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dc.contributor.author
Salazar, Germán Ariel
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dc.contributor.author
Gueymard, Christian
dc.contributor.author
Galdino, Janis Bezerra
dc.contributor.author
de Castro Vilela, Olga
dc.contributor.author
Fraidenraich, Naum
dc.date.available
2021-09-30T02:15:31Z
dc.date.issued
2020-01
dc.identifier.citation
Salazar, Germán Ariel; Gueymard, Christian; Galdino, Janis Bezerra; de Castro Vilela, Olga; Fraidenraich, Naum; Solar irradiance time series derived from high-quality measurements, satellite-based models, and reanalyses at a near-equatorial site in Brazil; Pergamon-Elsevier Science Ltd; Renewable & Sustainable Energy Reviews; 117; 109478; 1-2020; 1-15
dc.identifier.issn
1364-0321
dc.identifier.uri
http://hdl.handle.net/11336/141965
dc.description.abstract
This study analyzes five years of 1-min solar global horizontal irradiance (GHI) and direct normal irradiance (DNI) observations obtained at Petrolina (northeast Brazil). Quality-assured hourly and daily averages are obtained after applying filters and methodologies based on a Baseline Solar Radiation Network (BSRN) qualitycontrol procedure. To calculate correct hourly averages, a minimum fraction of 20% of valid GHI or DNI minutely data is needed, as well as at least 60% of valid days to calculate correct daily-mean monthly values. An asymmetric diurnal pattern is found in GHI and DNI during all months, attributed to consistently higher cloudiness in the morning. The quality-assured hourly and monthly-mean GHI and DNI time series are compared to estimates from 11 solar databases regularly used in solar resource assessment studies: CAMS, CERES, ERA5, INPE, MERRA-2, Meteonorm, NASA-POWER, NSRDB, SARAH, SWERA-BR, and SWERA-US. For hourly GHI values, a range of RMS differences is found between the best (CAMS, 17.3%) and the worst (MERRA-2, 38.9%) results. The latter database is also affected by a larger bias (18.7%) than CAMS (4%). Larger RMS differences are found with hourly DNI, in a range extending from 37% (CAMS) to 63.4% (ERA5). Biases are all above 12%, except for CERES ( 1%). For long-term mean-monthly GHI results, low biases of less than 1% are obtained with CAMS, CERES and NASA-POWER, whereas MERRA-2 overestimates (13%). Larger biases are found for meanmonthly DNI, spanning between CAMS (3%) and Meteonorm ( 18.4%). Overall, CAMS appears the most consistent solar database for long-term irradiance time series at Petrolina. The significant differences found here between modeled databases are larger than expected, and underline the importance of regional validation studies like this one to decrease the incidence of uncertainties in solar resource assessments on the design and performance of solar energy projects.
dc.format
application/pdf
dc.language.iso
eng
dc.publisher
Pergamon-Elsevier Science Ltd
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dc.rights
info:eu-repo/semantics/restrictedAccess
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.subject
Irradiancia solar
dc.subject
Validación
dc.subject
Control de calidad de datos
dc.subject
Evaluación del recurso solar
dc.subject.classification
Otras Ciencias de la Tierra y relacionadas con el Medio Ambiente
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dc.subject.classification
Ciencias de la Tierra y relacionadas con el Medio Ambiente
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dc.subject.classification
CIENCIAS NATURALES Y EXACTAS
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dc.title
Solar irradiance time series derived from high-quality measurements, satellite-based models, and reanalyses at a near-equatorial site in Brazil
dc.type
info:eu-repo/semantics/article
dc.type
info:ar-repo/semantics/artículo
dc.type
info:eu-repo/semantics/publishedVersion
dc.date.updated
2021-08-27T20:29:53Z
dc.journal.volume
117
dc.journal.number
109478
dc.journal.pagination
1-15
dc.journal.pais
Estados Unidos
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dc.journal.ciudad
Amsterdam
dc.description.fil
Fil: Salazar, Germán Ariel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Salta. Instituto de Investigaciones en Energía no Convencional. Universidad Nacional de Salta. Facultad de Ciencias Exactas. Departamento de Física. Instituto de Investigaciones en Energía no Convencional; Argentina. Universidade Federal de Pernambuco; Brasil
dc.description.fil
Fil: Gueymard, Christian. Solar Consulting Services; Estados Unidos
dc.description.fil
Fil: Galdino, Janis Bezerra. Universidade Federal de Pernambuco; Brasil
dc.description.fil
Fil: de Castro Vilela, Olga. Universidade Federal de Pernambuco; Brasil
dc.description.fil
Fil: Fraidenraich, Naum. Universidade Federal de Pernambuco; Brasil
dc.journal.title
Renewable & Sustainable Energy Reviews
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dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1016/j.rser.2019.109478
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/abs/pii/S1364032119306860
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