the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 11 Aug 2025
Small Uncrewed Aircraft Based Microphysical Measurements of Polar Stratus Cloud During The Pallas Cloud Experiment 2022
Abstract. A dataset of in-situ observations of stratus cloud microphysics was created from measurements performed at the Pallas atmosphere-ecosystem super site. The data were collected using a small uncrewed aircraft (SUA) and the low-cost, lightweight Universal Cloud and Aerosol Sounding System (UCASS, Smith et al., 2019). Data from the instrument – platform combination was previously validated in Girdwood et al. (2022b) during a similar field campaign at the same site. The dataset contains cloud droplet size distribution, number concentration, and mass concentration, in addition to geolocation data, and meteorological variables. The flight pattern of the SUA was planned to provide a quasi-vertical profile. A total of 84 of these profiles across 39 flights were performed during the campaign period. The data from the SUA flights are available from 10.5281/zenodo.14756233 (Girdwood et al. 2022a).
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Status: final response (author comments only)
- RC1: 'Comment on essd-2025-257', Anonymous Referee #1, 05 Sep 2025
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RC2: 'Comment on essd-2025-257', Anonymous Referee #2, 19 Sep 2025
The manuscript presents a dataset of in situ data of polar stratus clouds collected from a fixed-wing small uncrewed aircraft (SUA) during the Pallas Cloud Experiment (PaCE) 2022 at the Pallas atmosphere-ecosystem super site. The dataset over 39 flights with 84 quasi-vertical profiles includes data on cloud droplet size distributions including derived products (number concentration, liquid water content, effective radius), meteorological variables, and SUA flight data. A quality check was performed on the data and different processing depths (“a1” and “c1”) were applied.
General comments:
- I’m not sure if the dataset now only includes measurements of “arctic warm stratus” (line: 32), or also arctic cold stratus / mixed-phase clouds (line 104: “ice while flying”, line: 136 mixed-phase clouds).
- If you were also measuring mixed-phase clouds and aerosols (line: 53) how did you handle the discrimination between cloud droplets, ice crystals, and aerosols? Also, due to their very different refractive indices that could affect the measurement. This could strongly influence the measure cloud droplet size distribution and derive variables.
If you measure cold cloud or mixed-phase conditions a flag in the data set would be helpful, and some short sentences on how you define these temperature regimes, i.e., using the BME temperature or other instruments. - You could also include a “QA masking impact”, i.e., how much of the respective flight/profile (e.g., the fraction) was masked.
- What is largely missing in the manuscript is a compact uncertainty budget for (a) sizing (e.g., due to refractive-index / model dependence), (b) counting / concentration (e.g., sample volume), (c) LWC (e.g., density assumption, mixed-phase conditions), and (d) airspeed substitutions when the pitot tube froze (e.g., ground-station wind - based correction). Particularly the latter considering the wind speeds were presumably measured on ground level.
- Please extend the analysis part of the data on how the variables are derived from the particle size distribution measurements. Which processes “proc” were actually used.
- Summary/Conclusion: This part is very short and missing an outlook on what the dataset could be used for or how it could support other datasets if used in synergy. Mainly what is the fundamental value for future studies.
Specific comments:
- Line 117-119: This should go into the data analysis part, where you introduce the masks.
- Figure 5: Number concentration of cloud droplets, aerosols or both?
Do you always show the same x-range?
Are the concentration values saturated (e.g., profile 6) or just not displayed due to the x-axis range? - Figure 6: The x-axis label is confusing looks like “510”, please at least include the ticks for every profile. Also here particularly evident is that you need to give some error estimates. Comparing profile 002 with 011 already indicates that due to counting statistics the uncertainty for 002 is higher compared to profile 011.
- Line 120: Level “c1” means that the flight controller data was available and “a1” where it was not available? Please clarify.
- Line 117: What do you mean by “The data level is also included here.” This needs more explanation, what is a data level?
Minor comments:
- Line 44: what is (noa,a) after pitot tube?
- Line 56, 116: what is (noa,b)?
- Line 68: include space between 15° and angle
- Lines 69,70, 99, 100: include small space between unit m\,s
- Line 74: check reference year number
- Line 75: Period missing
- Line 101: remove first “time”
- Table 1: kg\,m^-3
- 115: I thin the company is called Sensirion not Senserion
- 116: Change “Bosh” to “Bosch”
- 119: altitude not attitude :)
- Table 2: define n/a in description (not available vs not applicable)
- Throughout: change in-situ to in situ
Citation: https://doi.org/10.5194/essd-2025-257-RC2 -
RC3: 'Comment on essd-2025-257', Anonymous Referee #3, 01 Oct 2025
The manuscript describes a dataset collected in 2022 to understand cloud microphysics using a small UAS. The article contains useful information regarding the UCASS sensor and the available data. The platform would be beneficial for addressing the data gap in in-situ cloud observations. However, the manuscript lacks some key information about data processing.
General Comments:
I think it would benefit the reader if there was more description about how this article differs and expands upon the work from Girdwood et al. 2022b. As the introduction stands now, I do not see how this dataset is unique or what was learned from the previous campaign.
There should be more description on the data processing mentioned in Software. The authors mention that there is space for customization but do not describe the standard practice used on the dataset herein. Overall, the description of the QA process needs to be expanded. I do not understand the processes which went into creating the c1 level files.
The meteorological observations (T and RH) are mentioned but never described in their data quality or availability. I would imagine condensation on the sensors could pose an issue, but this is not mentioned, nor do we see any examples of meteorological data plotted in the manuscript. Were there any calibration offsets or post-processing to ensure accurate measurements?
The doi links in the Abstract and Data Availability statement do not work.
Specific Comments:
L4: It would be nice to add the year of the Girdwood 2022b campaign to distinguish the two datasets better.
L20: Have there been other UAS to gather cloud physics observations? If so, they should be mentioned in the introduction.
L41: What is (noa, a)?
L44-L47: All of the pointing to references to describe the data processing makes it hard to follow.
L54-56: Are there any differences between these two sensors? Or in their respected data quality?
Fig 3: You might consider adding a satellite image to understand the cloud types and coverage in the flight path.
L102: Are there differences in data quality between ascending profiles and descending? How is the concern for rotor-wash influence on the environment mediated?
L104: This seems like a fundamental issue given the goals of the platform. How often was the pitot tube unusable? Does that reduce the frequency of observations?
L128: Fix the citation
Citation: https://doi.org/10.5194/essd-2025-257-RC3
Data sets
Data From the Universal Cloud and Aerosol Sounding System Abord an Uncrewed Aircraft During the Pallas Cloud Experiment 2022 Jessica Girdwood et al. https://doi.org/10.5281/zenodo.14756233
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The authors present cloud micro-physical measurements taken by the UCASS optical particle spectrometer aboard a small uncrewed aircraft (SUA) during the Pallas Cloud Experiment 2022. The manuscript provides a good overview on the used instrument and data products, and illustrates an example of measurements. I am lacking some information on the retrievals used and a discussion of their uncertainties and limitations. I recommend publication of the manuscript after the following comments have been addressed by the authors.
General comments
mass and number concentration and effective radius (Tab 1) calculated and what errors and limitations arise from the retrievals and assumptions therein? How is phase information taken into account when retrieving in mixed-phase or ice cloud conditions? I would suggest to add a sub-section to either Sec 2 or 3 illustrating this currently missing information on the dataset.
Specific comments
Abstract
Sec 1: Introduction
Sec 2: Methods
Sec 3: Data
Minor xtick labels should be added to all respective flights sub-panels at the bottom. Are all panels showing the same xrange? It would be nice to add ‘10’ and ‘20’ to the top x-ticks.
It seems like lines are connecting points throughout clear air patches (eg Fig 6 profiles 25-28 between 750-1200m). Replacing lines with plotted dots would further illustrate the vertical resolution of the measurements.
Summary
Technical Corrections