Arctic aerosol and meteorological observations using airborne and ground-based systems in spring 2024

Schuchard, Malte; Bärfuss, Konrad; Bretschneider, Lutz; Conrath, Thomas; Held, Andreas; Käthner, Ralf; Kellermann, Mona; Lampert, Astrid; Mathes, Theresa; Müller, Joshua; Pilz, Christian; Schlerf, Andreas; Siebert, Holger; Wehner, Birgit; Harm-Altstädter, Barbara

doi:10.5194/essd-2026-411

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https://doi.org/10.5194/essd-2026-411

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28 Jul 2026

| 28 Jul 2026

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

Arctic aerosol and meteorological observations using airborne and ground-based systems in spring 2024

Malte Schuchard, Konrad Bärfuss, Lutz Bretschneider, Thomas Conrath, Andreas Held, Ralf Käthner, Mona Kellermann, Astrid Lampert, Theresa Mathes, Joshua Müller, Christian Pilz, Andreas Schlerf, Holger Siebert, Birgit Wehner, and Barbara Harm-Altstädter

Abstract. A comprehensive observational data set of the vertical and horizontal distribution of aerosol particles and meteorological parameters is presented. Data were obtained from an Arctic field campaign conducted with three different measurement platforms deployed at distinct locations in Ny-Ålesund, Svalbard, during the transition period from spring to summer between 19 May 2024 and 8 June 2024. The uncrewed aerial system ALADINA was used for vertical and horizontal profiling in the lowermost 930 m above sea level, covering 38 measurement flights including 143 vertical profiles and 62 horizontal flight legs at different constant altitudes. The tethered balloon system BELUGA performed 90 vertical profiles up to a maximum altitude of 1.3 km above sea level. Together, the airborne platforms provide information on particle number concentrations, including ultrafine particles with diameters below 20 nm, size distribution from the nucleation to coarse mode, and meteorological parameters (i.e. temperature, humidity, pressure, wind direction, wind speed, and short-wave irradiance). In addition, a surface flux gradient system was applied for the calculation of turbulent fluxes of sensible heat and vertical motion of particles, covering a sampling time of about 214 h. An illustrative case study is shown for 3 June 2024, highlighting the spatial variability of aerosol particles, which is strongly influenced by the stability of the polar atmospheric boundary layer. The high‐resolution observations enable the study of processes of aerosol–cloud interactions, new particle formation and lead to a generally improved understanding of the spatial distribution of Arctic aerosols. The data of all three measurement platforms are publicly available on the world data centre PANGAEA as described in the data availability section.

Received: 29 May 2026 – Discussion started: 28 Jul 2026

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Status: final response (author comments only)

RC1: 'Comment on essd-2026-411', Anonymous Referee #1, 27 Aug 2026

The manuscript presents a combined observational data set collected during a three-week field campaign (19 May - 8 June 2024) in Ny-Ålesund, Svalbard, using three complementary platforms: the fixed-wing UAS ALADINA and the tethered balloon BELUGA, both profiling aerosol particle number concentration, size distribution and meteorological variables up to 1.3 km, and a near-surface flux-gradient system estimating turbulent sensible heat and particle number fluxes at about 2 m height. The authors describe the instrumentation, calibration and post-processing chain for each platform in detail, provide a campaign-wide overview of data availability and meteorological conditions, and illustrate the combined use of the three data sets with a case study on 3 June 2024, relating vertical and horizontal aerosol variability to boundary-layer stability, advection and surface exchange. The three resulting data sets are archived on PANGAEA with individual DOIs. The paper is intended as a data descriptor for this campaign data set. In its present form, I recommend major revisions according to my comments before the manuscript can be considered for publication in ESSD.
General comments
I have a fundamental reservation about the suitability of this manuscript for ESSD rather than for a methods-oriented outlet such as AMT (Copernicus). The dataset covers a single campaign of about three weeks at one site, with rather modest total sampling volumes once post-processing is applied (20 h for ALADINA, 39 h for BELUGA, 214 h for the surface gradient system; Table 1). ESSD's own editorial statement (Carlson and Oda, 2018) is explicit that a data paper must satisfy a dual criterion: data quality and interest/utility to a sufficiently broad user community, and it contrasts a "small data set collected over a short time at a single location" with genuine community-wide, multi-decadal compilations. I do not think this campaign qualifies as the latter. The dataset is scientifically respectable, but I am not convinced it meets the standard the journal itself sets. I would like to see the authors make an explicit case, in the introduction and conclusions, for why this specific combination of platforms and this specific three-week window constitutes a resource of lasting, broad utility rather than assuming this is self-evident.
The introduction builds an extensive case around pan-Arctic sources, transport pathways and seasonal aerosol regimes (L. 44-53 and surrounding paragraphs), but it does not engage at all with the substantial body of work already carried out specifically at Ny-Ålesund on ultrafine particles, particle size distribution, ice-nucleating particles, CCN and turbulent particle fluxes. Several groups have published extensively on exactly these topics at this site, and I consider their absence a genuine gap in the literature review. It directly affects the "interest and utility" argument, since the authors need to position their new data against what is already known and available for Ny-Ålesund specifically, not only against the generic Arctic picture. I would ask the authors to add this local context and to clarify how the present data set adds to, rather than duplicates, that existing body of Ny-Ålesund observations.
As currently written, roughly half of the manuscript (Sects. 3.1, 3.2, 3.3) reads as a sensor-development and calibration paper, not a data descriptor. Section 3.1.1 ("Platform and instrumentation", L. 180 onward) is the clearest example: it goes into a level of technical detail - telemetry frequencies, battery-swap logistics, sensor mounting geometry - that in my reading has, in all likelihood, already been published by the same authors elsewhere. The same applies to the derivations in Sect. 3.1.2 (the inverted first-order transfer function and phase-neutral filtering for TSYS01, the Arrhenius-type temperature dependence of the HMP110 time constant in Eq. 1/Fig. 5b, the geometric treatment of wind-direction uncertainty in Fig. 5a, and the Mach-number-based static-temperature correction). This is methodological material of the kind AMT exists for, and in several cases, it is already covered by citable companion papers (Bärfuss et al., 2023; Pilz et al., 2022; Mathes et al., 2025a). Before revising, I would ask the authors to check ESSD's own guidance on what level of instrumental/methodological detail a data descriptor is actually expected to carry (Sect. 3.4 of Carlson and Oda asks for enough detail "to allow readers to replicate the analysis", not a re-derivation of the underlying physics) and compress accordingly, moving material that is not novel to this dataset into a supplement or handling it by citation.
According ESSD's explicit open-format requirement (Sect. 3.1 of Carlson and Oda), the data availability section (Sect. 6) must state the file format(s) delivered (netCDF, csv, …) and be self-sufficient for a user with no other access to the manuscript. As it stands, Sect. 6 gives only the three PANGAEA DOIs and one sentence per data set; it does not state file formats, variable-naming conventions, or whether the three data sets share a common time base/geolocation convention that would let a user combine them (which is, after all, the entire scientific rationale of the paper). I would ask for this to be expanded.
David Carlson and Tomohiro Oda. Data publication – ESSD goals, practices and recommendations. Earth Syst. Sci. Data, 10, 2275–2278, 2018. https://doi.org/10.5194/essd-10-2275-2018, 2018

Specific comments
240 - 337 (Sect. 3.1.2), Fig. 4, Fig. 5, Fig. 6. In particular, the derivation of the solar-heating bias correction (L. 258 - 271) and the Arrhenius fit for the HMP110 (L. 284 - 298, Eq. 1, Fig. 5b) are original methodological contributions that deserve to be a citable AMT-type reference in their own right, not embedded prose in a data descriptor. If these corrections are indeed novel here (not already described in Bärfuss et al., 2023), that is precisely the argument for publishing them separately with proper methodological peer review, rather than as a paragraph inside a data paper.
150 - 152, "as well as snow height measured at the Bayelva research site" (Boike et al., 2018, 2022). Snow height measured at Bayelva can differ considerably from snow height at the centre of the Ny-Ålesund village itself, given the heterogeneous, patchy melt described by the authors themselves in Sect. 2.1. Other snow-height records for the immediate research area may exist and be more representative of the conditions sampled especially by the gradient system. The authors should clarify exactly how this variable is used in the subsequent analysis (it only appears qualitatively in Fig. 2c) and justify why the Bayelva record, 3 km away, is an adequate proxy for the campaign area rather than just the most convenient one.
Sect. 3.2.1 (BELUGA) / Sect. 3.3.1 (gradient system). Same concern as above: the level of detail on box construction (side length, insulation thickness, heating set point), inlet geometry, and flow-rate specifications exceeds what a data user needs and duplicates Pilz et al. (2022) and Mathes et al. (2025a).
Sect. 3.3.2, u* ≥ 0.15 m/s and R² ≥ 0.5 QC thresholds (L. 553–558). This is exactly the kind of explicit, quantitative QC criterion ESSD wants (cf. Carlson and Oda, Sect. 3.6) - good. Please also report, either here or in Table 1/Sect. 6, how many of the total 20-min flux intervals pass both thresholds, since this determines the effective size of the usable flux data set and is currently not stated anywhere.
Minor comments
Fig. 1 caption / L. 100 - 102. The caption states that ground-based stations shown as white dots "include the Zeppelin Observatory, Gruvebadet Atmosphere Laboratory, the Bayelva research site and the AWIPEV Research Base." I checked panels (a) and (b) and the AWIPEV Research Base is not shown/labelled in the figure at all, despite being listed in the caption. Please add the marker or correct the caption.
Fig. 2 caption: "in 2 h median intervals" - please confirm this applies only to the last two panels equally, since panel (a) shows discrete flight bars rather than a continuous median series.

Citation: https://doi.org/10.5194/essd-2026-411-RC1
RC2:
'Comment on essd-2026-411', Anonymous Referee #2, 30 Aug 2026
Review of “Arctic aerosol and meteorological observations using airborne and ground-based systems in spring 2024” by Schuchard et al. (essd-2026-411)
General assessment
This manuscript presents an extensive dataset of aerosol and meteorological observations obtained with the fixed-wing UAS ALADINA, the tethered-balloon system BELUGA, and a surface flux-gradient system during spring 2024 in Ny-Ålesund. The manuscript is generally well written and clearly structured. The authors have done a good job describing the platforms, instrumentation, measurement strategy, data processing and quality-control procedures. The combination of repeated vertical profiles, horizontal flight legs, aerosol size distributions and near-surface flux measurements represents a valuable dataset for studies of the Arctic atmospheric boundary layer.
Nevertheless, I believe that major revision is required before publication. My principal concern is that the quality assessment relies predominantly on laboratory calibrations and internal comparisons, whereas the connection to the extensive reference measurements available around Ny-Ålesund is largely missing. Consequently, the manuscript demonstrates that the airborne systems behave reasonably and produce internally consistent patterns, but it provides limited evidence for the absolute accuracy and comparability of the resulting aerosol and meteorological measurements under field conditions. I will only support the reviewer #1 comments about the data descriptor, but I still think the dataset is of high value and interest within the community.
Major comments

Comparison with reference measurements around Ny-Ålesund

Ny-Ålesund offers an unusually comprehensive measurement infrastructure, including the AWIPEV meteorological observations, the Zeppelin Observatory, Gruvebadet Atmosphere Laboratory and the Bayelva site. These stations are introduced in Sect. 2.1 and shown in Fig. 1, but their measurements are not used for field validation of the new datasets.
Laboratory calibration is essential, but it does not fully test the complete measurement chain under flight conditions. This includes inlet aspiration and transmission, tubing losses, flow stability, sensor ventilation, radiative effects, pressure and temperature dependence, response-time corrections and potential platform contamination.
I therefore strongly recommend comparing the airborne observations with temporally overlapping reference measurements. For example:

Near-surface ALADINA and BELUGA temperature, humidity, pressure and wind measurements could be compared with AWIPEV station or mast observations.

Aerosol particle number concentrations and size distributions could be compared with concurrent CPC, SMPS, NAIS or related observations at Gruvebadet and, where appropriate, Zeppelin.

Selected periods when ALADINA and BELUGA operated simultaneously could be used for direct comparisons at similar altitudes, even if the platforms were at somewhat different horizontal locations.

Comparisons should preferably include bias, scatter, correlation, number of matched observations and the expected uncertainty or representativeness range.

I recognise that differences are expected because the platforms and stations were not collocated and because the complex local topography can generate genuine spatial variability. These limitations should be quantified and discussed rather than used as a reason to omit the comparison. Even comparisons restricted to take-off, landing, near-surface balloon measurements or suitably selected wind sectors would considerably improve confidence in the absolute values.
This is particularly important for a data paper. Without such comparisons, much of the interpretation remains based on relative changes within each platform rather than demonstrating traceability and comparability of the reported values.

Aerosol inlet, aspiration and transmission efficiencies

The description of aerosol sampling is not yet sufficient to assess the representativeness of the aerosol data. Please provide, for ALADINA and all BELUGA aerosol payloads:

inlet geometry, diameter and orientation;

total and instrument-specific flow rates;

inlet velocity relative to aircraft or balloon airflow;

whether sampling is isoaxial and approximately isokinetic;

lengths, internal diameters and materials of sampling tubes;

residence times;

bends, flow splits and bypass flows;

aerosol drying or other sample conditioning;

calculated or measured size-dependent aspiration and transmission efficiencies;

treatment of diffusion, sedimentation, inertial, bend and electrostatic losses; and

information on whether corrections were applied to the archived data.

For ALADINA, the reported mean sampling-efficiency factor of 1.05 applies only between 40 and 500 nm. It therefore does not cover the smallest particles measured by the CPCs, whose lower cut-offs are 6 and 19 nm, or the coarse fraction measured by the OPC up to 10 µm. At an aircraft speed of approximately 28 m s−1, aspiration and orientation effects may be particularly important for the coarse-particle channels.
The same issue applies to the funnel inlets used by CAMP and mSEMS. The manuscript should state how the inlet geometry and balloon motion affect sampling. The downward-facing inlet of the surface gradient system should also be justified, including its potential effect on sampling larger particles.
If a complete inlet characterisation has been published previously, the relevant results should be briefly summarised here and the appropriate references provided. The reader should not have to infer the applicable particle-size range and sampling efficiency from several previous publications.

HMP110 response time and humidity reconstruction

Figure 5b indicates an HMP110 time constant reaching approximately 160 s. This appears very long relative to an ALADINA ascent or descent lasting about 7 min. Based on a 930 m profile completed in approximately 420 s, the mean vertical speed is about 2.2 m s−1. A time constant of 160 s would therefore correspond to a characteristic vertical response distance of roughly 350 m before reconstruction. Sharp features such as cloud boundaries, inversion layers or humidity gradients could be strongly displaced and attenuated.
The use of an inverse transfer function may partly reconstruct the signal, but it may also amplify noise and cannot necessarily recover atmospheric structure that the sensor did not resolve. Please:

explain more clearly how the temperature-dependent time constants were determined;

provide the range of derived time constants and the number of flights used;

quantify the resulting effective temporal and vertical resolution;

demonstrate that the reconstructed profiles are stable and not dominated by inversion artefacts;

validate the reconstructed humidity against the Rapid P14 and, where possible, against surface or radiosonde measurements; and

discuss the uncertainty and usefulness of flights for which only the reconstructed HMP110 measurement is available.

PANGAEA data and metadata

I checked the three PANGAEA records listed in the Data availability section:

ALADINA: https://doi.org/10.1594/PANGAEA.988207

BELUGA: https://doi.org/10.1594/PANGAEA.988353

Surface flux-gradient system: https://doi.org/10.1594/PANGAEA.984519

The records are accessible and generally well organised. They contain dataset-level citations, temporal and geographical coverage, instruments, variable names, units, events, licences and downloadable tab-delimited data. ALADINA is organised into 38 flight datasets, BELUGA into 23 flight datasets, and the gradient-system record contains processed profile and flux datasets.
However, several improvements are needed to make the datasets fully self-describing and independently reusable:
a. The ALADINA metadata state that the detailed system and processing description will be provided by “Schuchard et al. (in preparation)”. This should be updated to cite and link the present manuscript.
b. The gradient-system metadata contain an apparent incorrect reference to “spring 2025”, although the campaign occurred in 2024.
c. The same gradient-system metadata state in one place that measurements were made at five heights and elsewhere list six heights. This should be made consistent. If at least five of six levels were required for a valid profile, this distinction should be stated explicitly.
d. Quality-control information is uneven. BELUGA includes a temperature quality flag, but equivalent information describing the validity of aerosol data, wind data, solar-heating effects and other exclusions is not consistently available. ALADINA does not appear to provide explicit quality flags or flight-phase classifications, although substantial filtering and exclusion of manoeuvres are described in the manuscript.
e. Users should be able to identify vertical profiles, ascents, descents and horizontal flight legs without reconstructing these phases entirely from position and attitude data. I recommend including a measurement-phase or profile identifier, particularly for ALADINA and BELUGA.
f. The metadata or an accompanying README should clearly define whether each aerosol concentration is reported at ambient or standard conditions, which corrections have already been applied, the meaning of missing values, applicable uncertainty, lower and upper cut-offs, and whether particle size distributions are expressed as dN/dlogDp.
g. For BELUGA, the distinction between the altitude of TMP and the aerosol payload located 10 m below it is documented, but it would be preferable to provide the appropriate altitude explicitly for each measurement stream instead of requiring users to subtract 10 m.
h. Versioning should be checked. The ALADINA datasets refer to different parameter-table versions. The meaning of these versions and any differences among flights should be documented.
Overall, the PANGAEA metadata provide a good foundation, but the identified inconsistencies and missing quality-control details should be corrected before final publication.
Specific comments

Lines 55–60: Please provide references supporting the discussion of the extent and limitations of crewed aircraft observations in the Arctic.

Lines 64–68: The combination of UAS, tethered balloons and ground observations is not entirely new. Please cite previous multi-platform studies and clarify the specific novelty of the present campaign and dataset.

Figure 1: Panel (b) should include appropriate copyright and attribution information, consistently with panel (a).

Lines 120–121: Please explain the specific safety risk that required operations to remain outside clouds. Were supercooled clouds and icing expected, or was the restriction mainly intended to protect the instrumentation and maintain visual or operational safety? The present wording is too general.

ALADINA should be expanded at its first occurrence, including in the abstract or introduction, rather than only in Sect. 3.1.

Table 2: Please specify whether the stated CPC and OPC uncertainties refer to particle number concentration, particle sizing, or both. For the OPC, sizing and counting uncertainties should ideally be distinguished.

Lines 235–239: The wording implies a common controlled flow through all particle counters. Please provide the actual total flow and the flow through each individual CPC and OPC, together with the arrangement of flow splits.

Lines 281–299 and Fig. 5b: Please address the concern about the HMP110 response time and reconstructed vertical resolution, as discussed in Major Comment 3.

Lines 325–336: Please expand the description of aerosol sampling efficiency and losses, as discussed in Major Comment 2. A single correction factor for 40–500 nm is insufficient to characterise measurements spanning approximately 6 nm to 10 µm.

BELUGA should also be expanded at its first occurrence in the manuscript.

Lines 428–430: Please retain alphabetical ordering of citations, consistent with the rest of the manuscript; Tuch et al. should precede Wiedensohler et al.

Lines 430–435: The CPC flow was strongly modified from the manufacturer’s nominal value of approximately 0.7 L min−1 to approximately 0.11 L min−1. Please explain more rigorously how calibration against the electrometer compensates for this modification. The statement that the calibration includes “additional, unknown corrections” is not sufficiently transparent for a data paper.

Lines 444–446: Please clarify whether the factors 1.05 and 0.94 were obtained directly from laboratory comparison with an electrometer reference and whether they combine plateau efficiency and sampling losses. The size dependence of these corrections should be given.

Lines 457–460: Is the mSEMS correction factor of 0.72 applied uniformly to all scanned size channels? Please distinguish CPC detection efficiency from inlet and transport losses and state how size-dependent sampling losses are treated.

Lines 475–477 and Fig. 9d: The surface-system inlet appears to point downward. Please explain why this orientation was selected and discuss its potential influence on aspiration and sampling of larger particles.

Line 570: “starting at 00 UTC” appears incomplete or inconsistent with the other time notation. Consider “starting at 00:00 UTC”.

Recommendation
The dataset has clear scientific value, and the manuscript provides a strong description of the three measurement systems. However, field comparison against available reference observations, more complete aerosol-inlet characterisation, clarification of the humidity reconstruction, and correction and expansion of the repository metadata are necessary before the absolute reliability and reusability of the data can be adequately assessed. I therefore recommend major revision.
Citation: https://doi.org/10.5194/essd-2026-411-RC2

Data sets

Airborne measurements of Arctic aerosol and meteorological parameters using the UAV ALADINA in Ny-Ålesund during melting season in May/June 2024 [dataset publication series]. Malte Schuchard, Konrad Bärfuss, Lutz Bretschneider, Ralf Käthner, Astrid Lampert, Christian Pilz, Andreas Schlerf, and Barbara Harm-Altstädter https://doi.org/10.1594/PANGAEA.988207

Tethered balloon-borne measurements of meteorological and aerosol microphysical properties during the Arctic melt season 2024 [dataset bundled publication]. Mona Kellermann, Thomas Conrath, Ralf Käthner, Theresa Mathes, Joshua Müller, Christian Pilz, Birgit Wehner, Malte Schuchard, and Holger Siebert https://doi.org/10.1594/PANGAEA.988353

Particle flux-gradient relationships for the expedition AIDA, Ny Alesund, 2024 [dataset bundled publication]. Theresa Mathes, Christian Pilz, Louisa-Marie Otterbach, Birgit Wehner, and Andreas Held https://doi.org/10.1594/PANGAEA.984519

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This article combines measurements from an uncrewed aerial system, a tethered balloon system and a surface flux gradient system to study aerosol particles and meteorological parameters at the Arctic site Ny-Ålesund, Svalbard, in spring 2024. The vertical and horizontal observations from the ground to 1.3 kilometres above sea level show strong aerosol variability in correlation with specific meteorological conditions, providing a valuable basis for understanding Arctic aerosol processes.


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