Improved method for linear carbon monoxide simulation and source attribution in atmospheric chemistry models illustrated using GEOS-Chem v9

Fisher, Jenny A.; Murray, Lee T.; Jones, Dylan B. A.; Deutscher, Nicholas M.

doi:https://doi.org/10.5194/gmd-10-4129-2017

Articles | Volume 10, issue 11

https://doi.org/10.5194/gmd-10-4129-2017

© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

https://doi.org/10.5194/gmd-10-4129-2017

© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Articles | Volume 10, issue 11

Development and technical paper

|

15 Nov 2017

Development and technical paper |

| 15 Nov 2017

Improved method for linear carbon monoxide simulation and source attribution in atmospheric chemistry models illustrated using GEOS-Chem v9

Jenny A. Fisher, Lee T. Murray, Dylan B. A. Jones, and Nicholas M. Deutscher

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Final revised paper (published on 15 Nov 2017)
Supplement to the final revised paper
Preprint (discussion started on 03 May 2017)
Supplement to the preprint

Interactive discussion

Status: closed

AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

- Printer-friendly version

- Supplement

RC1: 'review comments', Anonymous Referee #1, 28 Jun 2017
- AC1: 'Response to Anonymous Referee #1', Jenny Fisher, 22 Jul 2017
RC2: 'review', Anonymous Referee #2, 30 Jun 2017
- AC2: 'Response to Anonymous Referee #2', Jenny Fisher, 22 Jul 2017

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision

AR by Jenny Fisher on behalf of the Authors (23 Jul 2017) Author's response Manuscript

ED: Referee Nomination & Report Request started (03 Aug 2017) by Volker Grewe

RR by Anonymous Referee #2 (16 Aug 2017)

Suggestions for revision or reasons for rejection

In general the authors considered all reviewer comments. In particular, the changed simulations names, inclusion of the new Table 1 and the updated figures help a lot to improve the manuscript. However, I think that some points could have been described in more detail or more clearly (e.g. the new equation 2). This would increase the quality of the document.
I overall agree with the points where the authors did not incorporate the suggested changes.

The issue of the influence of the prescribed CO production rates, however, is still not discussed in sufficient detail. The authors added a Section in the supplement clearly showing that for the years 2009/2010/2011 the variability of meteorology/emissions influence CO more as the variability of the secondary CO production. However, comparing only 2009/2010/2011 this could be by chance. As the usage of the prescribed CO production rates is crucial for a good performance of the linear CO only model this needs to be discussed in more detail - e.g. what happens under 'extreme' conditions (e.g. strong biomass burning events). Especially, as these CO production rates are tagged to distinguish the geographical regions, the influence of the prescribed production rates on the tagging results should be investigated.

Minor comments:
On p5 l 25 of the revised manuscript you are now writing: ".... to bring them up to date with". Does this mean that these updates were already included in version 11.01 and you updated only your "working version"? I think this paragraph should be rephrased to discuss in detail which updates of the CO-only simulation has been performed by whom (in which version).

Technical correction:
Supplement: Fig S8 - Figure and caption are on different pages.

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ED: Publish subject to minor revisions (Editor review) (11 Sep 2017) by Volker Grewe

AR by Jenny Fisher on behalf of the Authors (19 Sep 2017) Author's response Manuscript

ED: Publish as is (27 Sep 2017) by Volker Grewe

AR by Jenny Fisher on behalf of the Authors (27 Sep 2017)

Short summary

Carbon monoxide (CO) simulation in atmospheric chemistry models is used for source–receptor analysis, emission inversion, and interpretation of observations. We introduce a major update to CO simulation in the GEOS-Chem chemical transport model that removes fundamental inconsistencies relative to the standard model, resolving biases of more than 100 ppb and errors in vertical structure. We also add source tagging of secondary CO and demonstrate it provides added value in low-emission regions.