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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>
<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-2026-866</article-id>
<title-group>
<article-title>A high-resolution dataset of pre-rainfall low-level vertical wind shear derived from radar wind profilers across China</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Li</surname>
<given-names>Ning</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>Zheng</surname>
<given-names>Yongguang</given-names>
</name>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Xu</surname>
<given-names>Hui</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>Chen</surname>
<given-names>Tianmeng</given-names>
<ext-link>https://orcid.org/0000-0002-1564-7013</ext-link>
</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>Guo</surname>
<given-names>Xiaoran</given-names>
</name>
<xref ref-type="aff" rid="aff5">
<sup>5</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Zhao</surname>
<given-names>Linxi</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>Sun</surname>
<given-names>Yuping</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>Cai</surname>
<given-names>Xuewei</given-names>
</name>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Yang</surname>
<given-names>Honglong</given-names>
</name>
<xref ref-type="aff" rid="aff4">
<sup>4</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Zeng</surname>
<given-names>Liping</given-names>
</name>
<xref ref-type="aff" rid="aff5">
<sup>5</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Guo</surname>
<given-names>Jianping</given-names>
<ext-link>https://orcid.org/0000-0001-8530-8976</ext-link>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff4">
<sup>4</sup>
</xref>
<xref ref-type="aff" rid="aff6">
<sup>6</sup>
</xref>
</contrib>
</contrib-group><aff id="aff1">
<label>1</label>
<addr-line>State Key Laboratory of Severe Weather Meteorological Science and Technology &amp;  Specialized Meteorological Support Technology Research Center, Chinese Academy  of Meteorological Sciences, Beijing 100081, China</addr-line>
</aff>
<aff id="aff2">
<label>2</label>
<addr-line>College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing 100049, China</addr-line>
</aff>
<aff id="aff3">
<label>3</label>
<addr-line>National Meteorological Centre, Beijing 100081, China</addr-line>
</aff>
<aff id="aff4">
<label>4</label>
<addr-line>CMA Field Scientific Experiment Base for Low-Altitude Economy Meteorological Support of Unmanned Aviation in Guangdong-Hong Kong-Macao Greater Bay Area,  Shenzhen 518108, China</addr-line>
</aff>
<aff id="aff5">
<label>5</label>
<addr-line>Meteorological Observation Centre of China Meteorological Administration, Beijing 100081, China</addr-line>
</aff>
<aff id="aff6">
<label>6</label>
<addr-line>Guizhou New Meteorological Technology Co., Ltd, Guiyang, China</addr-line>
</aff>
<pub-date pub-type="epub">
<day>04</day>
<month>11</month>
<year>2026</year>
</pub-date>
<volume>2026</volume>
<fpage>1</fpage>
<lpage>32</lpage>
<permissions>
<copyright-statement>Copyright: &#x000a9; 2026 Ning Li 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-2026-866/">This article is available from https://essd.copernicus.org/preprints/essd-2026-866/</self-uri>
<self-uri xlink:href="https://essd.copernicus.org/preprints/essd-2026-866/essd-2026-866.pdf">The full text article is available as a PDF file from https://essd.copernicus.org/preprints/essd-2026-866/essd-2026-866.pdf</self-uri>
<abstract>
<p>Favorable low-level vertical wind shear (VWS) is an important dynamic feature conducive to rainfall development. However, continuous observations capable of resolving the fine-scale vertical structure and rapid pre-rainfall evolution of VWS remain limited. To address this observational gap, we developed a high-resolution low-level VWS dataset from wind measurements collected by a network of 28 radar wind profiler (RWP) stations across China during 2023&amp;ndash;2025, with a focus on the 2 h preceding rainfall onset. The dataset provides bulk VWS for both the fixed 0.6&amp;ndash;3.0 km layer and arbitrary combinations of vertical levels, local layer VWS, layer-mean VWS, maximum VWS, and the altitude of maximum VWS, with a temporal resolution of 6 min and a vertical resolution of 120 m over 0.6&amp;ndash;4.08 km AGL. Comparison with collocated radiosonde measurements supports the reliability of the RWP-derived VWS, while comparison with ERA5 shows that the reanalysis underestimates localized maximum VWS and does not reproduce its rapid minute-scale evolution. Non-HR events are generally associated with stronger but relatively steady background VWS, whereas HR events show a pronounced nonlinear increase in local low-level VWS during approximately the final 30 min before rainfall onset. The latter is accompanied by an upward shift in the altitude of maximum VWS, indicating a redistribution of the strongest shear within the lower troposphere. These contrasting evolution patterns demonstrate the ability of the dataset to resolve transient and vertically localized changes in pre-rainfall dynamic environments that are not adequately represented by coarser-resolution reanalysis data. The dataset is publicly available at &lt;a href=&quot;https://doi.org/10.5281/zenodo.23432237&quot; target=&quot;_blank&quot; rel=&quot;noopener&quot;&gt;https://doi.org/10.5281/zenodo.23432237&lt;/a&gt; (Li and Guo, 2026), which can serve as a valuable benchmark for diagnosing pre-rainfall dynamic environments to advance regional HR nowcasting. Accordingly, to realize such forecasting improvements, we must leverage fine-scale dynamic structures derived from RWP measurements for more complete characterizations of prestorm environments.</p>
</abstract>
<counts><page-count count="32"/></counts>
<funding-group>
<award-group id="gs1">
<funding-source>National Natural Science Foundation of China</funding-source>
<award-id>42325501</award-id>
</award-group>
</funding-group>
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