<?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>0012-7353</journal-id>
<journal-title><![CDATA[DYNA]]></journal-title>
<abbrev-journal-title><![CDATA[Dyna rev.fac.nac.minas]]></abbrev-journal-title>
<issn>0012-7353</issn>
<publisher>
<publisher-name><![CDATA[Universidad Nacional de Colombia]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S0012-73532020000400204</article-id>
<article-id pub-id-type="doi">10.15446/dyna.v87n215.89952</article-id>
<title-group>
<article-title xml:lang="en"><![CDATA[CFSR- NCEP Performance for weather data forecasting in the Pernambuco Semiarid, Brazil]]></article-title>
<article-title xml:lang="es"><![CDATA[Desempeño del CFSR- NCEP en la predicción de datos meteorológicos en el Semiárido de Pernambuco, Brasil]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Alfaro]]></surname>
<given-names><![CDATA[Marcela Daniela Mollericona]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Lopes]]></surname>
<given-names><![CDATA[Iug]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Montenegro]]></surname>
<given-names><![CDATA[Abelardo Antônio Assunção]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Leal]]></surname>
<given-names><![CDATA[Brauliro Gonçalves]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Universidade Federal Rural de Pernambuco Departamento de Engenharia Agrícola ]]></institution>
<addr-line><![CDATA[Pernambuco ]]></addr-line>
<country>Brazil</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,Universidade Federal do Vale do São Francisco  ]]></institution>
<addr-line><![CDATA[Pernambuco ]]></addr-line>
<country>Brazil</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>12</month>
<year>2020</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>12</month>
<year>2020</year>
</pub-date>
<volume>87</volume>
<numero>215</numero>
<fpage>204</fpage>
<lpage>213</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_arttext&amp;pid=S0012-73532020000400204&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_abstract&amp;pid=S0012-73532020000400204&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_pdf&amp;pid=S0012-73532020000400204&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract The present study aims to evaluate meteorological data -with real time actualization- from the Climate Forecast System Reanalysis (CFRS) of the National Centers for Environmental Prediction (NCEP), comparing them with data from local stations in two mesoregions: Sertão de Pernambuco (SP) and Sertão do São Francisco (SFF), semi-arid region of Pernambuco, Brazil. Statistical performance indicators were used for the period since 1979 to 2014 and the variables: precipitation (P), average, minimum and maximum temperature (Tm, Tn, Tx respectively), relative humidity (HR), wind speed (Vv), solar radiation (RS) and potential evapotranspiration (ETo). Tn, Tm and Tx showed the best results for the determination coefficient (R2), Willmott concordance index (d), Nash-Sutcliffe efficiency index (NSE) and percentage bias (PBIAS). ETo, P and HR obtained acceptable values for R2, d and NSE. CFSR data shows good performance with d values between 0.63 and 0.94.]]></p></abstract>
<abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen El presente estudio tiene como objetivo evaluar datos meteorológicos -con actualización en tiempo real- del Reanálisis del Sistema de Predicción del Clima (CFRS) de los Centros Nacionales de Predicción Ambiental (NCEP), comparándolos con datos de estaciones locales en dos mesoregiones: Sertão de Pernambuco (SP) y Sertão do São Francisco (SFF), región Semiárido de Pernambuco, Brasil. Se emplearon indicadores estadísticos de desempeño, para el período de 1979 a 2014 y las variables: precipitación (P), temperatura media, mínima y máxima (Tm, Tn, Tx respectivamente), humedad relativa (HR), velocidad del viento (Vv), radiación solar (RS) y evapotranspiración potencial (ETo). La Tn, Tm y Tx demostraron los mejores resultados para el coeficiente de determinación (R2), índice de concordancia de Willmott (d), índice de eficiencia de Nash-Sutcliffe (NSE) y sesgo porcentual (PBIAS). La ETo, P y HR obtuvieron valores aceptables para R2, d y NSE. Datos CFSR muestran buen desempeño con valores de d entre 0.63 a 0.94.]]></p></abstract>
<kwd-group>
<kwd lng="en"><![CDATA[CFSR]]></kwd>
<kwd lng="en"><![CDATA[NCEP]]></kwd>
<kwd lng="en"><![CDATA[weather stations]]></kwd>
<kwd lng="en"><![CDATA[climate forecast system reanalysis]]></kwd>
<kwd lng="es"><![CDATA[CFSR]]></kwd>
<kwd lng="es"><![CDATA[NCEP]]></kwd>
<kwd lng="es"><![CDATA[estaciones meteorológicas]]></kwd>
<kwd lng="es"><![CDATA[reanálisis del sistema de predicción del clima]]></kwd>
</kwd-group>
</article-meta>
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