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dc.contributor.authorMorales-Salinas, Luis
dc.contributor.authorOrtega-Farias, Samuel
dc.contributor.authorRiveros-Burgos, Camilo
dc.contributor.authorChávez, José L.
dc.contributor.authorWang, Sufen
dc.contributor.authorTian, Fei
dc.contributor.authorCarrasco-Benavides, Marcos
dc.contributor.authorNeira-Román, José
dc.contributor.authorLópez-Olivari, Rafael
dc.contributor.authorFuentes‑Jaque, Guillermo
dc.date.accessioned2023-09-26T15:07:03Z
dc.date.available2023-09-26T15:07:03Z
dc.date.issued2023
dc.identifier.urihttp://repositorio.ucm.cl/handle/ucm/4992
dc.description.abstractAtmospheric longwave downward radiation (Ld) is one of the significant components of net radiation (Rn), and it drives several essential ecosystem processes. Ld can be estimated with simple empirical methods using atmospheric emissivity (εa) submodels. In this study, eight global models for εa were evaluated, and the best-performing model was calibrated on a global scale using a parametric instability analysis approach. The climatic data were obtained from a dynamically consistent scale resolution of basic atmospheric quantities and computed parameters known as NCEP/NCAR reanalysis (NNR) data. The performance model was evaluated with monthly average values from the NNR data. The Brutsaert equation demonstrated the best performance, and then it was calibrated. The seasonal global trend of the Brutsaert equation calibrated coefficient ranged between 1.2 and 1.4, and the K-means analysis identified five homogeneous zones (clusters) with similar behavior. Finally, the calibrated Brutsaert equation improved the Rn estimation, with an error reduction, at the worldwide scale, of 64%. Meanwhile, the error reduction for each cluster ranged from 18 to 77%. Hence, Brutsaert’s equation coefficient should not be considered a constant value for use in εa estimation, nor in time or location.es_CL
dc.language.isoenes_CL
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 Chile*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/cl/*
dc.sourceScientific Reports, 13(1), 14465es_CL
dc.titleAssessment of atmospheric emissivity models for clear-sky conditions with reanalysis dataes_CL
dc.typeArticlees_CL
dc.ucm.facultadFacultad de Ciencias Agrarias y Forestaleses_CL
dc.ucm.indexacionScopuses_CL
dc.ucm.indexacionIsies_CL
dc.ucm.urinature.com/articles/s41598-023-40499-6es_CL
dc.ucm.doidoi.org/10.1038/s41598-023-40499-6es_CL


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