<?xml version="1.0" encoding="ISO-8859-1"?><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
<front>
<journal-meta>
<journal-id>0187-6236</journal-id>
<journal-title><![CDATA[Atmósfera]]></journal-title>
<abbrev-journal-title><![CDATA[Atmósfera]]></abbrev-journal-title>
<issn>0187-6236</issn>
<publisher>
<publisher-name><![CDATA[Universidad Nacional Autónoma de México, Instituto de Ciencias de la Atmósfera y Cambio Climático]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S0187-62362023000200279</article-id>
<article-id pub-id-type="doi">10.20937/atm.53043</article-id>
<title-group>
<article-title xml:lang="en"><![CDATA[Analyzing and forecasting lightning flashes and the related wind gusts at a wind energy power plant in a hilly region of western Greece]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Kolokythas]]></surname>
<given-names><![CDATA[Konstantinos V.]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Argiriou]]></surname>
<given-names><![CDATA[Athanassios A.]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Kotroni]]></surname>
<given-names><![CDATA[Vassiliki]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,University of Patras  ]]></institution>
<addr-line><![CDATA[Patras ]]></addr-line>
<country>Greece</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,National Observatory of Athens Institute for Environmental Research and Sustainable Development ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Greece</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>00</month>
<year>2023</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>00</month>
<year>2023</year>
</pub-date>
<volume>36</volume>
<numero>2</numero>
<fpage>279</fpage>
<lpage>298</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_arttext&amp;pid=S0187-62362023000200279&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_abstract&amp;pid=S0187-62362023000200279&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_pdf&amp;pid=S0187-62362023000200279&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="en"><p><![CDATA[ABSTRACT Wind power plants are vulnerable to abrupt weather changes caused by thunderstorms associated with lightning activity and accompanying severe wind gusts and rapid wind direction changes. Due to the damages that such phenomena may cause, the knowledge of the relationship between storm systems and the produced wind field is essential during the construction and operation phase of a plant. In the first part of this study, the relationship between severe wind gusts and lightning activity in a power plant in Greece is investigated. Wind data are measured at the wind turbines for a 3-year period (2012-2014); the corresponding lightning data come from the ZEUS lighting detection network. Wind gusts are well correlated to lightning strikes. This correlation is maximized during winter when well organized weather systems affect the area and minimized in summer as a result of local storms due to thermal instability. The second part of the study focuses on the development of an artificial neural network (ANN) model in order to forecast these two parameters in a 1-h ahead horizon based on wind speed, wind direction, and maximum observed wind gust measured at the nacelle of a wind turbine and four other variables, namely CAPE, TTI, wind speed at the 500 hPa isobaric level, and the 0-6 km vertical wind shear. The proposed model could be considered as a promising tool in simulating the occurrence both of wind gusts and lightning flashes, providing a relatively good evidence of the possibility of occurrence of such events.]]></p></abstract>
<abstract abstract-type="short" xml:lang="es"><p><![CDATA[RESUMEN Las plantas de energía eólica son vulnerables a tormentas eléctricas asociadas con la actividad de los rayos y las ráfagas de viento severas y cambios en la dirección del viento que las acompañan. Debido a una variedad de daños que tales fenómenos pueden causar, el conocimiento de la relación entre los sistemas de tormentas y el campo eólico producido es esencial para establecer una planta de energía eólica también durante la fase de construcción y operación. En la primera parte de este estudio se investiga la relación entre las fuertes ráfagas de viento y la actividad de los rayos en un parque eólico de Grecia. Los datos de viento provienen de aerogeneradores que cubren un periodo de tres años (2012-2014), mientras que los datos de rayos corresponden a la red de detección de iluminación ZEUS. Las ráfagas de viento están bien correlacionadas con los rayos. La correlación se maximiza durante el invierno cuando sistemas convectivos bien organizados afectan el área y es mínima en verano como resultado de las tormentas locales debidas a la inestabilidad térmica. En la segunda parte, el estudio se centra en el desarrollo de un modelo de red neuronal artificial con el fin de pronosticar estos dos parámetros a una hora utilizando cuatro variables, a saber, CAPE, TTI, velocidad del viento a 500 hPa y la cizalladura vertical del viento de 0-6 km. El modelo propuesto podría considerarse como una herramienta prometedora para simular la ocurrencia tanto de ráfagas de viento como de relámpagos, proporcionando una evidencia relativamente buena de la posibilidad de que ocurran tales eventos.]]></p></abstract>
<kwd-group>
<kwd lng="en"><![CDATA[wind gusts]]></kwd>
<kwd lng="en"><![CDATA[lightning strikes]]></kwd>
<kwd lng="en"><![CDATA[forecast]]></kwd>
</kwd-group>
</article-meta>
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