the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 05 Feb 2025
Tropical cirrus evolution in a km-scale model with improved ice microphysics
Abstract. Tropical cirrus clouds form via in situ ice nucleation below the homogeneous freezing temperature of water or detrainment from deep convection. Despite their importance, limited understanding of their evolution and formation pathways contributes to large uncertainty in climate projections. To address these challenges, we implement novel passive tracers in the cloud-resolving model SAM to track the three-dimensional development of cirrus clouds. One tracer tracks air parcels exiting convective updrafts, revealing a rapid decline in ice crystal size and number as anvils age. Another tracer focuses on in situ cirrus, capturing their formation in the cold upper atmosphere and the subsequent reduction in ice crystal number over time. We find that in situ cirrus dominate at colder temperatures and lower ice water contents, while anvil cirrus prevail at temperatures above -60 °C. Although in situ cirrus have a smaller radiative impact compared to anvil cirrus, their contribution must be considered when evaluating top-of-the-atmosphere radiative effects. These findings improve our ability to assess the distinct roles of convective and in situ cirrus in shaping tropical cirrus properties and their impacts on climate.
We also improve the model's representation of tropical cirrus through simple, computationally inexpensive microphysics modifications, achieving better agreement with tropical aircraft observations. We show that updrafts critical for tropical cirrus formation are only resolved at horizontal grid spacings finer than 250 m—much finer than those used in global storm-resolving models. To mitigate this limitation, we propose microphysics improvements that reduce biases without increasing computational costs.
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.
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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RC1: 'Comment on egusphere-2025-203', Anonymous Referee #1, 27 Feb 2025
Review of “Tropical cirrus evolution in a km-scale model with improved ice microphysics” by Gasparini et al.
This review was produced by a co-review team, as agreed with the editor.
General comments
The authors study tropical cirrus using an idealised simulation with a convection-permitting model (SAM), multi-campaign aircraft dataset (POSIDEN and ATTREX), satellite data (DARDAR, CCCM and 2C-ICE), and a selection of global-storm resolving models (GSRMs). It analyses these data from a variety of angles, including the use of atmospheric tracers, power spectra, standard deviation of vertical velocity, cloud radiative effect, ice water content (IWC), ice particle concentration and ice particle radius. The tracer analysis in particular focuses on the distinction of cirrus detrained from convective anvil cloud opposed to cirrus formed in-situ. Following this analysis, the authors conclude that in-situ cirrus prevails at colder temperatures and low IWC, while anvil cirrus prevails at warmer temperatures above -60C. The radiative analysis highlights the anvil cirrus as particularly important, but the authors suggest in-situ cirrus is still important in this regard. The authors explore model resolution and show that the updraught power spectra (which they consider important for cirrus formation) only becomes accurate around 250m grid spacing. They achieve better agreement between the model and observations with their proposed methods without the need to increase the computational cost.
It is great to see multi-campaign aircraft data exploited for improving model performance, and it is great to see some microphysical model development with computational resource in mind. There are many interesting results in this paper and, while they jump around different aspects of cirrus research, we think there is enough coherence for it to make a paper. However, if trying to cover a lot of ground, a paper needs a structure that helps the reader. We don’t think that is quite the case here. The least subjective aspect of this is the presentation of model improvement content after the presentation of scientific model results in relation to the tracers (which must have been based on the model improvements). We cannot understand the logic in this, so we suggest moving section 3 after at least section 4.1 but better would be after the whole of section 4. Other than this, we take issue with a few statements by the authors and believe there are few possible improvements, but once that has been considered we hope to see the manuscript reach publication.
Major comments
L9/L361 – The result suggests that in-situ, thinner clouds are not radiatively important. However, the authors caveat in both the abstract and in the text that such cloud must still be considered when looking at such radiation. The manuscript does not show any results to back this up, and I cannot see any argument made for why that is the case. Why “must” the in-situ CRE be considered? In what way does the thinner cirrus “contribute meaningfully”?
L270 – “cut the microphysical bias in half ” – I cannot see what this is based upon. In Figure 5, the small particle bias metric goes from 0.92 to 0.65, and the large particle bias metric goes from 0.52 to 0.4. How is this halving? Perhaps you need to give the formula for the metric or explain it more. We don’t fully understand what it is.
L276 – CC applies to the saturation vapour pressure. Whilst I can understand that it plays a role in moisture with height in a stable atmosphere, the connection to anvil cirrus seems much more complicated, as the available moisture at each height is a result of CAPE and low-level humidity. In fact, I might naively assume that because the saturation vapour pressure reduces with height (i.e. temperature), one should expect increasing condensate as moisture is lifted as it cannot remain as vapour. Are you drawing this statement of CC yourself? In which case, please explain the logical steps in greater detail. If this is something you consider to be widely accepted, please point to a reference or two that explains the mechanistic connection between IWC vertical profile and CC.
Fig9 – The GSRM data has not been described. Please add a description to the data section.
Fig 10 and L366 – I strongly object to the illustration on fig10 and the suggestion of any analysis “split into two separate evolution pathways”. Until this point, the paper was doing a brilliant job of both simplifying the problem whilst maintaining necessary complexity (e.g. Figure 3c). However, as far as I can tell, you have not used the tracers in the analysis of CRE. This is unfortunate, and I would strongly encourage to break the CRE analysis down by tracer if possible, as it would be fascinating. However, you have instead subjectively drawn on clouds to Figure 10. These are misleading because there is not such a simple split. Your own Figure 3c shows the large amount of overlap in the central part of the IWP spectrum. Whilst you could adjust the illustration to show that in-situ and anvil cirrus occur in the same place, how will you illustrate the dual-origin component? I often appreciate diagrams, but I think it is necessary to remove this as I don’t think it adequately reflects the value of your results.
L367 – Fig 3c shows similar amounts of anvil cirrus all the way to 0.01 g m-2. This is why I think your illustration is misleading (as described above). It makes one think there is this clear distinction, but there is not. Just because in-situ cirrus dominates <1gm-2 cloud doesn’t mean that a major fraction of anvil cirrus is not spreading to that thinness.
Minor comments
L49 – In the outline of the paper you first say you demonstrate modification and then look at tracers. I suggest this is a more logical ordering for your sections than you actually have.
Sec 2.1.2 – Possibly it would be good to further subsection this so each modification is clearly labelled as it would make it easier to refer back to the relevant text in fig5 caption.
L167- They use nighttime data only because the lidar signal is noisier during the daytime. Is this representative for the simulation?
Fig1 – Add description of solid and dashed black lines.
Sec 2.2 – How long is the simulation and how much of that has been used in the results?
Sec 2.3 and 2.4 – Maybe sections 2.3 and 2.4 would be better grouped under a “Data” section. The title for section 2.3 could be shortened to “In-situ observations”. In section 2.4, there’s no need for subsections, it’s clear enough if each of the datasets is presented in separate paragraphs.
Fig 2 – Could a second, later time be shown once convection has subsided? It would be useful to see how such cloud and tracer categorisation progresses after convection finishes but high cloud remains. It would be fine if only panel d was shown for the later time.
L219 – “excludes portions” – what portion is excluded? I don’t recall that being described.
Fig 3 – What’s the length of the time period used to generate this figure?
L225 – dual-origin “dominates” in the middle range is probably worth being explicit about. It looks to be the range should be 1-40 where dual-origin is the dominant category, not 1-10?
Fig 4 – “omit that panel” – but then you include the dashed contour on panel e. I would suggest you should be either including panel j, or omitting the dashed contour from panel e.
L245 – “converging” – It is not clear to me that they are converging. Similar overlap of dashed and solid contours in both 3-4h and 7-8h. What is this statement based on?
Fig9 – Is the tailing off of both model an observation from the 5/3 slope robust or a result of limited data? If the latter, consider showing uncertainty on the plot or setting a threshold for what parts of the lines are robust and to be plotted.
L413-414 - “We also perform a short sensitivity test…” What does short mean in this context? This explanation would be better suited in the methods.
L415 – (not shown) Can it be added to the appendix?
Fig5 caption – It would be helpful to reference relevant text for each modification.
Conclusions – The first paragraph says about tracers first but then the following text describes model improvement results first. That’s fine but it highlights that probably the model improvements results should come before tracer results in the main text too?
Technical corrections
L313 – “Of particular significance are the high-frequency fluctuations”. I'd change the order of the sentence: The high-frequency fluctuations are particularly significant...
Citation: https://doi.org/10.5194/egusphere-2025-203-RC1 - AC1: 'Reply on RC1', Blaž Gasparini, 23 May 2025
-
RC2: 'Comment on egusphere-2025-203', Anonymous Referee #2, 22 Mar 2025
In "Tropical cirrus evolution in a km-scale model with improved ice microphysics", Gasparini et al. present new results on the lifecycle, microphysical and radiative properties of tropical cirrus. The authors employ Lagrangian methods to study these cloud properties, however unlike previous studies they introduce the novel application of passive, online tracers to track not only the lifetime of the cirrus but also link the measured properties to the formation process allowing deeper insights and comparisons into the relative contributions of anvil and in situ cirrus than previous studies. Comparisons between modelled cirrus properties, satellite retrievals and in situ aircraft observations are made both to provide cirrus cloud properties including their radiative impact, as well as to guide improvements to the model microphysics scheme to better match observed cirrus properties. The manuscript is well written and presented.
Comments:
Line 25: Is precipitation the main reason for the reduction is mass? Except for MCSs with a large stratiform component, I would expect sublimation to be the main sink of ice mass. In terms of optical thickness, is this not primarily driven by the divergence of the anvil cloud? I don’t believe this reference is the most appropriate, or that a reference is necessary here.
Line 36: I don’t fully agree with this statement (on the pros of passive tracers). The main trade off for passive tracers is that they have to be run online, meaning that this approach cannot be applied retrospectively to existing model runs, arguably meaning that they are less flexible. In addition, tracer advection is a large cost in many km-scale models. I would argue that the main benefits of passive tracers is that they are more accurate and can allow further insights into complex processes including cirrus origin, which could be the basis for a call for more modellers to include them in large model runs (e.g. DYAMOND) for community use.
Section 2.1.2: This subsection is nice, but could be improved by briefly outlining the issues with the standard P3 scheme at the start to provide context for the modifications.
Line 155: Is the lack of observations near convective cores accounted for when comparing with the model output later in the manuscript?
Line 181: While this approach provides a CRE estimate closer to the net CRE, it hides effects of differences in cirrus properties throughout the diurnal cycle. Comparing figure B2 to 10, in appears that the differences between CERES and model CREs are relatively larger when only sampling around 1:30pm. Could an alternative approach be to take compare both the night-time and daytime CERES overpasses? This could be included as a suppementary figure.
Line 210: To clarify, dual-original cirrus is defined as new ice nucleation occurring less than 30 hours after detrainment?
Figure 10: What is the lower limit of IWP measured by the different satellite products?
Line 357: This result could be shown more clearly by including a figure showing the CRE x frequency contribution from each of detrained, in situ and dual-origin cirrus in the SAM model similar to fig. 3c, along with the total CRE contribution integrated over each distribution.
Technical corrections:
Eq. 6/7: Order of clear sky and all sky flux terms is different between eq. 6 and 7, should be made consistent for clarity
Line 216: Missing reference to fig. 3a
Figure 10: Clarity of legends could be improved by including all labels in one legend for fig. 10a and explicitly showing all colour/pattern combinations for fig. 10b/c rather than colour for LW/SW/net and pattern for model/CCCM
Citation: https://doi.org/10.5194/egusphere-2025-203-RC2 - AC2: 'Reply on RC2', Blaž Gasparini, 23 May 2025
-
RC3: 'Comment on egusphere-2025-203', Anonymous Referee #3, 25 Mar 2025
Review of Title: Tropical cirrus evolution in a km-scale model with improved ice microphysics
Author(s): Blaž Gasparini et al.General Comments
The authors present an analysis of temporal evolution of different cirrus types with the use of improved microphysical representation in the SAM model. A novel use of passive tracers in the model allows for tracking the cirrus evolution through part of the cirrus lifecycle and taking a look at the cloud radiative effects from these varied cirrus types. Model results are compared with satellite data and airborne observations collected in the Tropical Tropopause region with reasonable agreement, yet some discrepancies, which are discussed further in the text. The improvements in the microphysical model are a simple yet important step forward in representation of cirrus microphysics, and the passive tracers a unique tool to better track the influence of cloud formation mechanisms on characteristics and lifecycle. The concepts of the manuscript are fairly clear, but the text includes several general statements without direct quantification as well as general statements that point to another reference. The manuscript would benefit from further clarity through specificity, including brief summaries of the concept, definition, method, etc. referenced in the citated paper.Specific Comments
L120. Why is 80 minutes chosen for the arbitrary timescale? The reader is referenced to Gasparini et al. (2022), but for completeness it would be helpful to add a brief statement here.L148-150 and 381-383. Please elaborate on the bug that was recently fixed; is this bug present in the larger Kramer et al (2020) dataset? Is it also present in the original datasets in the NASA archives? On this latter point, somewhere in the paper or Code/Data Availability, reference to the original access for POSIDON, ATTREX, and CONTRAST data should be included.
L155-156. Please quantify “few measurements?”
L158. Please clarify why the years 2007-2010 were chosen? Would it be possible to utilize years that coincide with the aircraft data?
L167. Please comment on any potential biases from utilizing nighttime-only data?
Figure 4. How are these instances initialized?
Figure 4. The overlayed contours of peak probability are helpful, thank you.L243. “most of the in situ crystals are smaller than 30 um” ..are you referring to the 7-8 h plot in Fig 4i? For the other plots, there are still quite a number of ice crystals larger than 30 um. Please clarify, or better yet, give numerical quantification to “most.”
Figure 5. “The number represents..” is rather unclear. Would suggest being more specific: “The numbers in the upper left and upper right of the plot region..” Does this number have a name? “Calculated separately for small and large particle sizes..” Please indicate the size range for each.
Figures 6 and 8. How many airborne samples are represented in each bin? Can you provide an indication of aircraft time spent sampling at the various temperature bins?
Appendices. Temperature is given as degrees C throughout the paper, then referenced in degrees Kelvin in appendices. Would suggest keeping consistency
Technical Corrections
L86: “further refinements to would be” – remove “to”Citation: https://doi.org/10.5194/egusphere-2025-203-RC3 - AC3: 'Reply on RC3', Blaž Gasparini, 23 May 2025
Status: closed
-
RC1: 'Comment on egusphere-2025-203', Anonymous Referee #1, 27 Feb 2025
Review of “Tropical cirrus evolution in a km-scale model with improved ice microphysics” by Gasparini et al.
This review was produced by a co-review team, as agreed with the editor.
General comments
The authors study tropical cirrus using an idealised simulation with a convection-permitting model (SAM), multi-campaign aircraft dataset (POSIDEN and ATTREX), satellite data (DARDAR, CCCM and 2C-ICE), and a selection of global-storm resolving models (GSRMs). It analyses these data from a variety of angles, including the use of atmospheric tracers, power spectra, standard deviation of vertical velocity, cloud radiative effect, ice water content (IWC), ice particle concentration and ice particle radius. The tracer analysis in particular focuses on the distinction of cirrus detrained from convective anvil cloud opposed to cirrus formed in-situ. Following this analysis, the authors conclude that in-situ cirrus prevails at colder temperatures and low IWC, while anvil cirrus prevails at warmer temperatures above -60C. The radiative analysis highlights the anvil cirrus as particularly important, but the authors suggest in-situ cirrus is still important in this regard. The authors explore model resolution and show that the updraught power spectra (which they consider important for cirrus formation) only becomes accurate around 250m grid spacing. They achieve better agreement between the model and observations with their proposed methods without the need to increase the computational cost.
It is great to see multi-campaign aircraft data exploited for improving model performance, and it is great to see some microphysical model development with computational resource in mind. There are many interesting results in this paper and, while they jump around different aspects of cirrus research, we think there is enough coherence for it to make a paper. However, if trying to cover a lot of ground, a paper needs a structure that helps the reader. We don’t think that is quite the case here. The least subjective aspect of this is the presentation of model improvement content after the presentation of scientific model results in relation to the tracers (which must have been based on the model improvements). We cannot understand the logic in this, so we suggest moving section 3 after at least section 4.1 but better would be after the whole of section 4. Other than this, we take issue with a few statements by the authors and believe there are few possible improvements, but once that has been considered we hope to see the manuscript reach publication.
Major comments
L9/L361 – The result suggests that in-situ, thinner clouds are not radiatively important. However, the authors caveat in both the abstract and in the text that such cloud must still be considered when looking at such radiation. The manuscript does not show any results to back this up, and I cannot see any argument made for why that is the case. Why “must” the in-situ CRE be considered? In what way does the thinner cirrus “contribute meaningfully”?
L270 – “cut the microphysical bias in half ” – I cannot see what this is based upon. In Figure 5, the small particle bias metric goes from 0.92 to 0.65, and the large particle bias metric goes from 0.52 to 0.4. How is this halving? Perhaps you need to give the formula for the metric or explain it more. We don’t fully understand what it is.
L276 – CC applies to the saturation vapour pressure. Whilst I can understand that it plays a role in moisture with height in a stable atmosphere, the connection to anvil cirrus seems much more complicated, as the available moisture at each height is a result of CAPE and low-level humidity. In fact, I might naively assume that because the saturation vapour pressure reduces with height (i.e. temperature), one should expect increasing condensate as moisture is lifted as it cannot remain as vapour. Are you drawing this statement of CC yourself? In which case, please explain the logical steps in greater detail. If this is something you consider to be widely accepted, please point to a reference or two that explains the mechanistic connection between IWC vertical profile and CC.
Fig9 – The GSRM data has not been described. Please add a description to the data section.
Fig 10 and L366 – I strongly object to the illustration on fig10 and the suggestion of any analysis “split into two separate evolution pathways”. Until this point, the paper was doing a brilliant job of both simplifying the problem whilst maintaining necessary complexity (e.g. Figure 3c). However, as far as I can tell, you have not used the tracers in the analysis of CRE. This is unfortunate, and I would strongly encourage to break the CRE analysis down by tracer if possible, as it would be fascinating. However, you have instead subjectively drawn on clouds to Figure 10. These are misleading because there is not such a simple split. Your own Figure 3c shows the large amount of overlap in the central part of the IWP spectrum. Whilst you could adjust the illustration to show that in-situ and anvil cirrus occur in the same place, how will you illustrate the dual-origin component? I often appreciate diagrams, but I think it is necessary to remove this as I don’t think it adequately reflects the value of your results.
L367 – Fig 3c shows similar amounts of anvil cirrus all the way to 0.01 g m-2. This is why I think your illustration is misleading (as described above). It makes one think there is this clear distinction, but there is not. Just because in-situ cirrus dominates <1gm-2 cloud doesn’t mean that a major fraction of anvil cirrus is not spreading to that thinness.
Minor comments
L49 – In the outline of the paper you first say you demonstrate modification and then look at tracers. I suggest this is a more logical ordering for your sections than you actually have.
Sec 2.1.2 – Possibly it would be good to further subsection this so each modification is clearly labelled as it would make it easier to refer back to the relevant text in fig5 caption.
L167- They use nighttime data only because the lidar signal is noisier during the daytime. Is this representative for the simulation?
Fig1 – Add description of solid and dashed black lines.
Sec 2.2 – How long is the simulation and how much of that has been used in the results?
Sec 2.3 and 2.4 – Maybe sections 2.3 and 2.4 would be better grouped under a “Data” section. The title for section 2.3 could be shortened to “In-situ observations”. In section 2.4, there’s no need for subsections, it’s clear enough if each of the datasets is presented in separate paragraphs.
Fig 2 – Could a second, later time be shown once convection has subsided? It would be useful to see how such cloud and tracer categorisation progresses after convection finishes but high cloud remains. It would be fine if only panel d was shown for the later time.
L219 – “excludes portions” – what portion is excluded? I don’t recall that being described.
Fig 3 – What’s the length of the time period used to generate this figure?
L225 – dual-origin “dominates” in the middle range is probably worth being explicit about. It looks to be the range should be 1-40 where dual-origin is the dominant category, not 1-10?
Fig 4 – “omit that panel” – but then you include the dashed contour on panel e. I would suggest you should be either including panel j, or omitting the dashed contour from panel e.
L245 – “converging” – It is not clear to me that they are converging. Similar overlap of dashed and solid contours in both 3-4h and 7-8h. What is this statement based on?
Fig9 – Is the tailing off of both model an observation from the 5/3 slope robust or a result of limited data? If the latter, consider showing uncertainty on the plot or setting a threshold for what parts of the lines are robust and to be plotted.
L413-414 - “We also perform a short sensitivity test…” What does short mean in this context? This explanation would be better suited in the methods.
L415 – (not shown) Can it be added to the appendix?
Fig5 caption – It would be helpful to reference relevant text for each modification.
Conclusions – The first paragraph says about tracers first but then the following text describes model improvement results first. That’s fine but it highlights that probably the model improvements results should come before tracer results in the main text too?
Technical corrections
L313 – “Of particular significance are the high-frequency fluctuations”. I'd change the order of the sentence: The high-frequency fluctuations are particularly significant...
Citation: https://doi.org/10.5194/egusphere-2025-203-RC1 - AC1: 'Reply on RC1', Blaž Gasparini, 23 May 2025
-
RC2: 'Comment on egusphere-2025-203', Anonymous Referee #2, 22 Mar 2025
In "Tropical cirrus evolution in a km-scale model with improved ice microphysics", Gasparini et al. present new results on the lifecycle, microphysical and radiative properties of tropical cirrus. The authors employ Lagrangian methods to study these cloud properties, however unlike previous studies they introduce the novel application of passive, online tracers to track not only the lifetime of the cirrus but also link the measured properties to the formation process allowing deeper insights and comparisons into the relative contributions of anvil and in situ cirrus than previous studies. Comparisons between modelled cirrus properties, satellite retrievals and in situ aircraft observations are made both to provide cirrus cloud properties including their radiative impact, as well as to guide improvements to the model microphysics scheme to better match observed cirrus properties. The manuscript is well written and presented.
Comments:
Line 25: Is precipitation the main reason for the reduction is mass? Except for MCSs with a large stratiform component, I would expect sublimation to be the main sink of ice mass. In terms of optical thickness, is this not primarily driven by the divergence of the anvil cloud? I don’t believe this reference is the most appropriate, or that a reference is necessary here.
Line 36: I don’t fully agree with this statement (on the pros of passive tracers). The main trade off for passive tracers is that they have to be run online, meaning that this approach cannot be applied retrospectively to existing model runs, arguably meaning that they are less flexible. In addition, tracer advection is a large cost in many km-scale models. I would argue that the main benefits of passive tracers is that they are more accurate and can allow further insights into complex processes including cirrus origin, which could be the basis for a call for more modellers to include them in large model runs (e.g. DYAMOND) for community use.
Section 2.1.2: This subsection is nice, but could be improved by briefly outlining the issues with the standard P3 scheme at the start to provide context for the modifications.
Line 155: Is the lack of observations near convective cores accounted for when comparing with the model output later in the manuscript?
Line 181: While this approach provides a CRE estimate closer to the net CRE, it hides effects of differences in cirrus properties throughout the diurnal cycle. Comparing figure B2 to 10, in appears that the differences between CERES and model CREs are relatively larger when only sampling around 1:30pm. Could an alternative approach be to take compare both the night-time and daytime CERES overpasses? This could be included as a suppementary figure.
Line 210: To clarify, dual-original cirrus is defined as new ice nucleation occurring less than 30 hours after detrainment?
Figure 10: What is the lower limit of IWP measured by the different satellite products?
Line 357: This result could be shown more clearly by including a figure showing the CRE x frequency contribution from each of detrained, in situ and dual-origin cirrus in the SAM model similar to fig. 3c, along with the total CRE contribution integrated over each distribution.
Technical corrections:
Eq. 6/7: Order of clear sky and all sky flux terms is different between eq. 6 and 7, should be made consistent for clarity
Line 216: Missing reference to fig. 3a
Figure 10: Clarity of legends could be improved by including all labels in one legend for fig. 10a and explicitly showing all colour/pattern combinations for fig. 10b/c rather than colour for LW/SW/net and pattern for model/CCCM
Citation: https://doi.org/10.5194/egusphere-2025-203-RC2 - AC2: 'Reply on RC2', Blaž Gasparini, 23 May 2025
-
RC3: 'Comment on egusphere-2025-203', Anonymous Referee #3, 25 Mar 2025
Review of Title: Tropical cirrus evolution in a km-scale model with improved ice microphysics
Author(s): Blaž Gasparini et al.General Comments
The authors present an analysis of temporal evolution of different cirrus types with the use of improved microphysical representation in the SAM model. A novel use of passive tracers in the model allows for tracking the cirrus evolution through part of the cirrus lifecycle and taking a look at the cloud radiative effects from these varied cirrus types. Model results are compared with satellite data and airborne observations collected in the Tropical Tropopause region with reasonable agreement, yet some discrepancies, which are discussed further in the text. The improvements in the microphysical model are a simple yet important step forward in representation of cirrus microphysics, and the passive tracers a unique tool to better track the influence of cloud formation mechanisms on characteristics and lifecycle. The concepts of the manuscript are fairly clear, but the text includes several general statements without direct quantification as well as general statements that point to another reference. The manuscript would benefit from further clarity through specificity, including brief summaries of the concept, definition, method, etc. referenced in the citated paper.Specific Comments
L120. Why is 80 minutes chosen for the arbitrary timescale? The reader is referenced to Gasparini et al. (2022), but for completeness it would be helpful to add a brief statement here.L148-150 and 381-383. Please elaborate on the bug that was recently fixed; is this bug present in the larger Kramer et al (2020) dataset? Is it also present in the original datasets in the NASA archives? On this latter point, somewhere in the paper or Code/Data Availability, reference to the original access for POSIDON, ATTREX, and CONTRAST data should be included.
L155-156. Please quantify “few measurements?”
L158. Please clarify why the years 2007-2010 were chosen? Would it be possible to utilize years that coincide with the aircraft data?
L167. Please comment on any potential biases from utilizing nighttime-only data?
Figure 4. How are these instances initialized?
Figure 4. The overlayed contours of peak probability are helpful, thank you.L243. “most of the in situ crystals are smaller than 30 um” ..are you referring to the 7-8 h plot in Fig 4i? For the other plots, there are still quite a number of ice crystals larger than 30 um. Please clarify, or better yet, give numerical quantification to “most.”
Figure 5. “The number represents..” is rather unclear. Would suggest being more specific: “The numbers in the upper left and upper right of the plot region..” Does this number have a name? “Calculated separately for small and large particle sizes..” Please indicate the size range for each.
Figures 6 and 8. How many airborne samples are represented in each bin? Can you provide an indication of aircraft time spent sampling at the various temperature bins?
Appendices. Temperature is given as degrees C throughout the paper, then referenced in degrees Kelvin in appendices. Would suggest keeping consistency
Technical Corrections
L86: “further refinements to would be” – remove “to”Citation: https://doi.org/10.5194/egusphere-2025-203-RC3 - AC3: 'Reply on RC3', Blaž Gasparini, 23 May 2025
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