<?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>1794-6190</journal-id>
<journal-title><![CDATA[Earth Sciences Research Journal]]></journal-title>
<abbrev-journal-title><![CDATA[Earth Sci. Res. J.]]></abbrev-journal-title>
<issn>1794-6190</issn>
<publisher>
<publisher-name><![CDATA[Universidad Nacional de Colombia]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S1794-61902022000300231</article-id>
<article-id pub-id-type="doi">10.15446/esrj.v26n3.101477</article-id>
<title-group>
<article-title xml:lang="en"><![CDATA[Role of Ocean-Atmosphere Interface in Annual and Semiannual SST Cycles in the Indian Ocean]]></article-title>
<article-title xml:lang="es"><![CDATA[Papel de la interfaz océano-atmósfera en los ciclos anuales y semestrales de la TSM en el Océano Índico]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[de Oliveira Carvalho Junior]]></surname>
<given-names><![CDATA[Oldemar]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Centro de Estudos Budistas Bodisatva  ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>09</month>
<year>2022</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>09</month>
<year>2022</year>
</pub-date>
<volume>26</volume>
<numero>3</numero>
<fpage>231</fpage>
<lpage>238</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_arttext&amp;pid=S1794-61902022000300231&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_abstract&amp;pid=S1794-61902022000300231&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_pdf&amp;pid=S1794-61902022000300231&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="en"><p><![CDATA[ABSTRACT A long-term analysis of temperature can be used to describe the main mechanisms that operate at the surface of the ocean. The average sea surface temperature (SST) contour plots for the Indian Ocean are produced based on the World Ocean Atlas Data Set (1994). SST, together with the independent variables wind (Wx, zonal component of pseudo-stress wind and Wy, meridional component of pseudo-stress wind), net-down-fresh-water-flow (NDFF), and Ekman pumping, are included in a multiple regression analysis to define the relative importance of each one of these variables in the physical processes at the surface of the Indian Ocean. The NDFF data set is based on COADS (Comprehensive Ocean-Atmosphere Data Set). The wind data is obtained from the Florida State University (FSU). The harmonic terms of the variables are calculated, which is considered to be stationary and expressed by a Fourier series as a cosine function. The harmonic terms are multiplied by the maximum amplitude of the variables and then added to their mean annual values. The isotherms are mainly meridional along the western boundary, but zonal in the southern Indian Ocean. The annual component is seen to have a maximum in July, Summer Monsoon (SW Monsoon) and a minimum in January, during the Winter Monsoon (NE Monsoon). The amplitude of the semiannual component is smaller, with two maxima in May and October and two minima in February and August. The small magnitude of these residuals errors is an indication that the temperature variability during this period and for this area can be explained reasonably well by the two harmonic terms. In the Arabian Sea, the final regression equations for SST variability show that it is mainly affected by the Wx, Ekman pumping and NDFF. For most of the areas of the Bay of Bengal, as well as for most of the locations in the southern tropical Indian Ocean, the entered independent variables can explain SST. Two components fit to observation can be used to predict SST together with the regression equations. Although harmonic analysis can be used to study SST variability, a multiple regression analysis is required to identify and quantify the variables related to areas of large annual and semiannual variability. Different techniques are therefore used together to provide more reliable results in SST configuration in the Indian Ocean.]]></p></abstract>
<abstract abstract-type="short" xml:lang="es"><p><![CDATA[RESUMEN Este trabajo parte de la posiblidad de utilizar un análisis a largo plazo de la temperatura para describir los principales mecanismos que operan en la superficie del océano. Los diagramas de contorno de la temperatura promedio de la superficie del mar (TSM) para el Océano Índico se produjeron con base en el World Ocean Atlas Data Set (1994). El TSM, junto con las variables independientes viento (Wx, componente zonal del viento de pseudo-estrés y Wy, componente meridional del viento de pseudo-estrés), flujo neto de agua dulce (NDFF) y bombeo de Ekman se incluyeron en un análisis de regresión múltiple para definir la importancia relativa de cada una de estas variables en los procesos físicos en la superficie del Océano Índico. El conjunto de datos NDFF se basó en el COADS (Comprehensive Ocean-Atmosphere Data Set). Los datos de viento se obtuvieron de la Universidad Estatal de Florida (FSU). Se calcularon los términos armónicos de las variables, que se consideran estacionarios y se expresaron mediante una serie de Fourier como función coseno. Los términos armónicos se multiplicaron por la amplitud máxima de las variables y luego se sumaron a sus valores medios anuales. Las isotermas son principalmente meridionales a lo largo del límite occidental, pero zonales en el sur del Océano Índico. Se considera que el componente anual tiene un máximo en julio, monzón de verano (monzón del SW) y un mínimo en enero, durante el monzón de invierno (monzón del NE). La amplitud del componente semestral es menor, con dos máximos en mayo y octubre y dos mínimos en febrero y agosto. La pequeña magnitud de estos errores residuales es una indicación de que la variabilidad de la temperatura durante este período y para esta área puede explicarse razonablemente bien por los dos términos armónicos. En el Mar Arábigo las ecuaciones de regresión finales para la variabilidad de la SST muestran que se ve afectada principalmente por el Wx, el bombeo de Ekman y el NDFF. Para la mayoría de las áreas de la Bahía de Bengala, así como para la mayoría de las ubicaciones en el sur del Océano Índico tropical, las variables independientes ingresadas pueden explicar la TSM. Se pueden usar dos componentes ajustados a la observación para predecir la TSM junto con las ecuaciones de regresión. Aunque el análisis armónico se puede utilizar para estudiar la variabilidad de la TSM se requiere un análisis de regresión múltiple para identificar y cuantificar las variables relacionadas con áreas de gran variabilidad anual y semestral. Por lo tanto, se utilizan diferentes técnicas para proporcionar resultados más confiables en la configuración de la TSM en el Océano Índico.]]></p></abstract>
<kwd-group>
<kwd lng="en"><![CDATA[Harmonic analysis]]></kwd>
<kwd lng="en"><![CDATA[multiple regression]]></kwd>
<kwd lng="en"><![CDATA[ocean circulation]]></kwd>
<kwd lng="es"><![CDATA[Análisis armónico]]></kwd>
<kwd lng="es"><![CDATA[regresión multiple]]></kwd>
<kwd lng="es"><![CDATA[circulación oceánica]]></kwd>
</kwd-group>
</article-meta>
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