<?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-2025-721</article-id>
<title-group>
<article-title>LI-CCR: Dataset of daily lake ice evolution (2002&amp;ndash;2024) across global cold climate regions based on gap-filled MODIS observations</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Jiang</surname>
<given-names>Zhengxin</given-names>
</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>Qiu</surname>
<given-names>Yubao</given-names>
<ext-link>https://orcid.org/0000-0003-1313-6313</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>Leppäranta</surname>
<given-names>Matti</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff4">
<sup>4</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Li</surname>
<given-names>Xiaoting</given-names>
</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>Yao</surname>
<given-names>Peng</given-names>
</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>Jia</surname>
<given-names>Guoqiang</given-names>
</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>Shi</surname>
<given-names>Jiancheng</given-names>
</name>
<xref ref-type="aff" rid="aff5">
<sup>5</sup>
</xref>
</contrib>
</contrib-group><aff id="aff1">
<label>1</label>
<addr-line>Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China</addr-line>
</aff>
<aff id="aff2">
<label>2</label>
<addr-line>International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China</addr-line>
</aff>
<aff id="aff3">
<label>3</label>
<addr-line>College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China</addr-line>
</aff>
<aff id="aff4">
<label>4</label>
<addr-line>University of Helsinki, Helsinki 00014, Finland</addr-line>
</aff>
<aff id="aff5">
<label>5</label>
<addr-line>National Space Science Center, Chinese Academy of Sciences, Beijing 100190, China</addr-line>
</aff>
<pub-date pub-type="epub">
<day>19</day>
<month>01</month>
<year>2026</year>
</pub-date>
<volume>2026</volume>
<fpage>1</fpage>
<lpage>31</lpage>
<permissions>
<copyright-statement>Copyright: &#x000a9; 2026 Zhengxin Jiang 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-2025-721/">This article is available from https://essd.copernicus.org/preprints/essd-2025-721/</self-uri>
<self-uri xlink:href="https://essd.copernicus.org/preprints/essd-2025-721/essd-2025-721.pdf">The full text article is available as a PDF file from https://essd.copernicus.org/preprints/essd-2025-721/essd-2025-721.pdf</self-uri>
<abstract>
<p>Lake ice is an essential component of the terrestrial cryosphere and plays an important role in the socioeconomic and ecological systems of cold regions. However, existing lake ice datasets generally suffer from poor temporal continuity, limited spatial coverage, and a lack of observations for small and medium-sized lakes. Consequently, the global spatial patterns and long-term trends of lake ice have remained insufficiently understood. In this study, using MODIS observations, we developed global datasets of daily lake ice coverage (LIC), annual lake ice-cover status, annual lake ice phenology (LIP), and the probability of complete ice-cover occurrence (PCIO), including 32,800 lakes across global cold climate regions from 2002 through 2024. Validation against multiple remote sensing datasets demonstrated high accuracy and confirmed that our Lake Ice &amp;ndash; Cold Climate Regions dataset (LI-CCR) effectively captures the spatiotemporal evolution of the lake ice zone. Quality assessments were conducted for both LIC and LIP, and the information was included as an integral component of the LI-CCR. The results show that most cold regions lakes in the Northern (Southern) Hemisphere freeze before November (May) and melt from May (November) onward, with an average ice cover duration of about 200 days. Presently 89 % of the lakes experience completely frozen annually, and the number of intermittent or even ice-free lakes is increasing under the warming climate. The LI-CCR dataset provides comprehensive records of lake ice evolution in cold climate regions and offers valuable information for studies on lake&amp;ndash;climate interactions, cryosphere changes, and ecosystem responses. This LI-CCR dataset v2 is freely available from the Zenodo platform at &lt;a href=&quot;https://doi.org/10.5281/zenodo.17687698&quot; target=&quot;_blank&quot; rel=&quot;noopener&quot;&gt;https://doi.org/10.5281/zenodo.17687698&lt;/a&gt; (Jiang et al., 2025b).</p>
</abstract>
<counts><page-count count="31"/></counts>
</article-meta>
</front>
<body/>
<back>
</back>
</article>