Small Uncrewed Aircraft Based Microphysical Measurements of Polar Stratus Cloud During The Pallas Cloud Experiment 2022

Girdwood, Jessica; Brus, David; Doulgeris, Konstantinos-Matthaios; Böhmländer, Alexander

doi:https://doi.org/10.5194/essd-2025-257

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https://doi.org/10.5194/essd-2025-257

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11 Aug 2025

| 11 Aug 2025

Status: this preprint is currently under review for the journal ESSD.

Small Uncrewed Aircraft Based Microphysical Measurements of Polar Stratus Cloud During The Pallas Cloud Experiment 2022

Jessica Girdwood, David Brus, Konstantinos-Matthaios Doulgeris, and Alexander Böhmländer

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).

Received: 02 May 2025 – Discussion started: 11 Aug 2025

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Jessica Girdwood, David Brus, Konstantinos-Matthaios Doulgeris, and Alexander Böhmländer

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RC1:
'Comment on essd-2025-257', Anonymous Referee #1, 05 Sep 2025 reply
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
Sec 3.2 “Data Analysis and QA”: The data analysis part of this Section is very short. I would suggest to add a separate Section 4 titled e.g. “Overview of Cloud Properties” summarizing the measured properties that the title of the manuscript advertises. Within this Section, more general information on the cloudy conditions should be presented, e.g. by summarizing where (geographically; also with respect to cloud base and top) clouds were profiled; if the whole cloud layer or only parts of it were measured, and where profiling relative to cloud base and top was performed; how does the data set fits in with other cloud data sets obtained during the campaign? How did profiles of the same cloud vary within one flight? What are the errors of the retrieved variables?

I am missing an overview and discussion of the retrievals applied to the measurements. How are the variables

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
Line 2: add […] super site during the Pallas Cloud Experiment (PACE) in Autumn 2022.

L 4: How did measurements differ compared to previous data sets taken? (also see next comment)

Sec 1: Introduction
An additional paragraph is necessary to introduce the PACE experiment in more detail to the reader. Information should be added on other cloud measurements, previous in-situ observations within the PACE experiments, and how this dataset differs to previous ones.

L10: rather: Earth system models

L 11, ff: references given should be more specific and target gaps in the knowledge of clouds specifically observed at the PACE site.

L 13: also see comment above; which cloud processes are targeted with the measurements taken?

L 14: „One of the reasons for this“: unclear to what this is referring to

L 22: A short paragraph on the UCASS system should be added here to introduce it to the reader, including framing the system within other similar SUA systems. Some of the information given L 30 ff could be moved to an earlier stage of the manuscript.

Sec 2: Methods
Section title might be misleading. I would rather propose “Instrument and Flight strategy” as a title.

L 41, 56, 116: abbreviation (noa, b) needs to be explained

See GC2: a sub-section explaining the retrievals in more detail should be added here or in Sec 3.

Fig 3: it would be nice for the reader to get an understanding on where all flights were generally taking place. Is the selected plotted flight a random or representative example of the flight trajectory? It would be nice to see all flights on one map, e.g. color-coded by flight number; alternatively, if the plot gets too busy, a selection of representative or highlight flights could be added which could then be illustrated further in new Section 4 (see GC 1), including an illustration of how variable conditions were from profile to profile within the same flight. Additionally, an illustration of the vertical flight trajectories e.g. in a sub-figure (b) would add valuable information to the flight strategy.

Sec 3: Data
L 80: the global time step was set to 0.5s. What vertical and horizontal resolution, respectively, do the output variables have due to this averaging applied, and how does it change throughout the vertical profiles illustrated in Figs 5+6? This information would also be important to discuss in the Results Section (see GC 1)

L 87: “using one of a number of algorithms” should be specified in more detail; which ones were used? References should be added.

L 93: only discuss QA here (see general comment 1)

L 95: unspecific; constraints and limitations should be further discussed e.g. in previous Section

L 100: how were the threshold values chosen, and what uncertainty do they introduce to the masking?

L 101: unclear, sentence should be double-checked

L 103, 107: wind direction and speed were taken from Sammaltunturi station. From Fig 3, it seems like the flights were operated >3km away from the station. Were wind measurements only taken at ground? The authors should discuss in more detail how the wind information error due to the distance and orography affects processing, retrievals and data uncertainty.

Fig 5, 6: what is the minimal height that the instruments operate at? The plot seems to start around 400m; is this a system limitation or due to the observed cloud conditions or orography? Information should be added on where the particles were collected with respect to the cloud boundaries (see GC 2).

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.

Tab 2: Information on how long each flight lasted should be added. More information on the meaning of airspeed type ‘normal’ vs ‘corrected’ is needed in the text.

L 123 (also see GC 1): how variable are profiles change within each flight and how far spaced geographically?

Summary
A more concise outlook should be added to how this data set will be used in the future with respect to the questions and research areas raised in the introduction (L 12-14), and within other PACE measurements and modeling activities.

Technical Corrections
L 74: reference incomplete

L 94: spell out QA in Section title

L 109: Section title on new page

L 115, 116: what do ‘SHT’, ‘BME’, ‘AG’ stand for?

Fig 5, 6: top x-ticks don’t need 0 to match numbers given in Tab 2

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Citation: https://doi.org/10.5194/essd-2025-257-RC1
RC2:
'Comment on essd-2025-257', Anonymous Referee #2, 19 Sep 2025 reply
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

Reply
Citation: https://doi.org/10.5194/essd-2025-257-RC2

Jessica Girdwood, David Brus, Konstantinos-Matthaios Doulgeris, and Alexander Böhmländer

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

Jessica Girdwood, David Brus, Konstantinos-Matthaios Doulgeris, and Alexander Böhmländer

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Short summary

In-situ data of cloud microphysics is essential for targeted studies of cloud processes, validating remote sensing, and both assessing and improving the accuracy of weather and climate models. In this work we adopt a novel technique using a small uncrewed aircraft (SUA) and a bespoke sensor to produce vertical profiles of cloud microphysical parameters. The data are publicly available from https://zenodo.org/records/14756233.


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