Articles | Volume 24, issue 10
https://doi.org/10.5194/acp-24-5737-2024
© Author(s) 2024. This work is distributed under the Creative Commons Attribution 4.0 License.
Simulations of the impact of cloud condensation nuclei and ice-nucleating particles perturbations on the microphysics and radar reflectivity factor of stratiform mixed-phase clouds
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- Final revised paper (published on 21 May 2024)
- Preprint (discussion started on 24 Aug 2023)
Interactive discussion
Status: closed
Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor
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RC1: 'Comment on egusphere-2023-1887', Anonymous Referee #1, 07 Nov 2023
- AC2: 'Reply on RC1', Junghwa Lee, 13 Feb 2024
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RC2: 'Comment on egusphere-2023-1887', Anonymous Referee #2, 04 Jan 2024
- AC1: 'Reply on RC2', Junghwa Lee, 13 Feb 2024
Peer review completion
AR – Author's response | RR – Referee report | ED – Editor decision | EF – Editorial file upload
AR by Junghwa Lee on behalf of the Authors (23 Feb 2024)
Author's response
Author's tracked changes
Manuscript
ED: Referee Nomination & Report Request started (06 Mar 2024) by Tuukka Petäjä
RR by Anonymous Referee #2 (19 Mar 2024)
ED: Publish as is (24 Mar 2024) by Tuukka Petäjä
AR by Junghwa Lee on behalf of the Authors (28 Mar 2024)
Numerical evidence that the impact of CCN and INP concentrations on mixed-phase clouds is observable with cloud radars
By Junghwa Lee et al.
The authors present a model-based analysis of how changes in CCN and INP would affect mixed-phase cloud properties. The most interesting part of the study is the analysis of the impact of CCN and INP on ice particle properties. It is show that changes in CCN and INP could result in detectable changes in particle shapes, for example. Overall, the article is well-written, but there are a few issues that I have summarised below. My major concern is the analysis of how aspect ratio of particle changes as a function of changes in INP and CCN concentrations. I think the analysis would be clearer is a consistent particle classification would be used throughout the study.
Detailed comments:
Page 4. What are particle property variables (PPVs)? It would be helpful to see a list all PPV used in the study.
Page 5. The definition of the sphere volume circumscribing the ice particle is not very clear. Do you have a reference or more detailed explanation of how it is defined? It is no clear what the equation on line 137 implies in terms of an assumed particle shape.
Page 5, line 152 Explanation of the reflectivity factor is not accurate. The reflectivity factor characterises a volume of scatterers, not just one object. One object’s ability to scatter is characterised by a scattering cross section.
To be even more precise Ze is the equivalent reflectivity factor.
Line 177. It is a standard practice to use wavelength appropriate value, not use one computed for cm-wavelengths.
Line 273. “…concentration of INP concentration increases.”
Line 277. “This reduction in droplet size increases the altitude of the cloud base…” I don’t understand why the reduction in droplet size would affect the cloud base.
How is the cloud base defined? Is it defined from the LWC profiles? If yes, how do you separate contributions from cloud droplets and drizzle?
Figure 7. The maximum size of ice particles is just 2 mm for EXP1, while Figure 6 shows significant aggregation. Is there a reason why no larger particles are produced?
Figure 8. In order to interpret the figure, it would be good to know what AR values for typical particle types in your model are. What are AR values for crystals, graupel and aggregates? It is strange to see that graupel in EXP3 does not produce a noticeable change in AR. The statement “…exhibit a plate-like shape with AR (α) < 1,” on line 340 is too general and covers a large fraction of different ice particle types, ranging from pristine dendrites to aggregates. It is expected that aggregates have AR around 0.5 – 0.6 range (Hogan et al. 2012; Li et al. 2018 and Matrosov et al. 2017).
Line 351 “Figure 9(a) provides insights into the predominant shape of ice particles, with plates representing the majority of the particles.”What do you mean when you state that plates represent the majority of the particles? Are aggregates plates? What about graupel? I think you need to use more precise terminology.
Also, in the figure you use “pploy, cploy and irploy”, instead of “ppoly, cpoly and irpoly”.
Hogan, R. J., L. Tian, P. R. A. Brown, C. D. Westbrook, A. J. Heymsfield, and J. D. Eastment, 2012: Radar Scattering from Ice Aggregates Using the Horizontally Aligned Oblate Spheroid Approximation. J. Appl. Meteor. Climatol., 51, 655–671, https://doi.org/10.1175/JAMC-D-11-074.1.
Li, H., Moisseev, D., & von Lerber, A. (2018). How does riming affect dual-polarization radar observations and snowflake shape? Journal of Geophysical Research: Atmospheres, 123, 6070–6081. https://doi.org/10.1029/2017JD028186
Matrosov, S. Y., C. G. Schmitt, M. Maahn, and G. de Boer, 2017: Atmospheric Ice Particle Shape Estimates from Polarimetric Radar Measurements and In Situ Observations. J. Atmos. Oceanic Technol., 34, 2569–2587, https://doi.org/10.1175/JTECH-D-17-0111.1.
Line 364. While it is true that in Figure 9 we can see the difference between AR values for different experiments, I find it difficult to make a connection between this figure and Fig. 6. In Fig. 6 you use rime, aggr. and crystal. But later you introduce a very different classification: namely plate, dendrite, column, and various types of polycrystals in Fig. 9 (a) and in Fig 9 (b) this classification is reduced to plate and ir. poly. It would be better if you would be consistent. In Fig. 10 you go back to riming aggregation and deposition growth, so to which particle in Fig. 9 these processes correspond to?
Figure 12. Looking at EXP1 reflectivity profile in this figure, I find it even more surprising that in Fig. 7 the maximum particle size for EXP1 was just 2 mm. I would have expected to see larger aggregates.