<?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>0121-750X</journal-id>
<journal-title><![CDATA[Ingeniería]]></journal-title>
<abbrev-journal-title><![CDATA[ing.]]></abbrev-journal-title>
<issn>0121-750X</issn>
<publisher>
<publisher-name><![CDATA[Universidad Distrital Francisco José de Caldas]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S0121-750X2024000100203</article-id>
<article-id pub-id-type="doi">10.14483/23448393.19774</article-id>
<title-group>
<article-title xml:lang="en"><![CDATA[How Accurately Are Climatological Characteristics and Surface Water and Energy Balances Represented for the Colombian Amazon Basin?]]></article-title>
<article-title xml:lang="es"><![CDATA[¿Con qué exactitud se representan las características climatológicas y los balances superficiales de agua y energía en la Cuenca Amazónica Colombiana?]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Valencia-Monroy]]></surname>
<given-names><![CDATA[Carolina]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Baquero-Bernal]]></surname>
<given-names><![CDATA[Astrid]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Universidad Nacional de Colombia Instituto de Hidrologia, Meteorologia y Estudios Ambientales (IDEAM) ]]></institution>
<addr-line><![CDATA[Bogotá ]]></addr-line>
<country>Colombia</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,Universidad Nacional de Colombia Departamento de Física ]]></institution>
<addr-line><![CDATA[Bogotá ]]></addr-line>
<country>Colombia</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>04</month>
<year>2024</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>04</month>
<year>2024</year>
</pub-date>
<volume>29</volume>
<numero>1</numero>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_arttext&amp;pid=S0121-750X2024000100203&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_abstract&amp;pid=S0121-750X2024000100203&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_pdf&amp;pid=S0121-750X2024000100203&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract  Context: The Colombian Amazon basin (CAB) is characterized by having many areas with few or no in situ observations. To help fix this shortcoming, there are different gridded datasets that represent meteorological variable estimates from in situ, satellite-based, merged, and model-based products. However, before using them, it is necessary to evaluate their performance.  Method: We analyzed the capacity of five grid datasets to represent the annual cycle, the annual means, and the interquartile range of temperature and the variables that intervene in the surface water and energy balances of the CAB. The five datasets were a regional climate model (REMO) and four reanalyses (ERA40, ERA-Interim, NCEP/NCAR, and NCEP-v2). For the temperature and precipitation analyses, the Delaware, GPCP, CPC, CMAP, and CMAP-v2 datasets were also taken into account.  Results: The average annual temperature cycle in the CAB has an unimodal behavior, with higher values between October and March. Only Delaware and ERA-Interim describe this behavior and exhibit values close to those of the observations. The average annual cycle of precipitation is also unimodal, with higher values between March and July. Delaware, GPCP, CPC, and ERA-Interim describe this behavior, although ERA-Interim overestimates precipitation. Additionally, the four reanalyses, especially ERA-Interim, show an unexpected trend of increase in mean annual precipitation. As for the water balance, the precipitation and runoff maps of ERA-Interim and REMO show higher values in the foothills and east of 73 &#9702; W, a pattern that shows better agreement with the observations than those of the other datasets. ERA-Interim, REMO, and ERA-40 meet the closure condition of both the long-term water and the energy budgets. However, REMO and ERA-Interim overestimated precipitation, ERA-40underestimated it, and ERA-Interim overestimated solar radiation. This implies that some of the other variables for the water and energy balances are also poorly estimated.  Conclusions: The five gridded datasets that allow studying surface water and energy balances are not adequate, so better models and reanalyses are required.]]></p></abstract>
<abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen  Contexto: La Cuenca Amazónica Colombiana (CAB) se caracteriza por tener muchas áreas donde hay pocas observaciones in situ o ninguna. Para ayudar a corregir esta limitación, existen diferentes conjuntos de datos en rejilla que representan estimaciones de variables meteorológicas a partir de productos in situ, basados en satélites, fusionados y basados en modelos. Sin embargo, antes de utilizarlos, es necesario evaluar su desempeño.  Método: Se analizó la capacidad de cinco conjuntos de datos en rejilla para representar el ciclo anual, las medias anuales y el rango intercuartil de la temperatura y las variables que intervienen en los balances superficiales de agua y energía en la CAB. Los cinco conjuntos de datos son un modelo climático regional (REMO) y cuatro reanálisis (ERA40, ERA-Interim, NCEP/NCAR y NCEP-v2). Para los análisis de temperatura y precipitación, también se tuvieron en cuenta los conjuntos de datos Delaware, GPCP, CPC, CMAP y CMAP-v2.  Resultados: El ciclo anual medio de temperatura en la CAB tiene un comportamiento unimodal, con valores más altos entre octubre y marzo. Solo Delaware y ERA-Interim describen este comportamiento y presentan valores cercanos a los de las observaciones. El ciclo anual medio de precipitación también es unimodal, con valores más altos entre marzo y julio. Delaware, GPCP, CPC y ERA-Interim describen este comportamiento, aunque ERA-Interim sobreestima la precipitación. Además, los cuatro reanálisis, pero especialmente ERA-Interim, muestran una tendencia inesperada de aumento en la precipitación media anual. En relación al balance de agua, los mapas de precipitación y escorrentía de ERA-Interim y REMO muestran valores más altos en el piedemonte y al este de 73&#9702; W, un patrón que muestra una mejor concordancia con las observaciones que los de los otros conjuntos de datos. ERA-Interim, REMO y ERA-40 cumplen con la condición de clausura de los balances de agua y energía. Sin embargo, REMO y ERA-Interim sobreestiman la precipitación, ERA-40 la subestima y ERA-Interim sobreestima la radiación solar. Esto implica que algunas de las otras variables de los balances de agua y energía también están mal estimadas.  Conclusiones: Los cinco conjuntos de datos en rejilla que permiten estudiar los balances superficiales de agua y energía no son adecuados y, por lo tanto, se necesitan mejores modelos y reanálisis.]]></p></abstract>
<kwd-group>
<kwd lng="en"><![CDATA[Amazon basin]]></kwd>
<kwd lng="en"><![CDATA[climate]]></kwd>
<kwd lng="en"><![CDATA[energy balance]]></kwd>
<kwd lng="en"><![CDATA[water balance]]></kwd>
<kwd lng="es"><![CDATA[cuenca amazónica]]></kwd>
<kwd lng="es"><![CDATA[clima]]></kwd>
<kwd lng="es"><![CDATA[balance de energía]]></kwd>
<kwd lng="es"><![CDATA[balance de agua]]></kwd>
</kwd-group>
</article-meta>
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