<?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>S0187-62362022000400687</article-id>
<article-id pub-id-type="doi">10.20937/atm.52982</article-id>
<title-group>
<article-title xml:lang="en"><![CDATA[Application of a ground-based microwave radiometer in aviation weather forecasting in Indian Air Force]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Mishra]]></surname>
<given-names><![CDATA[Savitesh]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Pandit]]></surname>
<given-names><![CDATA[Shreya]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Mittal]]></surname>
<given-names><![CDATA[Ashish]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Srinivas]]></surname>
<given-names><![CDATA[Velampudi Sudarshan]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Air Force Centre for Numerical Weather Prediction  ]]></institution>
<addr-line><![CDATA[New Delhi ]]></addr-line>
<country>India</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,Indian Air Force Directorate of Meteorology ]]></institution>
<addr-line><![CDATA[New Delhi ]]></addr-line>
<country>India</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>00</month>
<year>2022</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>00</month>
<year>2022</year>
</pub-date>
<volume>35</volume>
<numero>4</numero>
<fpage>687</fpage>
<lpage>699</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_arttext&amp;pid=S0187-62362022000400687&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_abstract&amp;pid=S0187-62362022000400687&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_pdf&amp;pid=S0187-62362022000400687&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="en"><p><![CDATA[ABSTRACT Time and intensity-specific very short-term forecasting or nowcasting is the biggest challenge faced by an aviation meteorologist. Ground-based microwave radiometer (MWR) has been used for nowcasting convective activity and it was established that there is a good comparison between thermodynamic parameters derived from MWR and GPS radiosonde observations, indicating that MWR observations can be used to develop techniques for nowcasting severe convective activity. In this study, efforts have been made to bring out the efficacy of MWR in nowcasting thunderstorms and fog. Firstly, the observations of MWR located at Palam, New Delhi, India have been compared with the nearest radiosonde data to ascertain the variation in respective profiles. Large differences were found in relative humidity (RH), whereas temperatures from MWR were found to be close to radiosonde observed temperature up to 3.5 km. Subsequently, the scatter plots and correlation coefficients of thermodynamic indices/parameters indicated that most of the parameters are either not correlated or have moderate correlation only for 12:00 UTC profiles. The superepoch technique of lagged composite for various thermodynamic indices/parameters to obtain a combined picture of all the thunderstorm and dense fog cases on the time series could not determine any pattern to predict thunderstorm and dense fog with lead time of 2-4 hours. MWR profile for a case of occurrence of thunderstorm was analyzed. No significant variation was observed in most of the indices (as calculated from MWR observed parameters) prior to the occurrence of thunderstorm. RH at freezing level and between 950 and 700 hPa levels were the only parameters, which increased four hours prior to the occurrence.]]></p></abstract>
<abstract abstract-type="short" xml:lang="es"><p><![CDATA[RESUMEN El pronóstico específico en tiempo e intensidad, a muy corto plazo o inmediato, es el mayor reto al que se enfrenta un meteorólogo aeronáutico. El radiómetro de microondas terrestre (MWR, por sus siglas en inglés) se ha utilizado para realizar predicciones inmediatas de la actividad convectiva y se determinó que existe una buena comparación entre los parámetros termodinámicos derivados del MWR y las observaciones de radiosondas GPS, lo que indica que las observaciones realizadas con el MWR se pueden utilizar para desarrollar técnicas de predicción inmediata de condiciones convectivas severas. En este estudio se busca resaltar la eficacia de MWR en tormentas eléctricas y niebla de pronóstico inmediato. En primer lugar, las observaciones del MWR ubicadas en Palam, Nueva Delhi, India, se han comparado con los datos de la radiosonda más cercana para determinar la variación en los perfiles respectivos. Se encontraron grandes diferencias en la humedad relativa (RH), mientras que las temperaturas del MWR se encontraron cercanas a la temperatura de radiosonda observada hasta 3.5 km. Posteriormente, los gráficos de dispersión y el coeficiente de correlación de los índices/parámetros termodinámicos indicaron que la mayoría de los parámetros no están correlacionados o tienen una correlación moderada sólo para los perfiles a las 12:00 UTC. La técnica superepoch de composición rezagada para varios índices/parámetros termodinámicos para obtener una imagen combinada de todos los casos de tormenta y niebla densa en la serie de tiempo no pudo determinar ningún patrón para predecir tormentas y niebla densa con un tiempo de espera de 2-4 h. Se analizó el perfil del MWR para un caso de ocurrencia de tormenta. No se observó una variación significativa en la mayoría de los índices (calculados a partir de los parámetros observados con el MWR) antes de que ocurriera la tormenta. La HR a nivel de congelación y entre 950 y 700 hPa fueron los únicos parámetros que aumentaron 4 h antes de la ocurrencia.]]></p></abstract>
<kwd-group>
<kwd lng="en"><![CDATA[radiosonde]]></kwd>
<kwd lng="en"><![CDATA[microwave radiometer]]></kwd>
<kwd lng="en"><![CDATA[nowcasting]]></kwd>
<kwd lng="en"><![CDATA[superepoch analysis]]></kwd>
</kwd-group>
</article-meta>
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