<?xml version="1.0" encoding="UTF-8"?><?xml-stylesheet type="text/xsl" href="static/style.xsl"?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-04-14T20:09:12Z</responseDate><request verb="GetRecord" identifier="oai:uvadoc.uva.es:10324/59637" metadataPrefix="mods">https://uvadoc.uva.es/oai/request</request><GetRecord><record><header><identifier>oai:uvadoc.uva.es:10324/59637</identifier><datestamp>2024-12-04T13:09:00Z</datestamp><setSpec>com_10324_1176</setSpec><setSpec>com_10324_931</setSpec><setSpec>com_10324_894</setSpec><setSpec>col_10324_1359</setSpec></header><metadata><mods:mods xmlns:mods="http://www.loc.gov/mods/v3" xmlns:doc="http://www.lyncode.com/xoai" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-1.xsd">
<mods:name>
<mods:namePart>Calvo Sancho, Carlos</mods:namePart>
</mods:name>
<mods:name>
<mods:namePart>Quitián Hernández, Lara</mods:namePart>
</mods:name>
<mods:name>
<mods:namePart>González Alemán, Juan Jesús</mods:namePart>
</mods:name>
<mods:name>
<mods:namePart>Bolgiani, Pedro</mods:namePart>
</mods:name>
<mods:name>
<mods:namePart>Santos Muñoz, Daniel</mods:namePart>
</mods:name>
<mods:name>
<mods:namePart>Martín Pérez, María Luisa</mods:namePart>
</mods:name>
<mods:extension>
<mods:dateAvailable encoding="iso8601">2023-05-18T08:27:45Z</mods:dateAvailable>
</mods:extension>
<mods:extension>
<mods:dateAccessioned encoding="iso8601">2023-05-18T08:27:45Z</mods:dateAccessioned>
</mods:extension>
<mods:originInfo>
<mods:dateIssued encoding="iso8601">2023</mods:dateIssued>
</mods:originInfo>
<mods:identifier type="citation">Atmospheric Research, 2023, vol. 291, 106801</mods:identifier>
<mods:identifier type="issn">0169-8095</mods:identifier>
<mods:identifier type="uri">https://uvadoc.uva.es/handle/10324/59637</mods:identifier>
<mods:identifier type="doi">10.1016/j.atmosres.2023.106801</mods:identifier>
<mods:identifier type="publicationfirstpage">106801</mods:identifier>
<mods:identifier type="publicationtitle">Atmospheric Research</mods:identifier>
<mods:identifier type="publicationvolume">291</mods:identifier>
<mods:abstract>Tropical cyclones (TCs) can develop as a result of the tropical transition (TT) process, which occurs when an extratropical cyclone (EC) begins to exhibit tropical characteristics, forming a TC. In this study, four TT processes that lead to a hurricane structure [Delta (2005), Ophelia (2017), Leslie (2018), and Theta (2020)] are evaluated using two high-resolution numerical models (WRF and HARMONIE-AROME). Both tracks and intensities of the cyclones are assessed by comparing the simulated minimum sea level pressure and maximum wind speed to an observational dataset. Moreover, a spatial verification is performed by comparing the MSG-SEVIRI brightness temperature (BT) and accumulated precipitation (IMERG) to the corresponding simulations accomplished by both models. Analyzing the track results, the WRF model, on average, outstands HARMONIE-AROME. However, it is the HARMONIE-AROME model that performs better than WRF when reproducing the intensity of these cyclones. Concerning the BT spatial validation, HARMONIE-AROME slightly outperformed WRF when reproducing the cyclone's structure but failed when simulating the BT amplitude. Besides, both models achieved a nearly perfect cyclone location. In terms of accumulated precipitation results, the HARMONIE-AROME model overestimates the larger structures while underestimating the smaller ones, whereas the WRF model underestimates the bigger structures, being poorly located by both models. Although it is difficult to establish which numerical model performs better, the overall results show an outstanding of the HARMONIE-AROME model over the WRF model when simulating TT processes.</mods:abstract>
<mods:language>
<mods:languageTerm>eng</mods:languageTerm>
</mods:language>
<mods:accessCondition type="useAndReproduction">info:eu-repo/semantics/openAccess</mods:accessCondition>
<mods:accessCondition type="useAndReproduction">http://creativecommons.org/licenses/by-nc-nd/4.0/</mods:accessCondition>
<mods:accessCondition type="useAndReproduction">© 2023 The Authors</mods:accessCondition>
<mods:accessCondition type="useAndReproduction">Attribution-NonCommercial-NoDerivatives 4.0 Internacional</mods:accessCondition>
<mods:subject>
<mods:topic>Matemáticas</mods:topic>
</mods:subject>
<mods:subject>
<mods:topic>Artificial intelligence</mods:topic>
</mods:subject>
<mods:titleInfo>
<mods:title>Assessing the performance of the HARMONIE-AROME and WRF-ARW numerical models in North Atlantic Tropical Transitions</mods:title>
</mods:titleInfo>
<mods:genre>info:eu-repo/semantics/article</mods:genre>
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