Precipitation susceptibility in marine stratocumulus and shallow cumulus
from airborne measurements

Jung, Eunsil; Albrecht, Bruce A.; Sorooshian, Armin; Zuidema, Paquita; Jonsson, Haflidi H.

doi:https://doi.org/10.5194/acp-16-11395-2016

Articles | Volume 16, issue 17

https://doi.org/10.5194/acp-16-11395-2016

© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

https://doi.org/10.5194/acp-16-11395-2016

© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

Articles | Volume 16, issue 17

Research article

|

14 Sep 2016

Research article |

| 14 Sep 2016

Precipitation susceptibility in marine stratocumulus and shallow cumulus from airborne measurements

Eunsil Jung, Bruce A. Albrecht, Armin Sorooshian, Paquita Zuidema, and Haflidi H. Jonsson

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Final revised paper (published on 14 Sep 2016)
Preprint (discussion started on 14 Mar 2016)

Interactive discussion

Status: closed

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

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RC1: 'Review of Jung et al. “Precipitation Susceptibility in Marine Stratocumulus and Shallow Cumulus from Airborne Measurements”', Anonymous Referee #1, 18 Apr 2016
- AC1: 'Reply to referee #1', EUNSIL JUNG, 15 Jul 2016
RC2: 'Anonymous Referee #2', Anonymous Referee #2, 10 May 2016
- AC2: 'Reply to Referee #2', EUNSIL JUNG, 15 Jul 2016

Peer-review completion

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

AR by EUNSIL JUNG on behalf of the Authors (15 Jul 2016) Author's response Manuscript

ED: Referee Nomination & Report Request started (18 Jul 2016) by Hailong Wang

RR by Anonymous Referee #1 (08 Aug 2016)

Suggestions for revision or reasons for rejection

Review of Jung et al. “Precipitation Susceptibility in Marine Stratocumulus and Shallow Cumulus from Airborne Measurements”

The authors have generally addressed my major concerns with the paper. In particular, the authors have addressed the issue of data independence and demonstrated that their general conclusions remain unchanged. The authors have also shown that H and Nd are not correlated at the smaller spatial scales and are unlikely to affect the susceptibilities. There are still a couple minor instances where explanations are unclear or need some elaboration. Therefore, I recommend publication after these minor and technical comments have been addressed.

Minor comment

1) I do not quite understand the physical underpinning behind why the susceptibility should behave as they do, and I would like the authors to briefly address this. The three regimes of different process rates are used to explain the behavior of the susceptibility, and it is argued that at low LWP, not enough water is available to initiate rain. Indeed, the authors show that at low H, the susceptibility in many of the cases is indistinguishable from zero. Based on the measurements presented in this study, however, clouds with small H do appear to precipitate slightly (> 0.01 mm d-1), which suggests that autoconversion process is active in clouds with small H. Should we not then expect these clouds to have a susceptibility greater than zero? Are clouds with R~0.01 mm d-1 not considered to be precipitating? Or are other factors, which appear as noise in the relationship, making it difficult to discern a relationship?

Technical issues

P3 L31-32: “the interrelationships examined are representative of GCM spatial resolution” – it is not clear what is meant here. Yes, the area covered by the field campaign are on the order of a GCM grid box, but the susceptibilities are calculated based on variations at much smaller spatial scales, which the GCM will not be able to resolve.
P10 L25: Missing period between “accretion)” and “Here,”
P10 L29: Suggest inserting comma between “S0)” and “the accretion”

Table A1: It is my understanding that the correlations and P-values are calculated on the 1-sec data. Is this the case? If so, P-values are only meaningful when the data are all independent. So the correlations and the P-values should be calculated on the averaged data, there were averaged based on the e-folding timescale.

Figure B2: Based on how little the susceptibility changed from no-threshold to R>0.1 mm d-1 threshold. Can’t one infer that the threshold is not likely to be the reason behind the difference between the VOCALS data in this study and in Terai et al. (2012)?

Figure 11: In the text, it is incorrectly referenced as Fig. 7a. And in Fig. 11b and 11c, wouldn’t scavenging of aerosols lead to a change in Nd, rather than in R as the arrows indicate?

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RR by Anonymous Referee #3 (17 Aug 2016)

Suggestions for revision or reasons for rejection

I think the authors have done a nice job on addressing comments from two reviewers. Here I have some further comments for authors to consider:

Page 2, Lines 7-8: The difference of Si and S0 noted here is confusing and may not be correct. My understanding S0 is calculated for clouds that are precipitating. If a cloud does not precipitate, R is 0 and you can not calculate S0 (remember it is ln(R) is used in Eq. (1)). So it is confusing to see the statement of “SI is equivalent to S0 only when 100% of the sampled clouds are precipitating”. The only difference here is how large a threshold of rainrate is applied for calculating S0 or SI (They are completely equivalent).

Page 2, Lines 16-17, and Eq .(2): “When GCMs consider aerosols, the rainrate R is often parameterized in terms of LWP and Nd as Eq. (2). …”. This statement is inaccurate. Rainrate from liquid clouds are usually from two terms, one is autoconverion and the other is from accretion. The autoconversion term is typically parameterized using Eq. (2), but not for accretion. So this needs to be clarified here.

Page 2, Line 21: “S0 in Eq. (1) is equivalent to the exponent beta in eq. (2) at fixed LWP”. This statement is incorrect. As I note in my comments above, rainrate comes from two parts, one is from autoconverion and the other is from accretion. But beta in eq. (2) is for autoconversion. In S0, it includes contributions from both autoconverion and accretion. So only in the case where accretion has little contribution to rainrate, S0 may then be equal to beta.

Page 7, Line 22-23: Again, the statement ‘The low R threshold is intended to include both non-precipitating and precipitating clouds’ is confusing. I do not think non-precipitating clouds can be included by using a low R threshold. You will have to choose clouds with a certain R threshold. Even though this threshold can be very low, there are still clouds that are not included. Also, as a threshold of 0.001 mm/day is really low here, I wonder what is the uncertainty in your rainrate calculation. How this might affect the retrieval of rainrate that is low.

Page 8, Line 16: “one LWP value for the entire cloud layer on a given day”. This is not clear to me. Please clarify.

Page 9, e-folding time. The authors cited Leith (1973) for e-folding time. Please elaborate here what is the e-folding time in this context and how this is calculated, so readers may not have to refer back to Leith (1973) understanding this.

Page 12, line 16: Again, I think it is not appropriate to use “non-precipitating” here.

Page 14, line 7-8: the comparison between S0 and beta. As I noted above, S0 and beta are not the same thing, and you can not directly relate S0 with beta here. So the statement here is not supported.

Two missing references: Hill et al. (2015) and Wang et al. (2012)

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ED: Reconsider after minor revisions (Editor review) (17 Aug 2016) by Hailong Wang

AR by EUNSIL JUNG on behalf of the Authors (27 Aug 2016) Author's response Manuscript

ED: Publish as is (30 Aug 2016) by Hailong Wang

AR by EUNSIL JUNG on behalf of the Authors (01 Sep 2016) Author's response Manuscript

Short summary

We calculate the qualitative behavior of precipitation response to aerosol loadings with cloud depths for warm boundary layer clouds (stratocumulus and shallow marine cumulus), using aircraft measurements across four field campaigns. The finding shows that precipitation responds similarly to aerosol loadings for both stratocumulus and cumulus clouds, regardless of cloud type. Precipitation is most susceptible to aerosol perturbations in the medium–deep depth of clouds.