<?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>S0187-62362024000100006</article-id>
<article-id pub-id-type="doi">10.20937/atm.53248</article-id>
<title-group>
<article-title xml:lang="en"><![CDATA[Evaluation of the SACZ index as a prognostic tool based on GFS forecasts]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Aguiar]]></surname>
<given-names><![CDATA[Louise da Fonseca]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Cataldi]]></surname>
<given-names><![CDATA[Marcio]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Marton]]></surname>
<given-names><![CDATA[Edilson]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Ribeiro]]></surname>
<given-names><![CDATA[Eric Miguel]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Luz]]></surname>
<given-names><![CDATA[Priscila da Cunha]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Federal University of Rio de Janeiro (UFRJ) Geosciences Institute Department of Meteorology]]></institution>
<addr-line><![CDATA[Rio de Janeiro RJ]]></addr-line>
<country>Brazil</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,Federal Fluminense University (UFF) Laboratory of Monitoring and Modeling of Climate Systems (LAMMOC) ]]></institution>
<addr-line><![CDATA[Niterói RJ]]></addr-line>
<country>Brazil</country>
</aff>
<aff id="Af3">
<institution><![CDATA[,Agência Brasileira de Meteorologia Ltda. (CLIMATEMPO)  ]]></institution>
<addr-line><![CDATA[São Paulo SP]]></addr-line>
<country>Brazil</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>00</month>
<year>2024</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>00</month>
<year>2024</year>
</pub-date>
<volume>38</volume>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_arttext&amp;pid=S0187-62362024000100006&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_abstract&amp;pid=S0187-62362024000100006&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_pdf&amp;pid=S0187-62362024000100006&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="en"><p><![CDATA[ABSTRACT The South Atlantic Convergence Zone (SACZ) is an atmospheric phenomenon typical of summertime where a band of nebulosity causes intense or persistent rainfall in many regions of Brazil. SACZ episodes can be responsible for many natural disasters. Besides, the impacts of rainfall on water availability and consequently on the energy sector are extensive. The main objective of this study was to investigate the implementation of the SACZ index as an objective forecasting tool using input data from the Global Forecast System (GFS) model. Initially, we compared the index with the SACZ events identified by the Center for Weather Forecasting and Climate Studies (CPTEC ) from 2017 to 2021. Results showed that the index represented all events identified SACZs by CPTEC. Finally, we used data from the GFS 0.25 Degree from 2017 to 2021 to calculate Accuracy, Probability of detection, and False alarm ratio to evaluate the SACZ index as a prediction tool. Three thresholds are defined for the binary classification of a possible SACZ event. Results showed that above the most sensitive threshold (h1), within 10 days in advance, the sign of a possible SACZ can be detected. For the intermediate threshold (h2), a forecast of 96 h can detect a sign. For the most specific threshold (h3), the index can detect the event within 72 h in advance with a probability of detection of almost 90%. The SACZ index proved to be an efficient tool for detecting the dynamics of the phenomenon and can be used to assist operationally and in decision-making.]]></p></abstract>
<abstract abstract-type="short" xml:lang="es"><p><![CDATA[RESUMEN La Zona de Convergencia del Atlántico Sur (SACZ, por su sigla en inglés) es un fenómeno atmosférico típico del verano en América del Sur, donde una banda de nebulosidad provoca lluvias intensas o persistentes en muchas regiones de Brasil. Los episodios de SACZ pueden ser responsables de muchos desastres naturales. Además, los impactos de las precipitaciones sobre la disponibilidad de agua y, en consecuencia, sobre el sector energético son amplios. El objetivo principal de este estudio fue investigar la implementación del índice SACZ como una herramienta de pronóstico objetivo utilizando como entrada datos del Sistema Global de Predicción (GFS). Inicialmente se comparó el índice con eventos SACZ identificados por el Centro de Pronóstico del Tiempo y Estudios Climáticos (CPTEC) de 2017 a 2021. Los resultados mostraron que el índice representaba todos los eventos que el CPTEC identificó como SACZ . Finalmente, se utilizaron datos del Pronóstico Global GFS de 0.25º de 2017 a 2021 para calcular la Precisión, la Probabilidad de detección y el Índice de falsas alarmas con el fin de evaluar el índice SACZ como herramienta de predicción. Se definieron tres umbrales para una clasificación binaria de un posible evento SACZ. Los resultados mostraron que por encima del umbral más sensible (h1) se puede detectar el signo de una posible SACZ con 10 días de antelación. Para el umbral intermedio (h2), una previsión de 96 h puede detectar una señal. Para el umbral más específico (h3), el índice puede detectar el evento con 72 h de anticipación con una probabilidad de detección de casi 90 %. La aplicación del índice SACZ demostró ser una herramienta eficaz para detectar la dinámica del fenómeno, pudiendo utilizarse para auxiliar en la operación y toma de decisiones.]]></p></abstract>
<kwd-group>
<kwd lng="en"><![CDATA[atmospheric modeling]]></kwd>
<kwd lng="en"><![CDATA[weather forecasting]]></kwd>
<kwd lng="en"><![CDATA[South Atlantic Convergence Zone]]></kwd>
</kwd-group>
</article-meta>
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