Please see my comments in the attachment.

The manuscript “Measurement Report: Cloud and environmental properties associated with aggregated shallow marine cumulus and cumulus congestus” by Crosbie et al provides an insight into the measurements of six case-studies during the ACTIVATE field campaign from 2020 to 2022, and thereby aims to characterize the cloudiness and its environment by means of their thermodynamic, kinematic and microphysical properties. The measurements (supplemented by some reanalyses) are from two aircraft – a King Air primarily taking on the remote-sensing responsibilities with dropsondes and a Falcon jet flying in and out of clouds to get in-situ measurements. The value of the coordinated strategy of these flights is reflected in the possible synergies of the measurements that are highlighted here in various aspects. The manuscript effectively describes the cloud and environmental quantities of the six case-studies and can be a great starting point for subsequent investigations that wish to go in to much greater depth in understanding processes that link marine clouds and their environment.

I found the manuscript well-written, aptly structured, and clear in its presentation almost everywhere except for the quality of the figures. Here, I list some general comments (mostly minor) that I believe can add value to the existing state of the manuscript and request clarifications on some aspects.

General comments

1. Motivation for the observations: The current introduction is comprehensive and presents the complexity in processes with respect to scales and quantities. However, it leaves me hanging without a more direct link (or more specific questions) from the processes to the observations being discussed here. Are there observational challenges that have restricted us from getting a better picture? The manuscript needs to motivate the reader as to which are the unobserved processes, quantities or hitherto missed synergies that are accomplished here which will help answer specific questions of mesoscale aggregation that the introduction section raises. These observational "gaps" in the context of the mentioned process-understanding problems will motivate why such a synergy of two aircraft spanning in-situ and remote-sensing measurements is valuable and which strategies and measurements will subsequently help in improving the current state of process understanding.
2. In Section-7, there is not much mention about how these quantities are associated with the cloud processes, e.g. their lifecycle stage and other properties such as ql, Nd, etc, except a brief mention in L712-713. I realise it is out of the scope of this paper to characterize the subprocesses of the cases in detail, but in its current state, the section seems isolated from the discussions in the previous sections. If the authors could outline (or hypothesize) how these quantities might be related physically (or which physical sub-processes might be dominant so as to show such measurements), that would be quite useful for any subsequent investigations that will use these data. I see these have been sparsely mentioned in the conclusion, but some details in Section-7 would be good.
3. The study does not make any connections to similar measurements in existing literature or similar studies from other recent campaigns* in the region. It would be good to point out which aspects of shallow convection previously observed were confirmed by these case-studies, and/or what was new in these ACTIVATE cases. For example, the statements in L324 and L362 about moisture and stability is similar to observed case-studies from the NARVAL2 campaign. Connect these observations with similar strategies such as in the EUREC4A campaign, where the core measurement strategy also involved one aircraft (mainly remote sensing) above and another below (mainly in-situ).
4. Related to the point above, it feels like a missed opportunity with so many dropsonde launches that no estimation of the area-averaged measurements such as vertical velocity (W) first shown by Bony and Stevens (2019) and carried out extensively in campaigns such as EUREC4A and OTREC. This measurement provides a very important characterization of the environment. Although the spatial scale and time-advection would be different for these 6 case-studies, it provides more data points to compare with efforts of other cloud-organization studies that have shown W to be an important environmental factor (e.g. recently by Vogel et al, 2022)

* Examples of process case-studies in other campaigns:

• OTREC (Raymond, D. J., & Fuchs-Stone, Ž. (2021). Emergent properties of convection in OTREC and PREDICT. Journal of Geophysical Research: Atmospheres, 126, e2020JD033585. https://doi.org/10.1029/2020JD033585)
• NARVAL2 (George, G., B. Stevens, S. Bony, M. Klingebiel, and R. Vogel, 2021: Observed Impact of Mesoscale Vertical Motion on Cloudiness. J. Atmos. Sci., 78, 2413–2427, https://doi.org/10.1175/JAS-D-20-0335.1.)
• EUREC4A (Touzé-Peiffer, L., R. Vogel, and N. Rochetin, 2022: Cold Pools Observed during EUREC4A: Detection and Characterization from Atmospheric Soundings. J. Appl. Meteor. Climatol., 61, 593–610, https://doi.org/10.1175/JAMC-D-21-0048.1.)

Specific comments / clarifications

• All figures: Please vectorize for better quality and accessibility while zooming in.
• Make Section-2 title more suited to the study, e.g. “Measurement strategies and Data”
• In Section-3, mention the differences in the diel placement of the sampling between the 6 cases. From Table-1, it seems like Cases 1 & 6 (~15-16 UTC) are at a similar timeframe while the rest are all at another but not too varying timeframe (1830 - 2000 UTC). It's good to mention the sampling time difference among the cases, and if any quantities showed expected/unexpected deviations from the diel cycle of convection (e.g. Vial et al, 2019).
• L285-286: It is not clear how the cloud features were selected and how far in advance was this selection made. This would also clarify what "by design" means.
• L302: why not Case-3 (6.7 h)?
• L350: You could point to existing literature, where Mieslinger et al 2022 show the sensitivity of lidars can capture optically thin clouds that are often missed by coarse-resolution satellites.
• L351: Were there any large variabilities among the dropsonde profiles of a single case? e.g. due to cold-pools such as what Touzé-Peiffer et al, 2022 show? Also in L366: Are there variabilities among dropsondes in stability for launches within cloudy and clear areas?
• L400-403: This could have been interesting to see from the perspective of area-averaged W (mentioned in general comment-4)
• L448: Doesn't this counter the statement made in L442 that mean Nd does not change over the lifecycle?
• L470: It isn't clear why data should coalesce around (1,1) especially if most points are away from the adiabat.
• L670-673: How does this reconcile with the increased presence of the ammonium ion in AMS mass concentration? Did they not react with sea-salt much in Case-1? Or did they come in from upper layers seeing as it seems fairly top-heavy in Case-1 compared to the well-distributed Cases-2 and 3?
• L688: Please specify what ranges the Aitken and accumulation modes usually occupy and their relative importance in cloud processes.
• L784: How does the cloud situation compare with other studies that have looked at cases with Saharan dust in the environments (e.g. Gutleben et al, 2019)?
• Figure-2: Difficult to distinguish the different contour lines. Could the plot be made clearer somehow? Or the caption more detailed?
• Figure 3d: Please consider changing the color. It is tough to see between the clouds and pink line that there is an "x" there.
• Figure-5: How is the principal axis determined? Is it an approximation of the cloud cluster object to an ellipse? If so, how is the object defined?