Evaluation of ACCMIP ozone simulations and ozonesonde sampling biases using a satellite-based multi-constituent chemical reanalysis

Miyazaki, Kazuyuki; Bowman, Kevin

doi:https://doi.org/10.5194/acp-17-8285-2017

Articles | Volume 17, issue 13

https://doi.org/10.5194/acp-17-8285-2017

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

https://doi.org/10.5194/acp-17-8285-2017

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

Articles | Volume 17, issue 13

Research article

|

07 Jul 2017

Research article |

| 07 Jul 2017

Evaluation of ACCMIP ozone simulations and ozonesonde sampling biases using a satellite-based multi-constituent chemical reanalysis

Kazuyuki Miyazaki and Kevin Bowman

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Final revised paper (published on 07 Jul 2017)
Preprint (discussion started on 23 Dec 2016)

Interactive discussion

Status: closed

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

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- Supplement

RC1: 'Review of Miyazaki and Bowman', Anonymous Referee #2, 20 Jan 2017
- AC2: 'Response to referee #2', Kazuyuki Miyazaki, 05 Apr 2017
RC2: 'Review', Anonymous Referee #1, 27 Jan 2017
- AC1: 'Response to referee #1', Kazuyuki Miyazaki, 05 Apr 2017

Peer-review completion

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

AR by Kazuyuki Miyazaki on behalf of the Authors (05 Apr 2017) Author's response Manuscript

ED: Referee Nomination & Report Request started (05 Apr 2017) by Chul Han Song

RR by Anonymous Referee #2 (15 Apr 2017)

RR by Anonymous Referee #1 (08 May 2017)

Suggestions for revision or reasons for rejection

Evaluation of ACCMIP ozone simulations using a multi-constituent chemical reanalysis
by Kazuyuki Miyazaki and Kevin Bowman

Overview:

The paper is the first revision of an earlier submission. The paper has improved a lot because a more stringent focus was put on the ozone sampling bias. But, the authors should not only highlight the large sampling biases in certain regions but give more information about the areas of medium and low sampling biases. I recommend publication after addressing the following issues:

Abstract:

P1 L18: define better the relative sampling bias, i.e relative to what?)

P1L19: Also give information about typical sampling biases in other regions.

P1 L8 better “emissions sources”

P1 L25 – add . after al

P1 L28 “data do”

P3 L2 add “strong” between not and enough

P3 L16 f. Inness et al. 2013 use a coupled system IFS-MOZART. Flemming et al. 2017 use C-IFS with CB05 chemistry in their re-analysis.

P5 l31, at . after al

P11L25 Define “seasonal amplitude”

P17L33. Please discuss Fig. 11 in more detail, especially the analysis errors and their relation to the ACCMIP ensemble spread. Why is the ensemble spread at 200 hPa so much larger than the re-analysis error? How do the different tropopause definitions impact the ozone sampling error?

P19 L33: define sampling biases. Say what you did to get to relative numbers. Also summarise the sampling biases for the regions with low to moderate sampling biases (see Figure 9).

Table 2
Should be Legionowo not Legionowa
Spell out Hohenpbg

Figure 1:
Mention in caption that you show relative errors, also relative to what

Figure 5:
Clarify if the models are shown at “complete” or “ozone-sonde” sampling

Figure 6:
Please add also the seasonal amplitude from the ozone-sonde sampling as this is also done in the other figures (e.g. Figure 7). Explain averaging interval for the seasonal amplitude (i.e. monthly values)

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ED: Reconsider after minor revisions (Editor review) (18 May 2017) by Chul Han Song

AR by Kazuyuki Miyazaki on behalf of the Authors (25 May 2017) Author's response Manuscript

ED: Publish as is (12 Jun 2017) by Chul Han Song

Short summary

The ACCMIP ensemble ozone simulations are evaluated by a state-of-the-art multi-constituent chemical reanalysis. The reanalysis product provides comprehensive and unique information on the weakness of the individual models and multi-model mean. The differences are less evident with the current sonde network, which is shown to provide biased regional and monthly ozone statistics. The evaluation results have implications for ozone radiative forcing and the response of chemistry to climate.