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<front>
<journal-meta>
<journal-id journal-id-type="publisher">WESD</journal-id>
<journal-title-group>
<journal-title>Wind Energy Science Discussions</journal-title>
<abbrev-journal-title abbrev-type="publisher">WESD</abbrev-journal-title>
<abbrev-journal-title abbrev-type="nlm-ta">Wind Energ. Sci. Discuss.</abbrev-journal-title>
</journal-title-group>
<issn pub-type="epub">2366-7621</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/wes-2026-30</article-id>
<title-group>
<article-title>Methodology for the analysis of the effect of precipitation on wind farm performance</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Aparicio-Sanchez</surname>
<given-names>Maria</given-names>
<ext-link>https://orcid.org/0000-0001-8815-9830</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>Eguinoa</surname>
<given-names>Irene</given-names>
<ext-link>https://orcid.org/0000-0003-4833-7860</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>Cantero-Nouqueret</surname>
<given-names>Elena</given-names>
<ext-link>https://orcid.org/0000-0001-8638-329X</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>Olcoz-Alonso</surname>
<given-names>Alvaro</given-names>
<ext-link>https://orcid.org/0000-0002-8016-7171</ext-link>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
</contrib-group><aff id="aff1">
<label>1</label>
<addr-line>National Renewable Energy Centre (CENER), Sarriguren, Spain</addr-line>
</aff>
<pub-date pub-type="epub">
<day>05</day>
<month>02</month>
<year>2026</year>
</pub-date>
<volume>2026</volume>
<fpage>1</fpage>
<lpage>19</lpage>
<permissions>
<copyright-statement>Copyright: &#x000a9; 2026 Maria Aparicio-Sanchez 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://wes.copernicus.org/preprints/wes-2026-30/">This article is available from https://wes.copernicus.org/preprints/wes-2026-30/</self-uri>
<self-uri xlink:href="https://wes.copernicus.org/preprints/wes-2026-30/wes-2026-30.pdf">The full text article is available as a PDF file from https://wes.copernicus.org/preprints/wes-2026-30/wes-2026-30.pdf</self-uri>
<abstract>
<p>Wind turbines are exposed to rainfall, which has a long-term impact through erosion, and numerous studies have investigated the consequences of leading-edge erosion (LEE) on wind turbine blades. However, the potential effects of precipitation on turbine performance and on the experimental evolution of wakes have not yet been thoroughly analyzed. This paper presents a new methodology to study the impact of precipitation using experimental operational data. The methodology includes the necessary data processing, the definition of relevant meteorological parameters, and appropriate analysis methods. A commercial wind farm is evaluated following the proposed methodology, identifying differences in behavior between dry and rainy conditions at both the individual turbine level and the wind farm and wake levels, while accounting for the quantity and distribution of the available data.</p>
</abstract>
<counts><page-count count="19"/></counts>
<funding-group>
<award-group id="gs1">
<funding-source>Horizon 2020</funding-source>
<award-id>101083716</award-id>
</award-group>
</funding-group>
</article-meta>
</front>
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<back>
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</article>