the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 26 Jun 2025
Evidence for the role of thermal and cloud merging in mesoscale convective organization
Abstract. Observations from airborne field campaigns are used to study the interplay between boundary-layer thermals and clouds in the trades. The size distributions of thermal and cloud-base chords inferred from turbulence and horizontal lidar-radar measurements are robustly described by the sum of two exponentials. Analytical calculations and statistical simulations demonstrate that the two exponentials result from objects merging, respectively representing the populations of merged- and unmerged-object chords. They also show how circulations induced by convective objects facilitate the merging process. The observed day-to-day variability of these populations at cloud base can thus be tied to the variability of thermal merging across the depth of the subcloud layer. Clouds rooted in unmerged thermals are small and shallow while those rooted in merged thermals are wider and deeper. An intricate interplay between thermal- and cloud-merging arises: when thermal merging is weak, thermal number density is high and cloud bases merge easily, leading to strong mesoscale mass fluxes and "Gravel" shallow mesoscale organizations. In contrast, when thermal merging is strong, clouds are fed by sparser but wider thermals, leading to longer cloud lifetimes but weaker cloud merging, weaker mesoscale mass fluxes, and "Flower" mesoscale organizations. This interplay between thermal- and cloud-merging imposes an upper bound on cloud coverage and suggests a negative feedback on the growth of mesoscale circulations. Thermal merging also controls observed size distributions of thermals in deep convective regimes. The merging process thus appears to be a fundamental player in the mesoscale organization of convection.
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Status: final response (author comments only)
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RC1: 'Comment on egusphere-2025-2839', Anonymous Referee #1, 17 Jul 2025
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2025/egusphere-2025-2839/egusphere-2025-2839-RC1-supplement.pdf
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RC2: 'Comment on egusphere-2025-2839', Anonymous Referee #2, 08 Aug 2025
Review for Bony et al. ACP 2025
Evidence for the role of thermal and cloud merging in mesoscale convective organization
Summary
In this study, the authors examine the behaviors of thermals, and the cumulus clouds they support in the trade-wind region. They use a combination of observations taken from multiple platforms during the EUREC4A campaign to examine the interplay between thermals and clouds. Specifically, they find that their size distribution can be explained by the sum of two exponentials which they further determine to be related to “merged” and “unmerged” object (i.e., cloud or thermal) populations. This theoretical framework describing the relationship between merged and unmerged populations controlling the total behavior of trade thermals and clouds comes from extensive analytical calculations that are further validated through comparison with a one-dimensional statistical model. The attraction between clouds due to their convective circulations, helping this merging to happen, is also mathematically detailed. Once tested, the authors show the strength of this merging population framework through interpreting the EUREC4A (and later the deeper convective MAESTRO) observations. They find that the behaviors can be described well as interactions between merged and unmerged populations of clouds and thermals. Such interactions appear to shape the characteristics of the mesoscale cloud patterns observed in the tropics (e.g., gravel vs. Flower behaviors) and set the upper bound on the amount of cloud cover, which has crucial implications for trade cumulus feedback.
This is an exceptionally well-crafted and thoughtful study, expertly grounded in the literature and employing a wealth of cutting-edge observations as well as classical theory and statistical models. The results have the potential to revolutionize how the field thinks about tropical cumulus clouds; their development from and interaction with thermals; and how this interplay shapes cloud organization and ultimately influences the climate. In particular, the detailed analytical calculations and elegant theoretical framework developed in this work is a significant step forward in describing how cumulus, and potentially deeper convective clouds, develop, organize, and persist. This will likely be a major contribution to the field, advancing the fundamental understanding of cloud behaviors with critical implications for how they will respond under future climates and how we can improve their representation in high resolution models. I have noted places where analysis details could be clarified and otherwise urge prompt publication of this excellent manuscript.
Detail Comments
General: Please provide R2 values for scatter plots and be consistent about using R2 throughout (later figures use R instead). Assume these are all Pearson (Line 443) correlations at 95% confidence? Worth mentioning that somewhere as well.
Main Text
Figure 2, 5: Following the Q-Q plot in Figure 1, please provide the R2 values for the individual flight fits.
Line 50: It might be worth noting that many clouds are not classified into any of these four patterns (e.g., Schulz 2022)
Line 132: What instrument are you getting the vertical velocity from? Apologies if I missed this in the methods.
Figure 4, Lines 159-161: It looks like the figure described in the text and the caption do not match the actual figure. However, it sounds like a very intriguing result, so please include.
Figure 5: It might be helpful to indicate the heights (or at least the dominant types of legs that were flown) in each flight. It could help to illustrate your point about change in exponential behavior with height (i.e., one to two populations).
Figure 6: Please describe in more detail what is being shown in the different panels in the text. I think I follow your logic, but it would help to have your reasoning more explicitly stated. Also please label the panels (a-c).
Line 193: Just to be clear, the betaD0L0 is the ratio to determine if there is merging?
Line 217-220: where are you looking in Figure 6? Would be helpful to describe in a bit more detail how you see this.
Line 224: I don’t understand how you got this result, could you please add a little more detail?
Line 232, eq. 9: Would you please explain how you get to this in more detail? And why you are using a Lambert W function here?
Line 234, eq. 10: How do you get to the L0=sqrt(L1L2) result here?
Line 259-261: Do you think the merging here is assisted by mesoscale circulations in the real world? E.g., Janssens et al. 2023, 2024
Line 268, Figure 7c: Please add the statistical comparison here, such as reporting the R2. It looks like theory is underpredicting the medium to larger sizes a bit. I would have thought it should be better at the larger sizes based on the assumptions, which focuses on capturing the behavior in the larger size tail (if I understood correctly). This is particularly true for the merged case. Is there a reason we would expect this disagreement?
Line 293-294: Please add R2 to know how much variance is explained with this linear proxy.
Line 296: Please report the R2 for this correlation
Figure 8: Please add R2 for all these plots. Is the dashed line in d the best fit line? Otherwise, it looks like the dashed lines are 1:1? Are the error bars here and throughout (e.g., Figure 11) for a single standard error (or deviation), so 68% confidence?
Figure 9, Lines 308-321: It would be helpful to provide a little more detail in how to interpret this figure. It looks like the caption is inconsistent with what is being shown as well, please clarify. Specifically, for 9a, LTH1 and LTH2 are mentioned but not shown and the colors are green and brown in the caption but gray in the figure.
Line 344-346: It’s exciting to have two observations of the mass flux to compare here. Would it be possible to show the scatter between Mb estimates from the two different methods in the appendix? Or at least report the R2? Both would be preferable if doable.
Figures 10 and 13: These are very helpful and elegant diagrams, please make sure to reference in the text somewhere and thank you for including.
Figure 11b: why are some of these scatter points in gray?
Line 346-348: Are you inferring this from comparing 11a to b? Might be helpful to color the points by Mb in 11b or something so it is more explicit.
Line 348-350: Are you referring to the weak positive relationship here? Would be helpful to add the R2
Line 356-357, 11b,d: Please consider adding the R2 here as there is a fair amount of variability in this relationship.
Line 363: Also, Janssens et al. 2024?
Line 368-369: This is quite an interesting hypothesis; I hope you pursue this idea further.
Line 390: Please indicate which panel in Figure 11 you are highlighting here.
Line 430-436: This is very interesting. Do you think that the merging helps to transition the organization types? i.e. from something short lived, like Sugar and Gravel, to something long lived like Flowers? This is what happens in Narenpitak et al. 2021 and you discussed seeing something similar between flights 15 and 16. Might be worth mentioning the Lagrangian evolution implications somewhere (if not already in the discussion).
Figure 14b: Please report R2 to be consistent.
Appendix A
Line 606-607: Is this consistent with the discussion in the main text of having the thermals merging closer to the cloud base and not at the surface? This would seem to merge at the base but still have separate updrafts aloft.
Line 627-628: I don’t understand what this is saying, please clarify
Supplemental Material
S11: Please explain why this is the “actual” coverage?
Section S2.1: I think I am missing the definition of P0 and P0eff that are used in these equations. I couldn’t find them here or in the main text, apologies. Would be very helpful to have explicitly stated somewhere to follow the substitutions made later in the calculations.
S13: Please explain how Pmerging becomes P0eff?
S16-20: Please share a little more detail in how you do this. I think it is the same strategy you apply later as well, right?
S22-S24: I don’t follow how S22 collapses into 23 and 24, please share a little more detail
Above S25, S65: It would be very helpful to discuss how you used homothety here and potentially include a diagram. I am not familiar with this technique, and it seems crucial for this calculation and how you connect it to the framework used for the observational analysis.
S27: Please clarify how you derive the density.
S28: Please say a little more about the “simple arithmetic calculations” here
S41: Please clarify how you get to this, it seems like we have lost some constants.
S60-62: Please clarify how you get these approximations.
Discussion of S69: Please consider including this figure showing the simulations match the equation well, would be very valuable to have. Maybe add in an appendix for the main text?
Typographical Comments
Main Text
Figures 4, 7d, 9a, 11a,c: The edge labels/legends have been cutoff for these.
Line 48: “(George et al., 2023)”
Line 69: “the HALO”
Line 101: “anomalies called thermals”
Caption for Figure 2: “shown on Fig. 1c” rather than 1a?
Line 204 and elsewhere: suggest saying “is written as” instead of “writes” for describing these equations.
Line 256-258: Suggest splitting into two sentences.
Figure 7: colors appear different between the caption and figure: blue > purple and red > pink
Figure 12: consider reordering panels so they are discussed in order in the text. Also, is the dashed line in b the critical merging efficiency?
Line 448: “Feb”
Appendix A
Line 629: “its”
Line 648: “as is the”
Supplemental Material
Above S5: “is” instead of “writes”
Above S57: only one “that”
Above S58: “updraft sizes to the”
Above S64: “to an”
Above S67: “L2 is not”
Below S67: “strong constraint”
Citation: https://doi.org/10.5194/egusphere-2025-2839-RC2
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