Unveiling Cloud Microphysics of Marine Cold Air Outbreaks Through A-Train’s Active Instrumentation

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

This is a concise and well-directed study. It’s clearly and well-written with good figures that collapse a large volume of data into some clear results using a well-established metric to distinguish cold air outbreaks from frontal snowfall. The occurrence and microphysical properties of marine cold-air outbreaks are of critical importance to high-latitude weather and climate, making this an important contribution to the literature.

I have a few major comments asking for some expanded discussion of the retrieval products used, and linking the results back to the literature on CAOs, which I hope can be addressed without requiring more analysis. Most other comments are directed toward improving the figures in some specific ways. The literature review, methods and results are already very clear and concise. 

 

Major comments:

1. Could you please provide some comment in the paper on the extent to which the DARDAR-CLOUD product represents full profiles of ice and snow in north-Atlantic marine cold-air outbreaks. I’m specifically thinking of how frequently DARDAR’s retrieved profiles of ice and snow properties may be incomplete or biased due to the presence of supercooled liquid detected by CALIPSO (or not detected, once the lidar is extinguished). Is information on the frequency of supercooled and mixed-phase cloud in CAOs using DARDAR-MASK available from an existing study? Relating specifically to the use that this study makes of DARDAR-CLOUD: what does DARDAR-CLOUD do in the situation of mixed-phase cloud? Is a radar-only ice and snow retrieval carried out, while the lidar backscatter is assumed to relate to the liquid part? Or is no retrieval carried out? Are any assumptions made about the effects of riming? If not, what might be missed in this study? This context would help in the interpretation of the profiles of microphysical retrievals used in this study. Would sub-sampling of ice-only profiles help to explain any of the features identified here, or are there any microphysical features of CAO snow that we might expect to detect that aren’t represented in DARDAR-CLOUD? This isn’t outside the scope of explaining the results of the present paper, and needs further discussion.

 

2. The final results of this paper pertain to the total contribution of CAO events to the bulk mass of snow over the North Atlantic. But a few parts of this discussion need clarifying:

• • The subfigure titles of Figure 7 refer to “snow water path”, while “ice water path” is used everywhere else. This should be made consistent to avoid confusion.
  • Figure 7 is dominated by high values in one or two spatial features, leaving the rest looking very saturated at the low values. Unlike Figure 3, I think IWP would be better suited to a log-scale. 
  • The caption of Figure 8 lists the contents of the panels as “CAO (left), non-CAO (right) and unclassified (middle)“. This is easy to misread, leading to confusion. Perhaps in addition to describing the panels from left-to-right, this information could be included as titles to the subfigures.
  • How can we interpret the differences in snowfall distribution between the CAO, unclassified, and non-CAO events? 
    • In the introduction some expectations are raised about the expected differences between CAO and frontal snowfall (line 42). Does the argument made in the methods section about refining the classification criteria (L 115–121) mean that we can interpret non-CAO as a frontal regime? If so, would this be a more useful label to aid interpretation of the results—and if not, why not?
    • Further, in the introduction a key result is signposted but not paid off in the results or discussion: that within CAOs a longer fetch is expected to correspond to deeper convection and higher snowfall rates (L44–46). This seems to be corroborated by the results of Figure 5 (larger ice effective radius with distance from land/sea ice) and Figure 8 (higher IWP with distance from land/sea ice), but the word “fetch” is not used again after this paragraph. 

 

3. Figure 3.: the log units of effective radius are very obscure for the reader, and make this figure less easily interpreted. This is aided in the text with parenthetical values, but I think these figures and all discussion would be best done in linear units. The x-axis of the figure may still be kept in log-units if the authors prefer, but my experience is that for a variable that varies only over one order of magnitude, the difference between the two regimes would be clearer if this figure had linear x-axes.

 

4. Conclusions:

• • Please return to the literature in the introduction to evaluate how well these results corroborate or extend what’s expected or known.
  • To say that ice effective radius peaks “between 10−5 and 10−4 m” is much too vague. Figure 3 shows that both distributions have peaks between 10 and 100 microns, as will most ice clouds. 
  • Please briefly evaluate the retrieval products used in this paper: what might be their limitations? What are the open questions for the microphysics of CAO? 

 

Minor comments:

• The abbreviations list appears to be hallucinating: 
• “ACM-CAP” is not used in this paper. If this refers to the EarthCARE product going by this acronym, the abbreviation is incorrect.
• “Carbon Copy”, “Artificial Intelligence”, “Article Processing Charge”, “Directory of Open Access Journals”, “Three Letter Acronym”, “Linear Dichroism” and “Geostationary Earth Orbit” are complete non-sequiturs. Perhaps some of these are leftovers from a generic list in the article template.

Author Response

We thank the reviewer for their thoughtful and constructive comments, which have significantly improved the quality of our manuscript. The detailed responses are included in the attached MS word file. 

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

Comments on “Unveiling cloud microphysics of marine cold air outbreaks through a-train’s active instrumentation” by Mroz et al.

This work investigates the microphysical properties and vertical structure of snowfall in MCAO and non-MCAO using active remote sensing from combined CALIPSO-CloudSat. Results indicate that the cloud top height during MCAOs is almost below 3 km, while that during non-MCAOs extends up to 10 km. IWC in MCAOs is generally lower with a smaller effective radius. The topic is in the scope of the Atmosphere. After carefully reviewing the manuscript, I found that it is easy to follow but not well-organized. This manuscript can only be accepted after major revisions.

Abstract: The authors did not clearly present the key conclusions of this work, which is very important. Please add relevant discussions in this part.

Section Introduction: Despite the considerable amount of relevant research, the authors only cited four references. This could not convince the readers that the authors have a thorough understanding of the progress in the related research.And, the novelty of this paper was not clearly emphasized.

Section Data and Methods: The authors provide a detailed description of the relevant satellite instruments, but lack a detailed description regarding the specific data or dataset, the specific data volume, etc. used in this study. Besides, the data processing methods for IWC and other variables in section 3 (Lines 229-240) would be more appropriately placed in this section.

Author Response

We would like to thank the reviewer for very valuable comments. Please see the attached file for the responses. 

Author Response File: Author Response.pdf

Reviewer 3 Report

Comments and Suggestions for Authors

General Comments:

The paper provides a detailed investigation into the microphysical properties of snowfall associated with ‘Marine Cold Air Outbreaks (MCAOs)’ using CloudSat-CALIPSO observations and ERA5 reanalysis data. It effectively differentiates between CAO and non-CAO snowfall events, offering valuable insights into cloud microphysics, including ice water content, effective radius, and cloud vertical structure. The use of CloudSat-CALIPSO data enables a comprehensive examination of snowfall microphysics across different atmospheric conditions, while the incorporation of the instability parameter (M) for categorizing CAO and non-CAO conditions further improves the clarity of the study. The methodology and results are well-structured, with clear figures that effectively support key findings. However, certain aspects require further clarification and improvement. Below are major and minor comments.

Major Comments:

1. Page no. 2, Lines 75-84: The study extensively relies on CloudSat CPR and DARDAR retrievals. Have the snowfall rates or ice water contents been compared with independent datasets (e.g., ground-based radar or GPM DPR)? If not, acknowledging the limitations of these retrievals would improve transparency.
2. Page 3 (Lines 115-121): The choice of the |M| < 5 K threshold for excluding events seems somewhat arbitrary. Have sensitivity tests been conducted to assess how this threshold impacts results? Clarifying this point would strengthen the robustness of the classification approach.
3. Page 4 (Lines 151-169) The paper notes that CAO conditions lead to a narrower effective radius distribution (r_eff), suggesting limited ice growth due to lower ambient humidity. However, could differences in aerosol concentrations and cloud condensation nuclei (CCN) availability also play a role? A discussion of these processes would provide a more comprehensive explanation.
4. Page no. 8, Lines 245-255: Since CloudSat has a limited temporal sampling frequency (~16-day revisit cycle), how might this impact the statistical representativeness of the results? Including a brief discussion on potential sampling biases would enhance the interpretation.
5. In the summary and conclusion section, the study acknowledges that "unclassified" events dominate near the sea ice edge. Could these events significantly influence snowfall climatology in this region? If so, how do they compare micro-physically to the CAO and non-CAO categories?

Minor Comments:

1. Page 1, Lines 6-9, 14-19: The abstract could briefly mention key quantitative findings, such as differences in IWC or effective radius between CAO and non-CAO events. Further, the role of CAOs in modulating surface radiative balance is mentioned. It would be helpful to cite specific studies quantifying these radiative impacts.
2. I do not see sub-numbering of figures, such as Figure 4 (a), 4 (b), 4 (c), etc. Please ensure that sub-numbering is included throughout the manuscript for all figures, as it is currently missing. Also, in figure 3 why the colour bar is not same for the two plots. Please check it carefully throughout the manuscript.
3. Figure 3: The normalization method for radar reflectivity counts should be explicitly described in the caption to clarify whether area-weighted normalization has been applied.
4. Lines 200-212, Page no. 6: The discussion of effective radius (r_eff) could benefit from explicit numerical values (e.g., mean and interquartile range) to support the qualitative interpretation.
5. Lines 213-223, Page no 7: The role of ice nucleation processes in influencing cloud particle concentrations is not addressed. Could aerosol availability affect N₀∗ differences between CAO and non-CAO cases?

Line 270: The conclusion states that boundary-layer processes play a critical role, but additional references discussing their influence in high-latitude snowfall events would reinforce this claim.

Comments on the Quality of English Language

English could be improved.

Author Response

We would like to thank the reviewer for very valuable comments. Please see the attached file for the responses. 

Author Response File: Author Response.pdf

Reviewer 4 Report

Comments and Suggestions for Authors

General comments: The study provides novel insights into the microphysical properties of snowfall during Marine Cold Air Outbreaks (MCAOs) by leveraging the synergy of CloudSat and CALIPSO data. The use of the DARDAR product to analyze ice water content, effective radius, and particle concentration in MCAOs is innovative and offers a detailed understanding of these events. The written language is fine. However, the following issues need to be noted.

Comment 1: The abstract should reflect the contribution of this article to the research field, such as key conclusions and numbers.

Comment2: In Introduction

1. What is the problem that this study aims to solve? The introduction should be closely centered around the problem, such as the logical relationship of "raising the problem ->describing the problem ->how to do it", to enhance the academic quality of the writing.

2. The objectives, interests, questions/gaps, significance, etc. of this study need to be more clearly defined.

Comment3: In section 2

1. In Line 76, excess text "eg."?

2. In Lines 99-104, the detailed information on the two types of remote sensing observation data used in the article, such as time period, spatiotemporal resolution, sample size, etc., needs to be specifically explained. Suggest drawing a table to describe.

3. In Lines 105-114, could you give the details of the "DARDAR algorithm" and "M", e.g., formula and/or flowchart?

4. In Lines 115-121, the choice standard of the threshold as 5K should be clearly explained

5. Several data/method-related issues should discussed

1). The study relies on high-quality data from CloudSat, CALIPSO, and ERA5 reanalysis, ensuring reliability. The analysis of radar reflectivity, ice water content, and effective radius provides comprehensive insights into MCAO cloud structures. However, the authors might consider including additional metrics, such as cloud phase or aerosol interactions, to further enrich the microphysical analysis.

2)The methodology is robust and well-documented. The use of the M parameter to classify CAO and non-CAO events is a practical approach to distinguish between different meteorological regimes. However, further validation of the classification criteria using independent datasets or ground-based observations could strengthen the study.

3) The study covers an 11-year period, providing a robust temporal analysis. However, the spatial resolution of the data and the normalization by grid area are critical factors. The authors should discuss any potential limitations related to the spatial representativeness of the results, especially in regions with sparse data coverage.

5. It is recommended to add a flowchart to connect the data, models/methods, experiments, results, conclusions, etc. in this article for easier reading.

 

Comment4:For section 3,

1. For Figures 1-3, the ranges/intervals and color of the contour lines should be clearly noted.

2. In Lines 123-169, this section of validation and comparison seems to lack a section annotation, such as "3. x. Validation of..."

3. Please ensure that this section uses internationally recognized units. For example, “km” should be either Km or Kilometer

4. Overall, the new findings in the results section lack dialectical comparison with previous research, with only "Mateling et al" appearing multiple times, which greatly affects the scientific significance of the new findings in this article

Comment5: For section 4,

1. The conclusion should be an objective summary of the new discoveries and their dialectics in the Result and Discussion section.

2. What is the future direction of this research? The authors might suggest potential future research directions, such as incorporating additional satellite data or conducting targeted field campaigns to validate their findings. This would enhance the study's impact and relevance to the broader scientific community.

3. While the study provides a detailed comparison between CAO and non-CAO events, a brief discussion on how these findings compare with other related studies (e.g., polar lows or extratropical cyclones) would provide a broader context and strengthen the conclusions.

Comment6: Last, suggest adding a discussion section, which should include the following aspects:

1. Limitations of this study

2. Various new discoveries, innovations, and connotations, as well as dialectics with previous research

3. Possible future-specific applications and directions. The study highlights the importance of CAOs in high-latitude climate systems and their potential impact on weather prediction models. The authors should consider discussing the implications of their findings for future climate change scenarios, particularly in regions experiencing rapid Arctic warming.

4. Summarize the innovative significance and shortcomings to be explored in these new discoveries

Author Response

We would like to thank the reviewer for very valuable comments. Please see the attached file for the responses. 

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

Thanks for your through responses, I recommend this paper be accepted for publication.

Reviewer 2 Report

Comments and Suggestions for Authors

Authors have addressed all my concerns in the revised manuscript and response, and I have no more questions. The paper is recommended to be accepted.

Reviewer 4 Report

Comments and Suggestions for Authors

The authors have addressed all the issues as commented.  I suggest accepting.