An A-train and MERRA view of cloud, thermodynamic, and dynamic variability within the subtropical marine boundary layer

Kahn, Brian H.; Matheou, Georgios; Yue, Qing; Fauchez, Thomas; Fetzer, Eric J.; Lebsock, Matthew; Martins, João; Schreier, Mathias M.; Suzuki, Kentaroh; Teixeira, João

doi:https://doi.org/10.5194/acp-17-9451-2017

Articles | Volume 17, issue 15

https://doi.org/10.5194/acp-17-9451-2017

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

https://doi.org/10.5194/acp-17-9451-2017

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

Articles | Volume 17, issue 15

Research article

|

07 Aug 2017

Research article |

| 07 Aug 2017

An A-train and MERRA view of cloud, thermodynamic, and dynamic variability within the subtropical marine boundary layer

Brian H. Kahn, Georgios Matheou, Qing Yue, Thomas Fauchez, Eric J. Fetzer, Matthew Lebsock, João Martins, Mathias M. Schreier, Kentaroh Suzuki, and João Teixeira

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Final revised paper (published on 07 Aug 2017)
Preprint (discussion started on 06 Feb 2017)

Interactive discussion

Status: closed

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

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RC1: 'Review', Anonymous Referee #1, 03 Mar 2017
- AC1: 'response to referee #1', Brian Kahn, 30 Mar 2017
RC2: 'Review of Kahn et al.', Anonymous Referee #2, 10 Mar 2017
- AC2: 'response to referee #2', Brian Kahn, 30 Mar 2017

Peer-review completion

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

AR by Brian Kahn on behalf of the Authors (13 May 2017) Author's response Manuscript

ED: Referee Nomination & Report Request started (24 May 2017) by Johannes Quaas

RR by Anonymous Referee #1 (07 Jun 2017)

Suggestions for revision or reasons for rejection

The revised manuscript is much improved. There is much greater focus on presenting these observations and highlighting the potential for this kind of investigation at the smallest possible scales from satellites and reanalysis. Besides a few minor comments that could be addressed and some typographical errors, this paper appears suitable for publication. As was clear in the original version, the great strength of the paper is the excellent collation of observations and reanalysis to provide an interesting view of subtropical clouds. The findings appear generally in line with previous results, but this paper provides a good overview, and emphasizes smaller scales than most other studies. Probably the biggest weaknesses in the paper are: (1) the introduction does not connect very well to the rest of the study, and (2) the emphasis on the joint histograms (Figs 7-12) might be too strong. These are subjective, and maybe my take on these is different from another reader.

Minor Comments

1. In terms of the introduction, I think I understand what the text is trying to do. There is a lot of discussion and reference to cloud feedbacks and climate modeling, and the point might be that we need to better understand basic processes in nature to improve our understanding and prediction of the future. I found that by the end of the introduction, however, I did not have a very good understanding of where this paper was really heading and why it matters. That is to say, why it matters in relation to similar literature rather than the big picture of cloud feedbacks and climate change prediction. This is a minor comment, so the authors should not be compelled to change it, but my feeling is that this paper would be better served by condensing the present introduction to a paragraph or two and use the recovered space to provide more context for this study. The last two paragraphs of the section start to do that, but don't quite get there. For example, in the last paragraph (neglecting the "outline paragraph"), the purpose of the paper is stated in the first sentence, but that is followed by a summary of the methodology (page 3, lines 5-9) which could be deleted because they will be stated in more detail in the next section. A later sentence ("The geophysical fields ...") is also a little too much like methodology, but it could be rewritten to provide more information about why it is important to the goal of the paper to investigate these scales and to examine them as distributions.

2. It also seems that there is an overemphasis on the joint histograms. While these are nice figures with a lot of information, I often wondered whether they were being used effectively. In particular, the text asks the reader often to compare panels visually. Actually, this is a bit difficult because the data distribution, the gray shading, is the most striking part of the figures while the comparisons are almost always regarding the colored contour lines. It's hard to provide a good suggestion for how to improve this. One possibility is to support the joint distributions with the marginal (i.e., 1-d) distributions; this could be useful especially when the dependence seems less bivariate, like in Figure 1a, 1c, and 1d where the dependence on cloud fraction seems mostly negligible. Another aspect of this over emphasis on the joint histograms is that correlations are left as visual comparisons and are not actually quantified. One could imagine that some of these relationships are not statistically significant because a lot of the variation in the CF-radiance space is occurring far from the core of the data distribution. Similarly, the visual correlations of contour lines across panels could be very misleading (though I don't see any obvious examples where that would be the case); or more importantly, the connections might be made more strongly by making the link visually in the histograms and then bringing the comparisons together in a simpler summary figure that could collect the regions and/or variables into one set of axes. Again, this is a minor comment, but it would be worth considering, especially if the microphysical relationships of Section 4.4 could be more easily summarized in a simpler graphic.

3. Page 1, Line 18: "700 an 850" is supposed to be "700-850"

4. Page 5, Line 3-4: This statement that the unknown cases look like trade cumulus is interesting, but it is not clear whether this is a new result or is included in one of the previous references.

5. Page 6, Line 9: This must be NEA instead of NEP

6. Page 7, lines 10-15: Here and elsewhere, I am not sure dMSE is adding much to this paper as its physical significance does not seem to be explained. Is it just another measure of inversion strength, like LTS and EIS?

7. Section 4.1: The tone of this section seems to be more validation than "results." It seems to be mainly showing that expected features are captured. I'm not sure whether that is the intent of the section; if so, then it might be retitled, and if not, then maybe should be revised to highlight new results.

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RR by Anonymous Referee #2 (25 Jun 2017)

Suggestions for revision or reasons for rejection

I thank the authors for their extensive response to my critical review and their revised version. I very much appreciate that they have responded at length at my concerns and made appropriate changes to the manuscript. Their response has been much more convincing of the merit of this manuscript, in particular by more clearly stating the objective and the (limits to the) scope of the paper. I believe the title is a good choice, and I also appreciate the addition of more physical interpretation to what is shown in the plots, for instance, what it means that trade-cu are identified as having an unknown thermodynamic phase. Actually, some of the statements made in the response to reviewers may also be added to the actual manuscript, which would make some aspects a bit more explicit. Before final acceptance I would ask to consider these:

1. The authors state in their response that they do not attempt to “explain the transition” so much as rather present a new way to observe it. This can be emphasized in the paper itself, and I would even say this more explicitly in the abstract. Rather than “four subtropical transitions regions are investigated”, the authors could write something like “ we demonstrate a new way of observing the transition - a region of interest because of climate uncertainties - whereby we define stratocu and trade cu exclusively based on infrared thermodynamic phase” etc.

2. The authors write in their response that it is challenging to choose which figures to present when confronted with an enormous selection of available data. I understand, but I also think it is the authors task to convincingly show a figure they believe is interesting. I also think that this choice is generally motivated by a specific question: what would you like to answer, and hence, which variables are best to start looking at? The authors may present which questions they are interested in, which in some way they already do by looking at the transition, and in specific by going into more detail about the observed relationship between wind speed, relative humidity and precipitation (effective radius). Also in the abstract the authors could rephrase their last sentences into something like: “New ways of observing the transition, using the combined Atrain & MERRA dataset, already demonstrate a relationship between effective radius, wind speed and cloudsat precipitation estimates that was previously demonstrated in surface-based observations. Hence, the combined data sets have the potential of adding global context to process-level understanding.“

3. Within the text, the authors could also emphasize that the individual cloud and thermodynamic properties from AIRS and MODIS have been previously validated and evaluated at the pixel scale, and more explicitly say that the seasonal averages are one of the only ways to compare with previous studies given that the previous studies typically only show seasonal maps.

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ED: Reconsider after minor revisions (Editor review) (27 Jun 2017) by Johannes Quaas

AR by Brian Kahn on behalf of the Authors (04 Jul 2017) Author's response Manuscript

ED: Publish as is (06 Jul 2017) by Johannes Quaas

AR by Brian Kahn on behalf of the Authors (07 Jul 2017)

Short summary

The global-scale patterns of subtropical marine boundary layer clouds are investigated with coincident NASA A-train satellite and reanalysis data. This study is novel in that all data are used at the finest spatial and temporal resolution possible. Our results are consistent with surface-based data and suggest that the combination of satellite and reanalysis data sets have potential to add to the global context of our understanding of the subtropical cumulus-dominated marine boundary layer.