current knowledge of the methane budget, as inferred through hemispheric mole fraction observations, is limited primarily by uncertainty in the global mean hydroxyl radical concentration and emissions from fresh water. Our work quantitatively determines the added value of measurements of δ13C-CH4, which are sensitive to some uncertain parameters that mole fraction observations on their own are not. However, we demonstrate the critical importance of constraining isotopic initial conditions and isotopic source signatures, small uncertainties in which strongly influence long-term δ13C-CH4 trends, because of the long timescales over which transient perturbations propagate through the atmosphere. Our results also demonstrate that the magnitude and trend of methane mole fraction and δ13C-CH4 can be strongly influenced by the combined uncertainty of more minor components of the atmospheric budget, which are often fixed and assumed to be well-known in inverse modelling studies (e.g. emissions from termites, hydrates, and oceans). Overall, our work provides an overview of the sensitivity of atmospheric observations to budget uncertainties and outlines a method which could be employed to account for these uncertainties in future inverse modelling systems.

Angharad C. Stell et al.

 
Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement
 
Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement

Angharad C. Stell et al.

Model code and software

Global methane freshwater emission map for atmospheric modelling A.C. Stell https://doi.org/10.17605/OSF.IO/Q9F8P

Atmospheric methane source and sink sensitivity analysis using Gaussian process emulation A.C. Stell https://doi.org/10.17605/OSF.IO/Z435M

Angharad C. Stell et al.

Viewed

Total article views: 243 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
177 63 3 243 35 10 6
  • HTML: 177
  • PDF: 63
  • XML: 3
  • Total: 243
  • Supplement: 35
  • BibTeX: 10
  • EndNote: 6
Views and downloads (calculated since 24 Aug 2020)
Cumulative views and downloads (calculated since 24 Aug 2020)

Viewed (geographical distribution)

Total article views: 299 (including HTML, PDF, and XML) Thereof 297 with geography defined and 2 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 26 Jan 2021
Publications Copernicus
Download
Short summary
Although it is the second most important greenhouse gas, our understanding of the atmospheric methane budget is limited. The uncertainty highlights the need for new tools to investigate sources and sinks. Here, we use a Gaussian process emulator to efficiently approximate the response of atmospheric methane observations to changes in the most uncertain emission or loss processes. With this new method, we rigorously quantify the sensitivity of atmospheric observations to budget uncertainties.
Citation
Altmetrics