the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 05 Jan 2026
A Robust Aerosol Impact on Clouds Along the Subtropical to Tropical Transition
Abstract. Marine clouds undergo a transition from subtropical stratocumulus (Sc) to shallow cumulus (Cu) and eventually to deep convective (DC) systems as air masses progress from the subtropics towards the deep tropics. How aerosols modulate this Lagrangian cloud evolution remains largely uncertain. Using both 5-year long satellite observations mapped along 8-day Lagrangian trajectories and complementary large-eddy simulations from nine initiation locations across the Northeast Pacific, Southeast Pacific, and Southeast Atlantic. This framework allows us to quantify the aerosol effect and its co-variability with meteorological conditions on cloud microphysics, macrophysics, and top-of-atmosphere radiation through the full Sc-Cu-DC transition. This research reveals that increasing aerosol concentrations leads to deeper, and more reflective clouds throughout this cloud transition. Examining the thermodynamic evolution along the trajectory indicates a well-known trend: enhanced moistening near the boundary-layer top and lower free troposphere in polluted cases, suggesting that some of the co-variability between aerosol and meteorological conditions is internally driven. The agreement between model simulations and satellite data alongside the multi-basin coherence of the results indicates that aerosols systematically amplify cloud depth and reflectivity during the subtropical–to–tropical cloud transition.
Competing interests: At least one of the (co-)authors is a member of the editorial board of Atmospheric Chemistry and Physics.
Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this paper. While Copernicus Publications makes every effort to include appropriate place names, the final responsibility lies with the authors. Views expressed in the text are those of the authors and do not necessarily reflect the views of the publisher.- Preprint
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Status: open (until 01 Mar 2026)
- CC1: 'Comment on egusphere-2025-6481', Marcin J. Kurowski, 27 Jan 2026 reply
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RC1: 'Comment on egusphere-2025-6481', Anonymous Referee #1, 30 Jan 2026
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The manuscript explores aerosol effects along the stratocumulus to cumulus (Sc–Cu) transition and further downwind into deep cumulus convection in the tropics. The authors combine satellite observations, reanalysis data, Lagrangian trajectories, and large-eddy simulations. The results concerning the Sc–Cu transition are generally consistent with earlier work. The main contribution of this study is its extension toward the transition to deep convection and the suggestion that aerosols may affect thermodynamic properties along this evolution.
The extension of Lagrangian analyses into the deep convective regime is a potentially valuable direction, and the manuscript addresses an important question in this context. However, several aspects of the methodology raise concerns that may affect the strength of the conclusions regarding aerosol-driven thermodynamic feedbacks, particularly in distinguishing aerosol effects from aerosol–meteorology co-variability. Overall, the results are suggestive of a possible aerosol influence on thermodynamics, but stronger evidence would be needed to robustly support this interpretation.
In addition, the manuscript would benefit from improved writing, particularly in the organization and clarity of the methodology section. Below I provide detailed comments.
Major concerns
1. Simulations
The authors note that aerosol–meteorology co-variability may precondition the Sc–Cu–DC evolution, which is clearly evident, for example, in Figure 3. Several recent studies have emphasized that polluted and clean air masses often exhibit systematically different thermodynamic and meteorological properties, which complicates causal interpretation. Relevant literature on aerosol–meteorology co-variability should be more thoroughly discussed and cited (e.g., https://acp.copernicus.org/articles/25/3413/2025/ and https://doi.org/10.5194/acp-24-7331-2024).
To isolate aerosol effects while keeping meteorology fixed, the authors employ LES simulations. Figure 6 shows differences between polluted and clean simulations, but the description of the simulation methodology is unclear and raises concerns regarding the interpretation of these results. It is not clear whether the LES are intended to closely mimic the observed meteorological evolution along the trajectories or whether they represent semi-idealized simulations. While the authors state that simulations follow the trajectories, the description suggests a more idealized setup. This ambiguity is reinforced by the statement in the conclusions that the simulations rely on idealized setups with prescribed CCN perturbations.
Several key methodological details are insufficiently described:
Are the simulations nudged, and if so, how?
How do atmospheric profiles evolve during the simulations?
How are differences in temporal resolution between the LES and reanalysis data handled?
Aerosols are not prognostic in the simulations, which is a critical limitation given that the study focuses on aerosol–cloud interactions. This point requires deeper discussion regarding its implications.
The horizontal domain size (57.6 × 57.6 km) is marginal for resolving mesoscale cloud structures during the later stages of the Sc–Cu transition, and probably not sufficient to resolve deep convection. This concern is acknowledged by the authors themselves in the conclusions, where they state that the domain is not large enough to capture convective organization. This limitation weakens the interpretation of the simulated deep convective response and raises concerns regarding the conclusions.
2. Observations
Several issues arise in the satellite-based analysis. For example, Figure 4 shows droplet effective radius along the 8-day evolution. During days 6–8, clouds appear substantially deeper and likely include glaciated cloud tops. In such cases, MODIS liquid cloud retrievals such as re and LWP may not represent the deep convective clouds.
The authors choose AOD as the primary aerosol proxy, while acknowledging its limitations later in the manuscript. It is not clear why cloud droplet number concentration (Nd), which may be more directly related to CCN, was not considered more centrally. AOD is not available under cloudy conditions, especially over stratocumulus regions where cloud fraction is high, which adds further uncertainty. To address this, the authors use reanalysis AOD, which may introduce additional uncertainty beyond that of the AOD retrieval.
Furthermore, AOD is averaged along the entire trajectory. Why was aerosol loading at the initial day not used, as in previous studies? This relates directly to the unexplained increase in AOD after day 5 in Figure 2, which requires clarification.
Regarding MODIS observations, it should be clarified whether there are time periods without observations due to satellite overpass limitations and how this affects the daily averaging.
3. Trajectories
The choice of three initial trajectory points that are geographically very close requires justification. Given the scale of spatial meteorological variability, one would not expect substantial differences between such closely spaced points. The noisy results in Figure 5 across these points may introduce additional uncertainty that should be discussed.
4. Interpretation of the hermodynamic effects
One of the most interesting aspects of the manuscript is the suggestion that aerosols may actively modify thermodynamic profiles along the cloud transition, as discussed in Section 3.3 and illustrated in Figure 9. This interpretation is intriguing and consistent with mechanisms proposed in previous modeling studies. However, given the co-variability between aerosols and large-scale meteorological and thermodynamic conditions (see major comment 1), the current analysis does not yet unambiguously isolate an aerosol-driven thermodynamic effect.
While the consistency between observations and LES results is encouraging, the observational evidence alone cannot fully rule out the influence of pre-existing environmental differences, and the idealized nature of the simulations limits the strength of causal attribution. As a result, the conclusions regarding aerosol-induced thermodynamic feedbacks may benefit from a more cautious framing or from additional sensitivity analyses that further constrain the role of co-variability.
Minor comments
The manuscript provides very detailed figure-by-figure descriptions. In many cases, the figures can speak for themselves, and the text could focus more on interpreting the key results.
Line 120: The rationale for limiting SST variability is unclear and should be better explained.
Line 124: Is a precipitation threshold defined?
Line 203: Why is this procedure applied only to the polluted group?
Line 218: Clarify what is meant by “Differences will be mentioned.”
In figures such as Figure 3, consider using δ notation in parentheses for clarity.
Line 261: Missing citation of relevant recent studies (https://acp.copernicus.org/articles/25/3413/2025/ and https://doi.org/10.5194/acp-24-7331-2024).
Figures 5 and 8 are visually noisy. Consider improved visualization.
Figure 7: Differences between polluted and clean simulations are difficult to discern. Improved visualization would help.
Line 387: Clarify what is meant by “after accounting for SST differences.”
Lines 421–423: This statement is not fully supported by the presented results.
An AI assistance statement appears after line 210 and seems misplaced.
Citation: https://doi.org/10.5194/egusphere-2025-6481-RC1
Data sets
Dataset for the paper "A Robust Aerosol Impact on Clouds Along the Subtropical to Tropical Transition" by Yeheskel et al. Netta Yeheskel and Guy Dagan https://doi.org/10.5281/zenodo.18031100
Model code and software
System for Atmospheric Modeling Marat Khairoutdinov http://rossby.msrc.sunysb.edu/
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- 1
I encourage the authors to more thoroughly engage with the recent literature on the diurnal cycle of the Sc-to-Cu transition and the role of aerosols, including both observational and numerical studies:
Pugsley, E. Gryspeerdt, & V. Nair, Cloud fraction response to aerosol driven by nighttime processes, Proc. Natl. Acad. Sci. U.S.A.122 (47) e2509949122, (2025).
Li, J., Wang, Y., Li, J., Zhang, W., Zhang, L., and Wang, Y.: Strong aerosol indirect radiative effect from dynamic-driven diurnal variations of cloud water adjustments, Atmos. Chem. Phys., 25, 17455–17472, https://doi.org/10.5194/acp-25-17455-2025, 2025.
Kurowski, M. J., Lebsock, M. D., and Smalley, K. M.: The diurnal susceptibility of subtropical clouds to aerosols, Atmos. Chem. Phys., 25, 15329–15342, https://doi.org/10.5194/acp-25-15329-2025, 2025.
Smalley, K. M., Lebsock, M. D., & Eastman, R. (2024). Diurnal patterns in the observed cloud liquid water path response to droplet number perturbations. Geophysical Research Letters, 51, e2023GL107323.