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dc.contributor.authorBaigorria, Guillermo
dc.contributor.authorVillegas, Esequiel B.
dc.contributor.authorTrebejo, Irene
dc.contributor.authorCarlos, Jose F.
dc.contributor.authorQuiroz, Roberto
dc.date.accessioned2021-06-25T21:20:22Z
dc.date.available2021-06-25T21:20:22Z
dc.date.issued2004
dc.identifier.issn1097-0088
dc.identifier.urihttps://hdl.handle.net/20.500.12542/993
dc.description.abstractThis study of the distribution in space and time of atmospheric transmissivity τ takes into account the fact that, in complex terrain, many factors affect this variable; thus, it is not possible to use the generalizations that can be applied under more homogeneous conditions. Climatic controls, topography and even sea currents have important effects on clouds and aerosols affecting τ , simultaneously leading to differences in the distribution of incident solar radiation. Different models exist to estimate incoming solar radiation as a function of relative sunshine hours (observed sunshine hours/theoretical sunshine hours, n/N) or differences between maximum and minimum temperatures T . We calibrated, validated and evaluated four of these empirical relations based on data from 15 weather stations in Peru. Models were calibrated using 66% of the daily historical record available for each weather station; the rest of the information was used for validation and comparison. The Angstr ˚ om–Prescott model was used to estimate incoming solar radiation based on ¨ n/N, and gave the best performance of all the models tested. The other models (Bristow–Campbell, Hargreaves, and Garcia) estimated incoming solar radiation based on T . Of all the models in this group, the Bristow–Campbell model performed best; it is also valuable because of the physical explanation involved. The empirical coefficients of all the models evaluated are presented here. Two empirical equations are proposed with which to estimate values of the coefficients bB and cB in the Bristow–Campbell model, as a function of T and latitude, allowing the model to be applied to other study areas. Copyright  2004 Royal Meteorological Societyes_PE
dc.formatapplication/pdfes_PE
dc.language.isoenges_PE
dc.publisherJohn Wiley & Sonses_PE
dc.relation.urihttps://rmets.onlinelibrary.wiley.com/doi/abs/10.1002/joc.1060es_PE
dc.rightsinfo:eu-repo/semantics/openAccesses_PE
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 Estados Unidos de América*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/us/*
dc.sourceRepositorio Institucional - SENAMHIes_PE
dc.sourceServicio Nacional de Meteorología e Hidrología del Perúes_PE
dc.subjectRadiaciónes_PE
dc.subjectAtmospheric Transmissivityes_PE
dc.subjectSolar Radiation.es_PE
dc.subjectModelos y Simulaciónes_PE
dc.subjectÅngström–Prescott Modeles_PE
dc.titleAtmospheric transmissivity: distribution and empirical estimation around the central Andeses_PE
dc.typeinfo:eu-repo/semantics/articlees_PE
dc.identifier.doihttps://doi.org/10.1002/joc.1060.
dc.source.journalInternational Journal of Climatology
dc.subject.ocdehttps://purl.org/pe-repo/ocde/ford#1.05.08es_PE
dc.subject.ocdehttps://purl.org/pe-repo/ocde/ford#1.05.09es_PE
dc.publisher.countryPEes_PE


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