<?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>S0187-62362019000100001</article-id>
<article-id pub-id-type="doi">10.20937/atm.2019.32.01.01</article-id>
<title-group>
<article-title xml:lang="en"><![CDATA[A novel velocity dealiasing algorithm for S-Band weather radars]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Chu]]></surname>
<given-names><![CDATA[Zhigang]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Wu]]></surname>
<given-names><![CDATA[Di]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Hu]]></surname>
<given-names><![CDATA[Hanfeng]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Xu]]></surname>
<given-names><![CDATA[Dan]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Chen]]></surname>
<given-names><![CDATA[Aijun]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Nanjing University of Information Science and Technology Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD)]]></institution>
<addr-line><![CDATA[Jiangsu ]]></addr-line>
<country>China</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>00</month>
<year>2019</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>00</month>
<year>2019</year>
</pub-date>
<volume>32</volume>
<numero>1</numero>
<fpage>1</fpage>
<lpage>13</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_arttext&amp;pid=S0187-62362019000100001&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_abstract&amp;pid=S0187-62362019000100001&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_pdf&amp;pid=S0187-62362019000100001&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="en"><p><![CDATA[ABSTRACT Noise, especially continuous noise, is an important factor that affects the velocity dealiasing of Doppler weather radars. A challenge in the design of dealiasing algorithm is how to effectively suppress noise. Therefore, a novel anti-noise dealiasing algorithm (AND) for Doppler velocities was proposed in this paper. In comparison with traditional methods, the AND utilizes a new separation-restoration noise suppression scheme, which can significantly reduce the interference of noise on dealiasing without losing data. This algorithm utilizes three fitting curves as references to correct ambiguous echoes, and it can further suppress residual noise and dynamically match wind fields at varying scales. The AND has been applied to the CINRAD-SA network of operational radars in China, achieving a better performance on noisy echoes, isolated echoes, typhoon echoes, and tornado echoes.]]></p></abstract>
<abstract abstract-type="short" xml:lang="es"><p><![CDATA[RESUMEN El ruido, en especial el continuo, es un factor importante que afecta el dealiasing (supresión del solapamiento) de la velocidad en radares meteorológicos Doppler. En este trabajo se propone un novedoso algoritmo (anti-noise dealiasing algorithm, AND) para solventar este problema. En comparación con los métodos tradicionales, el AND utiliza un nuevo esquema de separación y restauración para eliminar el ruido, que puede reducir de manera significativa la interferencia de éste en el dealiasing sin pérdida de información. El algoritmo utiliza tres ajustes de curvas como referencia para corregir ecos ambiguos. Además puede eliminar el ruido residual y comparar dinámicamente campos de viento en diversas escalas. El AND se ha aplicado en los radares operativos de la red CINRAD-SA en China, con buenos resultados en cuanto a ecos de ruido, ecos aislados, ecos de tifón y ecos de tornado.]]></p></abstract>
<kwd-group>
<kwd lng="en"><![CDATA[Doppler weather radar]]></kwd>
<kwd lng="en"><![CDATA[data quality control]]></kwd>
<kwd lng="en"><![CDATA[continuous noise]]></kwd>
<kwd lng="en"><![CDATA[continuous noise suppression]]></kwd>
<kwd lng="en"><![CDATA[velocity dealiasing]]></kwd>
</kwd-group>
</article-meta>
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