<?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>S0187-62362016000400343</article-id>
<title-group>
<article-title xml:lang="en"><![CDATA[A method for convective storm detection using satellite data]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Silva Neto]]></surname>
<given-names><![CDATA[Carlos Pinto Da]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Alves Barbosa]]></surname>
<given-names><![CDATA[Humberto]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Assis Beneti]]></surname>
<given-names><![CDATA[Cesar Augustus]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Universidade Federal do Paraná Centro Politécnico Sistema Meteorológico do Paraná (SIMEPAR)]]></institution>
<addr-line><![CDATA[Curitiba Paraná]]></addr-line>
<country>Brazil</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,Universidade Federal de Alagoas Laboratório de Análise e Processamento de Imagens de Satélites (LAPIS) ]]></institution>
<addr-line><![CDATA[Maceió Alagoas]]></addr-line>
<country>Brazil</country>
</aff>
<aff id="Af3">
<institution><![CDATA[,Universidade Federal do Paraná Centro Politécnico Sistema Meteorológico do Paraná (SIMEPAR)]]></institution>
<addr-line><![CDATA[Curitiba Paraná]]></addr-line>
<country>Brazil</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>10</month>
<year>2016</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>10</month>
<year>2016</year>
</pub-date>
<volume>29</volume>
<numero>4</numero>
<fpage>343</fpage>
<lpage>358</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_arttext&amp;pid=S0187-62362016000400343&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_abstract&amp;pid=S0187-62362016000400343&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_pdf&amp;pid=S0187-62362016000400343&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract: Moisture and instability, along with a triggering mechanism, are the main keys of deep convective storms initiation and evolution. Satellite data can provide indirect measurements of instability and moisture of a wide area in short periods of time. This paper studies the use of an objective method based on a blended use of multiple satellite-based convection estimation techniques. This method is based on different techniques arranged in a several layers approach of different convective features, aiming to stratify a cloud shield. Meteosat Second Generation (MSG) infrared (IR) 10.8 &#956;m and water vapor (WV) 6.2 &#956;m channels are explored together with tropopause temperature information provided by a numerical model. Threshold, brightness temperature differences (BTD), and time trends are applied to the information available resulting in a five layers product, highlighting areas of different convective activities. This cloud shield stratification method showed a great ability to better evaluate strong convection when compared with simpler techniques such as IR false color, and was especially useful to better identify the strongest convective cell in a large area with several convective outbreaks. A validation analysis was conducted using radar and lightning data, showing that this approach is very helpful in distinguishing very strong cases from weaker ones by pointing out subtle convective patterns only present in severe storms. Also, small changes in storm evolution were more pronounced in the method output. Besides some uncertainties that were observed, likely due to the large viewing angle, techniques derived from MSG spectral bands displayed good accuracy in studying large convective systems in the South America southern region.]]></p></abstract>
<abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen: La humedad y la inestabilidad, en conjunto con un mecanismo de disparo, son las principales claves de iniciación y evolución de las tormentas de convección profunda. Los datos satelitales pueden proporcionar mediciones indirectas de la inestabilidad y la humedad de una amplia área en cortos periodos de tiempo. En este trabajo se estudia la utilización de un método objetivo basado en el uso combinado de técnicas de estimación de convección basadas en satélites. Este método se fundamenta en diferentes técnicas dispuestas en un enfoque multicapa de diferentes características convectivas, con el objetivo de estratificar un tope nuboso. Se investigan los canales infrarrojo (IR) de 10.8 &#956;m y de vapor de agua de 6.2 &#956;m de Meteosat segunda generación (MSG) junto con la temperatura de la tropopausa proporcionada por un modelo numérico. Se aplican el umbral, diferencias de brillo de temperatura y tendencias en el tiempo a la información disponible, de lo cual resulta un producto de cinco capas que destaca las áreas de diferentes actividades de convección. Este método de estratificación mostró gran capacidad para evaluar mejor la convección fuerte en comparación con las técnicas más simples como IR de falso color, y fue especialmente eficiente para identificar la célula de convección fuerte en un área grande con varios focos convectivos. Se llevó a cabo un análisis de validación utilizando datos de radar y de rayos, lo cual demuestra que este enfoque es muy útil para distinguir los casos fuertes de los débiles desde las primeras horas mediante la selección de patrones convectivos sutiles solamente presentes en tormentas severas. Los pequeños cambios en la evolución de la tormenta también se apreciaron mejor en los resultados arrojados por este método, lo cual facilita su identificación. Además se observaron algunas incertidumbres, probablemente debido al gran ángulo de visión, lo cual demuestra que la técnica derivada de las bandas espectrales del MSG tiene buena precisión para el estudio de los grandes sistemas convectivos en la región austral de Sudamérica.]]></p></abstract>
<kwd-group>
<kwd lng="en"><![CDATA[Deep convection]]></kwd>
<kwd lng="en"><![CDATA[satellite]]></kwd>
<kwd lng="en"><![CDATA[mesoscale convection system]]></kwd>
</kwd-group>
</article-meta>
</front><back>
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