<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE article PUBLIC "-//NLM//DTD Journal Publishing DTD v3.0 20080202//EN" "https://jats.nlm.nih.gov/nlm-dtd/publishing/3.0/journalpublishing3.dtd">
<article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" article-type="data-paper" specific-use="SMUR" dtd-version="3.0" xml:lang="en">
<front>
<journal-meta>
<journal-id journal-id-type="publisher">ESSDD</journal-id>
<journal-title-group>
<journal-title>Earth System Science Data Discussions</journal-title>
<abbrev-journal-title abbrev-type="publisher">ESSDD</abbrev-journal-title>
<abbrev-journal-title abbrev-type="nlm-ta">Earth Syst. Sci. Data Discuss.</abbrev-journal-title>
</journal-title-group>
<issn pub-type="epub">1866-3591</issn>
<publisher><publisher-name></publisher-name>
<publisher-loc>Göttingen, Germany</publisher-loc>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.5194/essd-2026-192</article-id>
<title-group>
<article-title>An airborne in-situ dataset of cloud microphysical properties in supercooled large droplet icing conditions</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Menekay</surname>
<given-names>Deniz</given-names>
<ext-link>https://orcid.org/0009-0003-1111-2745</ext-link>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Lucke</surname>
<given-names>Johannes</given-names>
<ext-link>https://orcid.org/0000-0001-6724-864X</ext-link>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Jurkat-Witschas</surname>
<given-names>Tina</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Voigt</surname>
<given-names>Christiane</given-names>
<ext-link>https://orcid.org/0000-0001-8925-7731</ext-link>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Kirschler</surname>
<given-names>Simon</given-names>
<ext-link>https://orcid.org/0000-0003-4232-8277</ext-link>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Bourdon</surname>
<given-names>Aurélien</given-names>
</name>
<xref ref-type="aff" rid="aff4">
<sup>4</sup>
</xref>
</contrib>
</contrib-group><aff id="aff1">
<label>1</label>
<addr-line>Institute of Atmospheric Physics, German Aerospace Center (DLR), Oberpfaffenhofen, Germany</addr-line>
</aff>
<aff id="aff2">
<label>2</label>
<addr-line>Institute of Atmospheric Physics, Johannes Gutenberg University Mainz, Mainz, Germany</addr-line>
</aff>
<aff id="aff3">
<label>3</label>
<addr-line>Institute of Astronomical and Physical Geodesy, Technical University of Munich (TUM), Munich, Germany</addr-line>
</aff>
<aff id="aff4">
<label>4</label>
<addr-line>The French facility for airborne research (SAFIRE), Météo-France, CNRS, CNES, Cugnaux, France</addr-line>
</aff>
<pub-date pub-type="epub">
<day>26</day>
<month>03</month>
<year>2026</year>
</pub-date>
<volume>2026</volume>
<fpage>1</fpage>
<lpage>26</lpage>
<permissions>
<copyright-statement>Copyright: &#x000a9; 2026 Deniz Menekay et al.</copyright-statement>
<copyright-year>2026</copyright-year>
<license license-type="open-access">
<license-p>This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this licence, visit <ext-link ext-link-type="uri"  xlink:href="https://creativecommons.org/licenses/by/4.0/">https://creativecommons.org/licenses/by/4.0/</ext-link></license-p>
</license>
</permissions>
<self-uri xlink:href="https://essd.copernicus.org/preprints/essd-2026-192/">This article is available from https://essd.copernicus.org/preprints/essd-2026-192/</self-uri>
<self-uri xlink:href="https://essd.copernicus.org/preprints/essd-2026-192/essd-2026-192.pdf">The full text article is available as a PDF file from https://essd.copernicus.org/preprints/essd-2026-192/essd-2026-192.pdf</self-uri>
<abstract>
<p>Detailed and comprehensive data sets on microphysical cloud properties in icing conditions are rare. In April 2023, fifteen research flights were performed with the SAFIRE ATR 42 research aircraft during the SENS4ICE-EU airborne measurement campaign over France and adjacent marine regions to measure clouds containing supercooled large droplets (SLD) at altitudes between 2 and 6 km and temperatures of 0 to -18 &amp;deg;C. Ten cloud probes were deployed on the aircraft, comprising four imaging probes, two light-scattering probes, and three hotwire probes, in order to characterise natural SLD conditions and to test newly developed icing detection sensors. This work presents a comprehensive cloud dataset derived from the in-situ instruments used during the campaign, which is accessible on the HALO (High Altitude and Long Range Research Aircraft) database. The dataset includes measurements of liquid and ice water content, combined particle size distributions, cloud microphysical properties, and meteorological parameters relevant to icing environments. In addition to documenting the dataset structure and processing methods, the paper provides an overview of flight strategies, instrument configurations, and statistical characteristics of the observed cloud properties, including their dependence on temperature and altitude. The dataset is suitable for studies of atmospheric icing conditions, mid-level clouds, sensor development, and model evaluation. It represents a rare collection of in-situ observations of SLD characteristics in icing environments and supports the evaluation of numerical weather prediction models under icing conditions to improve weather forecasts in hazardous conditions.</p>
</abstract>
<counts><page-count count="26"/></counts>
<funding-group>
<award-group id="gs1">
<funding-source>Horizon 2020</funding-source>
<award-id>824253</award-id>
</award-group>
<award-group id="gs2">
<funding-source>Deutsche Forschungsgemeinschaft</funding-source>
<award-id>522359172</award-id>
</award-group>
</funding-group>
</article-meta>
</front>
<body/>
<back>
</back>
</article>