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<front>
<journal-meta>
<journal-id journal-id-type="publisher">EGUsphere</journal-id>
<journal-title-group>
<journal-title>EGUsphere</journal-title>
<abbrev-journal-title abbrev-type="publisher">EGUsphere</abbrev-journal-title>
<abbrev-journal-title abbrev-type="nlm-ta">EGUsphere</abbrev-journal-title>
</journal-title-group>
<publisher><publisher-name>Copernicus Publications</publisher-name>
<publisher-loc>Göttingen, Germany</publisher-loc>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.5194/egusphere-2026-5470</article-id>
<title-group>
<article-title>Quantifying daily aerosol direct radiative effects in mainland China using a weather-aerosol normalized machine learning framework based on observational data, 1993&amp;minus;2020</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Li</surname>
<given-names>Zhigang</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>Shi</surname>
<given-names>Haoze</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Ji</surname>
<given-names>Chao</given-names>
</name>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
</contrib>
</contrib-group><aff id="aff1">
<label>1</label>
<addr-line>The school of Geo-Science and Technology, Zhengzhou University, Zhengzhou, 450052, P. R. China</addr-line>
</aff>
<aff id="aff2">
<label>2</label>
<addr-line>Power China Chengdu Engineering Corporation Limited, Chengdu, 611130, P. R. China</addr-line>
</aff>
<aff id="aff3">
<label>3</label>
<addr-line>State Key Laboratory of Remote Sensing and Digital Earth, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, P.R. China</addr-line>
</aff>
<pub-date pub-type="epub">
<day>02</day>
<month>10</month>
<year>2026</year>
</pub-date>
<volume>2026</volume>
<fpage>1</fpage>
<lpage>23</lpage>
<permissions>
<copyright-statement>Copyright: &#x000a9; 2026 Zhigang 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://egusphere.copernicus.org/preprints/2026/egusphere-2026-5470/">This article is available from https://egusphere.copernicus.org/preprints/2026/egusphere-2026-5470/</self-uri>
<self-uri xlink:href="https://egusphere.copernicus.org/preprints/2026/egusphere-2026-5470/egusphere-2026-5470.pdf">The full text article is available as a PDF file from https://egusphere.copernicus.org/preprints/2026/egusphere-2026-5470/egusphere-2026-5470.pdf</self-uri>
<abstract>
<p>Aerosol direct radiative effect (ADRE) is a key component of the Earth&amp;rsquo;s radiation budget, yet its spatiotemporal variability and sensitivity to meteorological conditions remain insufficiently constrained across China. Here, we quantify daily ADRE at 72 radiation stations from 1993 to 2020 using a weather-aerosol normalization (WAN) machine learning framework, and examine its spatial pattern, seasonal cycle, and sensitivity&amp;nbsp;to aerosol optical depth (AOD) and environmental factors. Physical consistency of the framework is validated at over 98% of stations via SHapley Additive exPlanations (SHAP) analysis. The nationwide daily mean&amp;nbsp;ADRE is -0.761 MJ m&lt;sup&gt;&amp;minus;2&lt;/sup&gt; (-8.81 W m&lt;sup&gt;&amp;minus;2&lt;/sup&gt;), with strongest cooling in the Southern region (-0.904 MJ m&lt;sup&gt;&amp;minus;2&lt;/sup&gt;, -10.46 W m&lt;sup&gt;&amp;minus;2&lt;/sup&gt;) and weakest in the Tibetan Plateau (-0.187 MJ m&lt;sup&gt;&amp;minus;2&lt;/sup&gt;, -2.16 W m&lt;sup&gt;&amp;minus;2&lt;/sup&gt;). Seasonally, spring hosts the most peak-ADRE stations (50.7% of stations), whereas summer dominates regional mean intensity in northern, northwestern, and Tibetan Plateau regions;&amp;nbsp;southern China remains strong year-round. The ADRE sensitivity&amp;nbsp;to AOD spans -8.63 to -0.43 MJ m&lt;sup&gt;&amp;minus;2&lt;/sup&gt; per unit AOD&amp;nbsp;(highest in northwest China under frequent clear skies, dust aerosols, and high surface albedo), with negative AOD&amp;ndash;ADRE correlations at all stations (median &amp;minus;0.66). Sensitivity peaks under clear skies (59.7% of stations) and low humidity, where cloud-shielding effects are minimal. Notably, positive ADRE events (1.4%-51.7%) occur preferentially&amp;nbsp;at low AOD rather than high humidity, reflecting baseline-definition artifacts (AOD &amp;le; seasonal 5th percentile) and reduced signal-to-noise under clean backgrounds. This observationally constrained benchmark delineates dominant controls on daily ADRE and supports aerosol radiative forcing assessment in China.</p>
</abstract>
<counts><page-count count="23"/></counts>
<funding-group>
<award-group id="gs1">
<funding-source>National Natural Science Foundation of China</funding-source>
<award-id>42501431</award-id>
</award-group>
<award-group id="gs2">
<funding-source>Henan Provincial Science and Technology Research Project</funding-source>
<award-id>262102321033</award-id>
</award-group>
</funding-group>
</article-meta>
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