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<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-2025-726</article-id>
<title-group>
<article-title>A Forty-Four-Year Comprehensive Dataset of Maize Phenology in China&apos;s Huang-Huai-Hai Plain</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Zhang</surname>
<given-names>Quanjun</given-names>
<ext-link>https://orcid.org/0000-0001-6087-3928</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>Wu</surname>
<given-names>Dongli</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>Cheng</surname>
<given-names>Zhaojin</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
</contrib>
</contrib-group><aff id="aff1">
<label>1</label>
<addr-line>Meteorological Observation Centre, China Meteorological Administration, Beijing, China</addr-line>
</aff>
<aff id="aff2">
<label>2</label>
<addr-line>Rizhao Meteorological Bureau of Shandong Province, Rizhao, China</addr-line>
</aff>
<pub-date pub-type="epub">
<day>13</day>
<month>02</month>
<year>2026</year>
</pub-date>
<volume>2026</volume>
<fpage>1</fpage>
<lpage>18</lpage>
<permissions>
<copyright-statement>Copyright: &#x000a9; 2026 Quanjun Zhang 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-2025-726/">This article is available from https://essd.copernicus.org/preprints/essd-2025-726/</self-uri>
<self-uri xlink:href="https://essd.copernicus.org/preprints/essd-2025-726/essd-2025-726.pdf">The full text article is available as a PDF file from https://essd.copernicus.org/preprints/essd-2025-726/essd-2025-726.pdf</self-uri>
<abstract>
<p>The dataset presents a FAIR (Findable, Accessible, Interoperable, and Reusable), comprehensive, long-term dataset documenting maize phenology dynamics across China&apos;s Huang-Huai-Hai Region (HHHP), a critical area for national grain production. Spanning the period 1981&amp;ndash;2024, the dataset integrates observations from 101 agrometeorological stations across eight provinces and municipalities, capturing ten key phenological stages&amp;mdash;from sowing to maturity&amp;mdash;and deriving four critical growth lengths. A multi-tiered quality control protocol, including automated consistency checks, climate data cross-referencing, and expert arbitration, was applied to ensure data integrity. Analytical outputs include kernel density estimation for characterizing probability distributions and univariate linear regression for quantifying decadal trends. The dataset comprises 1,616 diagnostic plots in JPEG format and two core data tables in XLSX format, with a total uncompressed volume of 1.50 GB.&lt;/p&gt;
&lt;p&gt;The dataset is publicly available via the Science Data Bank under the accession code &lt;a href=&quot;https://doi.org/10.57760/sciencedb.32076&quot; target=&quot;_blank&quot; rel=&quot;noopener&quot;&gt;https://doi.org/10.57760/sciencedb.32076&lt;/a&gt; and supports diverse applications in climate impact assessment, crop model improvement, and adaptation strategy development.</p>
</abstract>
<counts><page-count count="18"/></counts>
</article-meta>
</front>
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