Global and regional estimates of warm cloud droplet number concentration based on 13 years of AQUA-MODIS observations

Bennartz, Ralf; Rausch, John

doi:https://doi.org/10.5194/acp-17-9815-2017

Articles | Volume 17, issue 16

https://doi.org/10.5194/acp-17-9815-2017

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

https://doi.org/10.5194/acp-17-9815-2017

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

Articles | Volume 17, issue 16

Research article

|

22 Aug 2017

Research article |

| 22 Aug 2017

Global and regional estimates of warm cloud droplet number concentration based on 13 years of AQUA-MODIS observations

Ralf Bennartz and John Rausch

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Final revised paper (published on 22 Aug 2017)
Preprint (discussion started on 10 Jan 2017)

Interactive discussion

Status: closed

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

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SC1: 'Strange sentence in abstract', Alf Grini, 17 Jan 2017
- AC1: 'reply', Ralf Bennartz, 22 May 2017
RC1: 'Uncertainty quantification overly superficial, adiabatic model description missing', Anonymous Referee #1, 05 Feb 2017
- AC2: 'response to anonymous reviewer #1 Comments', Ralf Bennartz, 22 May 2017
RC2: 'Referee review of Bennartz and Rausch, ACPD, 2017', Anonymous Referee #2, 07 Feb 2017
- AC3: 'response to anonymous reviewer #2', Ralf Bennartz, 22 May 2017

Peer-review completion

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

AR by Ralf Bennartz on behalf of the Authors (22 May 2017) Author's response Manuscript

ED: Referee Nomination & Report Request started (25 May 2017) by Philip Stier

RR by Anonymous Referee #1 (06 Jun 2017)

Suggestions for revision or reasons for rejection

Bennartz and Rausch have answered my minor or specific comments satisfactorily. However, I feel that my two main remarks were not addressed substantially.

1. As for the “Idealized Stratiform Boundary Layer Cloud”, I believe I’d be happy if they explicitly wrote, at the instance where the authors introduce this term, that they mean exactly the same they meant before by the term “adiabatic cloud model”. As such, the reader can understand that it is simply a re-branding of the same thing.

2. As for the “uncertainty” assessment – the authors still call the sub-scale variability “uncertainty”. I believe this is mis-leading. The newly added paragraph does not improve the assessment much. The authors write in this paragraph “… the standard deviation of all Level 2 observations within a given 1x1 degree box … should in any case be larger than the uncertainty derived from error propagation”. This would be the case if all errors are statistical errors. However, it is clear that there may be substantial systematic errors in the retrieval as well.
The authors write that because the subscale standard deviation is larger than the assessed propagated retrieval error, data users may be more interested in this quantity. I believe, in turn, that users should be able to tell apart what is variability and what is error. Only the latter is an actual uncertainty, the former should be a measure of a meaningful physical behaviour.
As such, I maintain my previous remark that if the authors choose to report subscale variability, they should call it “subscale variability”. If the authors choose to do more rigorous error analysis, more detail is needed on how the error is computed and how it is propagated. In any case, the reader needs more details on how exactly Fig. 8 (top panel) was created.

Typos

p2 l28: km²
p16 l18: consistent
p16 l26: “These … themselves”
Caption Fig. 3: “fraction of a typical” - the authors should clarify what they mean by “typical”

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RR by Anonymous Referee #2 (10 Jun 2017)

ED: Reconsider after major revisions (21 Jun 2017) by Philip Stier

AR by Ralf Bennartz on behalf of the Authors (11 Jul 2017) Manuscript

ED: Publish as is (17 Jul 2017) by Philip Stier

AR by Ralf Bennartz on behalf of the Authors (20 Jul 2017)

Short summary

Cloud droplet number concentration is linked to air pollution levels via indirect aerosol effects. The climatological results presented here provide constraints on cloud droplet number concentration globally, thereby helping to evaluate global climate models and study the impact of pollution regionally and globally.