|The main value of this work lies in the information offered from measurements of aerosol and cloud properties in fairly convective clouds in an interesting location. |
1) The main objective(s) of this paper are unclear:
a. The title indicates closure, but reasonable closure is not possible here for two reasons. One is that there are two measurements of cloud droplet number concentrations that are separated by 20-30% before considering the uncertainty in the measurements. The second reason is that there is no independent estimate of kappa. With the information presented, the model is incapable of producing closure because it is the comparison of the model and observations that is used to estimate the best kappa. This implicitly assumes that the other observations are correct, but we know that is not the case because the two Nd measurements disagree. I am not being critical of the Nd measurements: I applaud the authors for including both. My suggestion is to take your best case, in terms of measured quantities, including information available to define kappa, and attempt closure of the model with the two measurements of Nd. Your best case might be the simplest, and the one that has the best estimate of updraft speed or w; more discussion of w later. The objective of this best case would be to be able to say something about how the two measurements relate to the modelled Nd.
b. In the abstract and later in the text, there is considerable discussion of the best kappa value. I don’t see this as a major objective of this paper. There are better ways to estimate kappa, which the authors refer to, than to use such a convoluted approach that incudes uncertainties. Use estimates of kappa from previous studies in the region.
c. The last sentence of the abstract says that “Our results indicate that Aitken mode particles and their hygroscopicity can be important for droplet formation at low pollution levels and high updraft velocities in tropical convective clouds.” This seems like a result worthy of publication, if the authors first acknowledge previous related work: Leaitch, W. R. et al., Effects of 20–100 nm particles on liquid clouds in the clean summertime Arctic, Atmos. Chem. Phys. 16, 11107–11124 (2016); Baccarini et al., Frequent new particle formation over the high Arctic pack ice by enhanced iodine emissions, Nature Comm. https://doi.org/10.1038/s41467-020-18551-0, 2020.
d. The last sentence of Section 1 tells us that the modelling is used to examine the sensitivities of Nd to kappa, Na and w, but we’ve been subjected to such sensitivity studies for many years now, dating back to at least 1971 (Junge and McLaren, JAS, 1971), which told us that the number distribution was more important than the chemical content of the particles. Why is another sensitivity study of this important?
2) Lines 42-50: Leaitch et al., Cloud albedo increase from carbonaceous aerosol, Atmos. Chem. Phys., 10, 7669-7684, 2010 is relevant here.
3) Line 93 – What is the Aerosol Measurement System, and why do we need to know its acronym?
4) Lines 104-106 – Your inferred Aitken distribution has a minimum at about 80 nm, based on the Wex, Gong and Quinn distributions. The below-cloud distributions measured over the North Atlantic Ocean by Leaitch et al. (ACP, 2010), also used in parcel model calculations, had minima at about 100 nm. Such a minimum might make a substantial difference in your results, for example, potentially requiring a smaller kappa for the Aitken mode.
5) Lines 118-126 – Are the differences in the sampling approach by the CAS and CCP potentially responsible for the bias in the two measurements?
6) Lines 131-133 – Given the better agreement with the King probe, why were the CAS measurements not chosen to compare to the model alone? Were number or sizing differences mostly responsible for the differences between the CAS and CCP probe comparisons with the King probe?
7) Section 3.1 –
a) It would be helpful to have an example of the time series of Nd and w during a cloud penetration to demonstrate the application of this approach here. By design, the PMM analysis appears to ensure the connection between Nd and w shown in Figures 3 and 4, whereas other methods, such as Peng that you later refer to as weaker (Lines 339-345), do not. Because of the apparent forced dependence by the PMM method, it seems inappropriate to use this approach to make conclusive statements about the dependence of Nd on w.
b) The Peng approach, and perhaps others, were developed for stratus and stratocumulus with relatively low updraft speeds. The pathways of air parcels through such clouds, as shown by modelling studies (e.g., at CSU), are much different than for more convective clouds, and therefore the Peng approach may not be appropriate here in any case. For strong convection, the w may significantly increase with height above cloud base. How do you know that your w, measured more than 20 metres above base, were indeed representative of the w at cloud base? The Nd may not change much with height (assuming only homogeneous entrainment), but the w can, and based on the LWC shown in Figure 2 sampling was conducted well above cloud base in many cases, which would lead to overestimating w in some cases.
8) Line 190 – Unless there is some inhomogeneous mixing.
9) Lines 207-208 - Curious statement: effectively, you are saying that variations in Nd of 20-40% aren't large enough to worry about. Is that the status of the indirect effects?
10) Lines 209-211 - This statement is predicated on the correct answer lying between the two measurements, yet there is nothing in the paper to suggest that is correct.
11) Lines 219-220 – “Confirm” is an exaggeration. It could be true, but you haven’t demonstrated this, and there are better ways to estimate kappa. This approach is too uncertain.
12) Lines 222-225 – If you sampled very near cloud base, then it would seem difficult for entrainment to increase the Nd. Again, it is important to illustrate your in-cloud selection process. If you sampled too high above cloud base, then you need to question your estimate of w. Also, your statement here is incorrect if the CCP measurements of Nd are closest to reality. Overall, I don’t find this paragraph useful.
13) Lines 231-235 – When you say the hygroscopicity of particles could change due to dissolution of soluble compounds, do you mean the uptake of highly soluble gases, such as HNO3? If so, a reference is in order: Kulmala et al., maybe JGR, in the 1990s. If you are talking about delays associated with weakly soluble compounds, then Shantz et al.: Effect of organics of low solubility on the growth rate of cloud droplets, J. Geophys. Res., 108, 4168-4177, 2003 is appropriate here and on line 405. Your assumption that reduced solubility might flatten the curves more may or may not be correct, depending on the entire chemical composition of the size distribution. Shantz et al found that delayed growth reduced the Nd relative to a highly soluble compound. I don’t see enough support for your statement that “such composition effects can likely be excluded.”
14) Lines 236-237 – Yet, your Aitken mode is highly soluble.
15) Lines 338-247 – Again, I suggest that your tendency of measured Nd vs w is at least in part a result of your approach.
16) Line 274 – Nd to Na?
17) Lines 350-353 – “we conclude that the sensitivity of Nd to Na is much greater than that to w under these conditions which is also reflected by the rather small increase in Nd with w at high updraft velocities”. Again, we need to know where with respect to cloud base that the w were measured, in case some of your w are overestimated.