Analysis and quantification of ENSO-linked changes in the tropical Atlantic cloud vertical distribution using 14 years of MODIS observations

Madenach, Nils; Carbajal Henken, Cintia; Preusker, René; Sourdeval, Odran; Fischer, Jürgen

doi:https://doi.org/10.5194/acp-19-13535-2019

Articles | Volume 19, issue 21

https://doi.org/10.5194/acp-19-13535-2019

© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/acp-19-13535-2019

© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 19, issue 21

Research article

|

07 Nov 2019

Research article |

| 07 Nov 2019

Analysis and quantification of ENSO-linked changes in the tropical Atlantic cloud vertical distribution using 14 years of MODIS observations

Nils Madenach, Cintia Carbajal Henken, René Preusker, Odran Sourdeval, and Jürgen Fischer

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Final revised paper (published on 07 Nov 2019)
Preprint (discussion started on 16 Jan 2019)

Interactive discussion

Status: closed

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

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RC1: 'Review of “Observation of ENSO linked changes in the tropical Atlantic cloud vertical distribution using 14 years of MODIS observations”', Anonymous Referee #1, 12 Feb 2019
- AC1: 'Reply to comment from Anonymous Referee #1', Nils Madenach, 21 Feb 2019
RC2: 'Review', Anonymous Referee #3, 20 May 2019

Peer-review completion

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

AR by Nils Madenach on behalf of the Authors (28 Jun 2019) Author's response Manuscript

ED: Referee Nomination & Report Request started (15 Jul 2019) by Bernhard Mayer

RR by Anonymous Referee #1 (13 Aug 2019)

Suggestions for revision or reasons for rejection

The revised paper is largely unchanged from the initially-submitted paper, which I did not find to be a useful contribution to the literature. However, since there is nothing fundamentally wrong with the paper, I will not stand in the way of publication. I think the authors have failed to provide much if any useful insights beyond what we already understand about the climate system.

In my opinion, the separation of the timeseries into two time periods and then computing trends within them is both arbitrary and largely meaningless. Any timeseries that has local extrema at the endpoints and in the middle could be split this way, and there is no good physical motivation for considering trends separately over these two time periods. Fundamentally the signal the authors are nominally interested in is the response of clouds to warming or to ENSO climate variations driven by El Nino, so why not just regress clouds on surface temperature or an ENSO index rather than computing trends over two periods? Unless the relevant physics somehow different over the two periods, which would be odd but at least interesting, all this analysis does is overly complicate a simple story: that ENSO induces regional ascent/descent anomalies that cause regional increases/decreases in high cloud coverage (and hence regional anomalies in the gross cloud top height, which in this case is just a proxy for anomalies in high cloud coverage).

It is also completely lost on me what insights are gained from the multiple linear regression, which includes none of the actual physics that governs clouds. (It just demonstrates that one can decompose a timeseries of regionally-averaged quantities into a mean, trend, seasonal cycle, and an ENSO term.)

Some additional specific comments:
1) The first paragraph of the introduction confuses cloud radiative forcing (or cloud radiative effect) with the cloud radiative feedback. Cloud radiative effect quantifies the radiative effect of clouds on the mean-state of the climate; the cloud feedback quantifies how this radiative effect changes per unit global temperature change. Hence the first sentence of the introduction is incorrect, as is the sentence starting on Line 3 of Page 2.
2) I don’t understand the analysis described on page 9: “As we look here at effects associated with ENSO, we used the MLRM without Nino3.4 index (see Sec. 3.2).” What does “here” mean? It is never explicitly stated how the Nino3.4 index is included in the MLRM in the first place, and it is unclear why one would remove it from the MLRM in order to look at its effects. Further, I don’t understand what you are doing in this statement: “To find the best separation of the phases the maximum of the sum of the explained variances of the two models was calculated for differing phase separations.”
3) There are many grammatical errors throughout, including:
a. P3,line26: should be “additional”
b. P4, line 22: subject-verb agreement
c. P6, lines11-12: phrasing is odd “roughly….HCF”
d. P7: unclear what “major phases” means
e. P8, line 2: “vise verse”
f. P8, line 14: should be “opposing”
g. P9, line 2: should be “where”
h. P10, line 10: “is despite of the low”
i. Table 1: “ascend” should be “ascent”

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ED: Publish subject to minor revisions (review by editor) (22 Aug 2019) by Bernhard Mayer

AR by Nils Madenach on behalf of the Authors (01 Sep 2019) Author's response Manuscript

ED: Publish as is (05 Oct 2019) by Bernhard Mayer