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		<doi>10.16993/tellusa.3261</doi>
		<issn>0280-6495</issn>
		<citationkey>TippettGoPeMaFiCo:2024:DaSoSe</citationkey>
		<title>Data Source Sensitivity in Solar Radiation Typical Meteorological Year (TMY) for Five Different Regions of Brazil</title>
		<year>2024</year>
		<month>Apr.</month>
		<typeofwork>journal article</typeofwork>
		<secondarytype>PRE PI</secondarytype>
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		<author>Tippett, Anna,</author>
		<author>Gonçalves, André Rodrigues,</author>
		<author>Pereira, Enio Bueno,</author>
		<author>Martins, Fernando Ramos,</author>
		<author>Fisch, Gilberto,</author>
		<author>Costa, Rodrigo Santos,</author>
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		<orcid>0000-0002-9430-1685</orcid>
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		<orcid>0000-0002-7618-4462</orcid>
		<orcid>0000-0001-6668-9988</orcid>
		<orcid>0000-0002-9544-4610</orcid>
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		<group>DIIAV-CGCT-INPE-MCTI-GOV-BR</group>
		<affiliation>University of Oxford</affiliation>
		<affiliation>Instituto Nacional de Pesquisas Espaciais (INPE)</affiliation>
		<affiliation>Universidade de Taubaté (UNITAU)</affiliation>
		<affiliation>Universidade Federal de São Paulo (UNIFESP)</affiliation>
		<affiliation>Universidade de Taubaté (UNITAU)</affiliation>
		<affiliation>Instituto Nacional de Pesquisas Espaciais (INPE)</affiliation>
		<electronicmailaddress>acvtippett@gmail.com</electronicmailaddress>
		<electronicmailaddress>andre.goncalves@inpe.br</electronicmailaddress>
		<journal>Tellus A: Dynamic Meteorology and Oceanography</journal>
		<volume>76</volume>
		<number>1</number>
		<pages>29-41</pages>
		<secondarymark>A2_MATEMÁTICA_/_PROBABILIDADE_E_ESTATÍSTICA A2_INTERDISCIPLINAR A2_GEOCIÊNCIAS</secondarymark>
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		<keywords>TMY, Typical Meteorological Year, Meteorological Data, Solar Energy, Solar Radiation.</keywords>
		<abstract>In this article, we examine how sensitive the methodology for calculating a Typical Meteorological Year (TMY) is to changes in the source of the meteorological data series and the weighting factors used. Three different sources of meteorological data  ground-based observations, modeled satellite-derived data, and ERA5 reanalysis data  were used to determine the sensitivity of the TMY to the data source. The TMY was created for five different climatic regions in Brazil using 13 years of hourly data for meteorological indices consisting of maximum, minimum, and average air temperature, relative humidity, wind speed, global total horizontal radiation, and normal direct solar radiation. The study shows that the source of the meteorological data plays little role in determining the most typical months. The typicality of the months was consistent even when data sources as diverse as in situ and modeled data were used. The study also shows that the exact choice of weighting scheme for the meteorological data source is relatively arbitrary, if not irrelevant. This is because meteorological parameters are not independent variables and therefore often represent redundant information. A few independent parameters are sufficient to produce a good TMY and adding several interdependent parameters does not improve the quality of the TMY produced.</abstract>
		<area>CST</area>
		<language>en</language>
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