Warm-phase Microphysical Evolution in Large Eddy Simulations of Tropical Cumulus Congestus: Constraining Drop Size Distribution Evolution using Polarimetery Retrievals and a Thermal-Based Framework

Stanford, McKenna; Fridlind, Ann; Ackerman, Andrew; van Diedenhoven, Bastiaan; Xiao, Qian; Wang, Jian; Matsui, Toshihisa; Hernandez-Deckers, Daniel; Lawson, Paul

doi:https://doi.org/10.5194/egusphere-2024-2413

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https://doi.org/10.5194/egusphere-2024-2413

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05 Aug 2024

| 05 Aug 2024

Warm-phase Microphysical Evolution in Large Eddy Simulations of Tropical Cumulus Congestus: Constraining Drop Size Distribution Evolution using Polarimetery Retrievals and a Thermal-Based Framework

McKenna Stanford, Ann Fridlind, Andrew Ackerman, Bastiaan van Diedenhoven, Qian Xiao, Jian Wang, Toshihisa Matsui, Daniel Hernandez-Deckers, and Paul Lawson

Abstract. Improving parameterizations of convective microphysics in Earth system models (ESMs) requires well-constrained cases suitable for scaling between cloud-resolving models and ESMs. We propose a benchmark large eddy simulation (LES) cumulus congestus case study from the NASA Cloud, Aerosol, and Monsoon Processes Philippines Experiment (CAMP²Ex) and demonstrate its observational constraints using novel polarimetric retrievals and in situ cloud microphysics measurements. Simulations using bulk and bin microphysics with observed aerosol input are compared to cloud-top retrievals of cloud droplet effective radius (R_eff) and number concentration (N_d) from the airborne Research Scanning Polarimeter (RSP). The bulk scheme reasonably reproduces characteristic profiles of cloud-top N_d that decrease with altitude, while the bin simulation realizes greater discrepancies due to weaker precipitation formation. The N_d profile is strongly sensitive to the collision-coalescence process and the vertically resolved aerosol distribution, but appears well-constrained, whereas a persistent low-bias in R_eff is evident in both schemes. Comparison of simulated and in situ droplet size distributions (DSDs) show that low-biased R_eff originates from a cloud droplet mode that is too narrow relative to observations. Finally, a thermal-tracking framework demonstrates that the dilution of N_d throughout a thermal's lifetime is heavily determined by collision-coalescence and the height-varying aerosol distribution, and that in the absence of these, the impact of entrainment on diluting N_d is largely offset by continuous aerosol activation. Implications for developing warm-phase convective microphysics schemes for ESMs, evaluation of cumulus congestus using single column model versions of ESMs, and translating results to global, space-based polarimetry platforms are discussed.

Received: 31 Jul 2024 – Discussion started: 05 Aug 2024

Competing interests: At least one of the (co-)authors is a member of the editorial board of Atmospheric Chemistry and Physics. The peer-review process was guided by an independent editor, and the authors also have no other competing interests to declare.

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Journal article(s) based on this preprint

25 Sep 2025

Warm-phase microphysical evolution in large-eddy simulations of tropical cumulus congestus: evaluating drop size distribution evolution using polarimetry retrievals, in situ measurements, and a thermal-based framework

McKenna W. Stanford, Ann M. Fridlind, Andrew S. Ackerman, Bastiaan van Diedenhoven, Qian Xiao, Jian Wang, Toshihisa Matsui, Daniel Hernandez-Deckers, and Paul Lawson

Atmos. Chem. Phys., 25, 11199–11231, https://doi.org/10.5194/acp-25-11199-2025,https://doi.org/10.5194/acp-25-11199-2025, 2025

Short summary

McKenna Stanford, Ann Fridlind, Andrew Ackerman, Bastiaan van Diedenhoven, Qian Xiao, Jian Wang, Toshihisa Matsui, Daniel Hernandez-Deckers, and Paul Lawson

Interactive discussion

Status: closed

RC1: 'Comment on egusphere-2024-2413', Anonymous Referee #1, 06 Sep 2024

Review
Included here are the more substantial and/or longer comments (i.e., notes, rather than comments, from the attached manuscript file). Grammatical corrections and suggested wording for clarity are included as annotations on the attached manuscript file, but not here. Only the yellow highlighted text and red comments need be addressed directly from the manuscript file. The associated line numbers of those comments are listed at the end of this document.
General comments:
The subject of this study is microphysics in tropical cumulus congestus, with a focus on the number concentration and effective radius of cloud droplets near cloud or thermal tops. Retrievals of these quantities at/near cloud top obtained from the airborne Research Scanning Polarimeter (RSP). These were compared to analogous quantities from a set of simulations with bulk 2-moment microphysics and with bin microphysics. In-situ measurements of the DSDs were also compared with simulated DSDs. In addition, a thermal-tracking analysis method was also used to gain insight into the evoluation of microphysical quantities in thermals, and how it varies with microphysics.
The manuscript is generally well written, well organized, and contains excellent graphics. Only minor revisions are recommended.

The more substantial and/or longer (but still minor) comments:
1. line 149: why is k needed if Reff and veff are both retrieved? Do you want k to relate Rv to Reff?
2. lines 420-21: It is not clear how this works; explain. Do you mean to say: weak pcp production allows cloud droplets to accumulate in an outflow layer?
3. lines 455-58. An alternative conclusion: dynamics matters, but its effects are accumulated or averaged. Drops are a product of their histories not their instantaneous environment.
4. lines 516-17: Fallout of rain would not affect supersaturation, right? But rain is a sink of Nc so increase of Nc due to activation is not clearly evident in presence of rain.
5. section 4.5: Where in a cloud (relative to the current cloud top) is a thermal typically located? At cloud top?
6. Fig. 13 might be less cluttered if streamlines were shown in a separate row, and omitted otherwise
7. Figure 15: Because thermals presumably entrain at different fractional rates, I would expect the variability about the means plotted in Fig. 15 to be large. I recommend giving the reader some idea of the variability among thermals by adding shaded error bars to these plots, for the CNTL and FIXED_AERO_NO_AC profiles.
Ideally, one would stratify the thermal-tracking analysis by fractional entrainment rate. What is plotted in Figure 15 is what a bulk cumulus parameterization would be asked to predict, as opposed to one based on thermals with different fractional rates, such as Arakawa and Schubert (1974), and examined in terms of parcels with different entrainment rates by Lin and Arakawa (1997, Part 2) (https://doi.org/10.1175/1520-0469(1997)054%3C1044:TMEPOS%3E2.0.CO;2).
I recommend making the suggested change to Figure 15 and to add a discussion of what is plotted in terms of a bulk model vs a 'spectral' model.
8. lines 535-36: It must be activation of newly entrained CCN. The concentration of CCN from cloud base will be diluted by entrainment, and these CCN alone cannot maintain a constant Nc (per unit mass) with z.
9. lines 537-38: Define secondary activation. If this means activation of

newly entrained CCN, then this hypothesis is the same as the first hypothesis. If it means reactivation of CCN from lower levels (i.e., not entrained at the current level), then it cannot offset entrainment dilution.
10. Section 5.1: This short review of convective microphysics in large scale models may be useful to some readers. However, there are no specific recommendations. It could, and perhaps should, be omitted in the interests of reducing the length of the manuscript.
If you do retain this subsection you may want to point out that adding complexity to convective microphysics schemes usually entails tuning of the microphysical parameters, in particular, rates of conversion to precipitation, rather than using results from cloud resolving models.
Are you aware of any convection microphysics schemes that are aerosol or CDNC aware?
11. lines 565-566: Explain/justify/revise this statement.
Condensed water amount is almost entirely a function of altitude not updraft speed. That is why updraft mass flux is generally sufficient to predict the large-scale convective condensation rate rather than requiring vertical velocity and updraft fractional area separately.
12. lines 569-581: Before such details as you discuss in this paragraph are included convective microphysics schemes, we may be using convection-permitting models.
13. Lines 582-591: Perhaps this paragraph should be moved to some other section because the topic seems to differ from that in the rest of the paragraph.
14. Section 5.2 heading: "Training" sounds like ML. Is that intended? If not, then perhaps you could use ‘Evaluation and improvement' which is of course what training is, but doesn't sound like ML.

Other comments: (see annotatations in manuscript file)
Lines 69, 80, 116, 123, 127, Eq. 2, 145, 157, 211, 221, 254, 282-284, 291,

343, 361-362, 379, 396, 399 (3 comments), 412, 419, 420, 425, 429, 460, 497, 498, 500, 504, Figure 13 caption, 521, 560-561, 565, 568, 636 (2), 642, 643, 645 (2), 650, 653-654, 664, 667, 674

Citation: https://doi.org/10.5194/egusphere-2024-2413-RC1
RC2: 'Comment on egusphere-2024-2413', Anonymous Referee #2, 30 Sep 2024

The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-2413/egusphere-2024-2413-RC2-supplement.pdf

Citation: https://doi.org/10.5194/egusphere-2024-2413-RC2
AC1: 'Comment on egusphere-2024-2413', McKenna Stanford, 20 Jan 2025

Please find our response to both reviewers in the attached document.

Citation: https://doi.org/10.5194/egusphere-2024-2413-AC1

Interactive discussion

Status: closed

RC1: 'Comment on egusphere-2024-2413', Anonymous Referee #1, 06 Sep 2024

Review
Included here are the more substantial and/or longer comments (i.e., notes, rather than comments, from the attached manuscript file). Grammatical corrections and suggested wording for clarity are included as annotations on the attached manuscript file, but not here. Only the yellow highlighted text and red comments need be addressed directly from the manuscript file. The associated line numbers of those comments are listed at the end of this document.
General comments:
The subject of this study is microphysics in tropical cumulus congestus, with a focus on the number concentration and effective radius of cloud droplets near cloud or thermal tops. Retrievals of these quantities at/near cloud top obtained from the airborne Research Scanning Polarimeter (RSP). These were compared to analogous quantities from a set of simulations with bulk 2-moment microphysics and with bin microphysics. In-situ measurements of the DSDs were also compared with simulated DSDs. In addition, a thermal-tracking analysis method was also used to gain insight into the evoluation of microphysical quantities in thermals, and how it varies with microphysics.
The manuscript is generally well written, well organized, and contains excellent graphics. Only minor revisions are recommended.

The more substantial and/or longer (but still minor) comments:
1. line 149: why is k needed if Reff and veff are both retrieved? Do you want k to relate Rv to Reff?
2. lines 420-21: It is not clear how this works; explain. Do you mean to say: weak pcp production allows cloud droplets to accumulate in an outflow layer?
3. lines 455-58. An alternative conclusion: dynamics matters, but its effects are accumulated or averaged. Drops are a product of their histories not their instantaneous environment.
4. lines 516-17: Fallout of rain would not affect supersaturation, right? But rain is a sink of Nc so increase of Nc due to activation is not clearly evident in presence of rain.
5. section 4.5: Where in a cloud (relative to the current cloud top) is a thermal typically located? At cloud top?
6. Fig. 13 might be less cluttered if streamlines were shown in a separate row, and omitted otherwise
7. Figure 15: Because thermals presumably entrain at different fractional rates, I would expect the variability about the means plotted in Fig. 15 to be large. I recommend giving the reader some idea of the variability among thermals by adding shaded error bars to these plots, for the CNTL and FIXED_AERO_NO_AC profiles.
Ideally, one would stratify the thermal-tracking analysis by fractional entrainment rate. What is plotted in Figure 15 is what a bulk cumulus parameterization would be asked to predict, as opposed to one based on thermals with different fractional rates, such as Arakawa and Schubert (1974), and examined in terms of parcels with different entrainment rates by Lin and Arakawa (1997, Part 2) (https://doi.org/10.1175/1520-0469(1997)054%3C1044:TMEPOS%3E2.0.CO;2).
I recommend making the suggested change to Figure 15 and to add a discussion of what is plotted in terms of a bulk model vs a 'spectral' model.
8. lines 535-36: It must be activation of newly entrained CCN. The concentration of CCN from cloud base will be diluted by entrainment, and these CCN alone cannot maintain a constant Nc (per unit mass) with z.
9. lines 537-38: Define secondary activation. If this means activation of

newly entrained CCN, then this hypothesis is the same as the first hypothesis. If it means reactivation of CCN from lower levels (i.e., not entrained at the current level), then it cannot offset entrainment dilution.
10. Section 5.1: This short review of convective microphysics in large scale models may be useful to some readers. However, there are no specific recommendations. It could, and perhaps should, be omitted in the interests of reducing the length of the manuscript.
If you do retain this subsection you may want to point out that adding complexity to convective microphysics schemes usually entails tuning of the microphysical parameters, in particular, rates of conversion to precipitation, rather than using results from cloud resolving models.
Are you aware of any convection microphysics schemes that are aerosol or CDNC aware?
11. lines 565-566: Explain/justify/revise this statement.
Condensed water amount is almost entirely a function of altitude not updraft speed. That is why updraft mass flux is generally sufficient to predict the large-scale convective condensation rate rather than requiring vertical velocity and updraft fractional area separately.
12. lines 569-581: Before such details as you discuss in this paragraph are included convective microphysics schemes, we may be using convection-permitting models.
13. Lines 582-591: Perhaps this paragraph should be moved to some other section because the topic seems to differ from that in the rest of the paragraph.
14. Section 5.2 heading: "Training" sounds like ML. Is that intended? If not, then perhaps you could use ‘Evaluation and improvement' which is of course what training is, but doesn't sound like ML.

Other comments: (see annotatations in manuscript file)
Lines 69, 80, 116, 123, 127, Eq. 2, 145, 157, 211, 221, 254, 282-284, 291,

343, 361-362, 379, 396, 399 (3 comments), 412, 419, 420, 425, 429, 460, 497, 498, 500, 504, Figure 13 caption, 521, 560-561, 565, 568, 636 (2), 642, 643, 645 (2), 650, 653-654, 664, 667, 674

Citation: https://doi.org/10.5194/egusphere-2024-2413-RC1
RC2: 'Comment on egusphere-2024-2413', Anonymous Referee #2, 30 Sep 2024

The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-2413/egusphere-2024-2413-RC2-supplement.pdf

Citation: https://doi.org/10.5194/egusphere-2024-2413-RC2
AC1: 'Comment on egusphere-2024-2413', McKenna Stanford, 20 Jan 2025

Please find our response to both reviewers in the attached document.

Citation: https://doi.org/10.5194/egusphere-2024-2413-AC1

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload

AR by McKenna Stanford on behalf of the Authors (20 Jan 2025) Author's response Author's tracked changes Manuscript

ED: Referee Nomination & Report Request started (27 Jan 2025) by Raphaela Vogel

RR by Anonymous Referee #2 (20 Mar 2025)

RR by Anonymous Referee #3 (12 Jun 2025)

Suggestions for revision or reasons for rejection

The authors present in this paper observations of microphysical properties (droplet size, concentration and DSD shape) in tropical cumulus congestus obtained at cloud top with the Research Scanning Polarimeter (RSP), and in-cloud with the fast forward-scattering spectrometer probe (FFSSP) obtained during the CAMP2Ex experiment. They compare these to a set of large-eddy simulations varying different properties of the microphysical scheme (bulk vs bin microphysics, different bulk schemes, turbulence, and aerosol profile). Thermals were also tracked in the LES to follow how microphysical properties evolve over time.

The paper reads well, the figures are clear and the authors discuss very well the limitations and difficulties of constraining the case they present. I believe the paper to be worthy of publication in ACP.

My only comment would be regarding nu_eff in the simulations: is it actually measuring the broadness of the distribution, or is it measuring its bimodality? Looking at Fig. 9-10, nu_eff has a plateau around 10-100 μm, where it is measuring the broadness of the cloud mode. It rapidly increases near the second mode – the vertical axis is cut off early, but my guess is that it plateaus again after the integral upper bound has passed most of the rain peak, and nu_eff then measures the broadness of the entire DSD. In that regard, I don’t think LES values of nu_eff outside of the first or the second plateau are particularly meaningful: they simply measure the presence of a second mode in the DSD relative to an arbitrary size of 100 μm (or 50 μm, as the authors underline). My question would be then: how does this work for the RSP? Since the values reported on Fig. 7 e-f are all below ~0.3, is it much less sensitive to the presence of that peak? I believe some discussion on that would help better understand the apparent discrepancy between measurements and simulations.

Hide

ED: Publish subject to minor revisions (review by editor) (13 Jun 2025) by Raphaela Vogel

AR by McKenna Stanford on behalf of the Authors (26 Jun 2025) Author's response Author's tracked changes Manuscript

ED: Publish as is (02 Jul 2025) by Raphaela Vogel

AR by McKenna Stanford on behalf of the Authors (15 Jul 2025) Manuscript

Journal article(s) based on this preprint

25 Sep 2025

McKenna W. Stanford, Ann M. Fridlind, Andrew S. Ackerman, Bastiaan van Diedenhoven, Qian Xiao, Jian Wang, Toshihisa Matsui, Daniel Hernandez-Deckers, and Paul Lawson

Atmos. Chem. Phys., 25, 11199–11231, https://doi.org/10.5194/acp-25-11199-2025,https://doi.org/10.5194/acp-25-11199-2025, 2025

Short summary

McKenna Stanford, Ann Fridlind, Andrew Ackerman, Bastiaan van Diedenhoven, Qian Xiao, Jian Wang, Toshihisa Matsui, Daniel Hernandez-Deckers, and Paul Lawson

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The evolution of cloud droplets, from the point they are activated by atmospheric aerosol to the formation of precipitation, is an important process relevant to understanding cloud-climate feedbacks. This study demonstrates a benchmark framework for using novel airborne measurements and retrievals to constrain high-resolution simulations of moderately deep cumulus clouds and pathways for scaling results to large-scale models and space-based observational platforms.


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