Analysis of Spanish Radiometric Networks with the Novel Bias-Based Quality Control (BQC) Method

Different types of measuring errors can increase the uncertainty of solar radiation measurements, but most common quality control (QC) methods do not detect frequent defects such as shading or calibration errors due to their low magnitude. We recently presented a new procedure, the Bias-based Qualit...

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Autores: Urraca, Ruben [0000-0003-0453-1143], Antonanzas, Javier [0000-0002-8042-9207], Sanz-Garcia, Andres [0000-0003-0413-4965], Martinez-de-Pison, Francisco Javier [0000-0002-3063-7374]
Formato: artículo
Estado:Versión publicada
Fecha de publicación:2019
País:España
Recursos:Universidad de La Rioja (UR)
Repositorio:RIUR. Repositorio Institucional de la Universidad de La Rioja
OAI Identifier:oai:portal.dialnet.es:doc/5d31765a2999521056384985
Acesso em linha:https://investigacion.unirioja.es/documentos/5d31765a2999521056384985
Access Level:acceso abierto
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network_acronym_str ES
network_name_str España
repository_id_str
spelling Analysis of Spanish Radiometric Networks with the Novel Bias-Based Quality Control (BQC) MethodUrraca, Ruben [0000-0003-0453-1143]Antonanzas, Javier [0000-0002-8042-9207]Sanz-Garcia, Andres [0000-0003-0413-4965]Martinez-de-Pison, Francisco Javier [0000-0002-3063-7374]Different types of measuring errors can increase the uncertainty of solar radiation measurements, but most common quality control (QC) methods do not detect frequent defects such as shading or calibration errors due to their low magnitude. We recently presented a new procedure, the Bias-based Quality Control (BQC), that detects low-magnitude defects by analyzing the stability of the deviations between several independent radiation databases and measurements. In this study, we extend the validation of the BQC by analyzing the quality of all publicly available Spanish radiometric networks measuring global horizontal irradiance (9 networks, 732 stations). Similarly to our previous validation, the BQC found many defects such as shading, soiling, or calibration issues not detected by classical QC methods. The results questioned the quality of SIAR, Euskalmet, MeteoGalica, and SOS Rioja, as all of them presented defects in more than 40% of their stations. Those studies based on these networks should be interpreted cautiously. In contrast, the number of defects was below a 5% in BSRN, AEMET, MeteoNavarra, Meteocat, and SIAR Rioja, though the presence of defects in networks such as AEMET highlights the importance of QC even when using a priori reliable stations.NLM (Medline)2019info:eu-repo/semantics/articleSubtype: Articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://investigacion.unirioja.es/documentos/5d31765a2999521056384985reponame:RIUR. Repositorio Institucional de la Universidad de La Riojainstname:Universidad de La Rioja (UR)Inglésinfo:eu-repo/semantics/altIdentifier/doi/10.3390/S19112483info:eu-repo/semantics/altIdentifier/pmid/31151288info:eu-repo/semantics/altIdentifier/eissn/1424-8220Analysis of Spanish Radiometric Networks with the Novel Bias-Based Quality Control (BQC) Method, 2019, vol. 19, núm. 11info:eu-repo/semantics/openAccessoai:portal.dialnet.es:doc/5d31765a29995210563849852026-06-14T12:47:17Z
dc.title.none.fl_str_mv Analysis of Spanish Radiometric Networks with the Novel Bias-Based Quality Control (BQC) Method
title Analysis of Spanish Radiometric Networks with the Novel Bias-Based Quality Control (BQC) Method
spellingShingle Analysis of Spanish Radiometric Networks with the Novel Bias-Based Quality Control (BQC) Method
Urraca, Ruben [0000-0003-0453-1143]
title_short Analysis of Spanish Radiometric Networks with the Novel Bias-Based Quality Control (BQC) Method
title_full Analysis of Spanish Radiometric Networks with the Novel Bias-Based Quality Control (BQC) Method
title_fullStr Analysis of Spanish Radiometric Networks with the Novel Bias-Based Quality Control (BQC) Method
title_full_unstemmed Analysis of Spanish Radiometric Networks with the Novel Bias-Based Quality Control (BQC) Method
title_sort Analysis of Spanish Radiometric Networks with the Novel Bias-Based Quality Control (BQC) Method
dc.creator.none.fl_str_mv Urraca, Ruben [0000-0003-0453-1143]
Antonanzas, Javier [0000-0002-8042-9207]
Sanz-Garcia, Andres [0000-0003-0413-4965]
Martinez-de-Pison, Francisco Javier [0000-0002-3063-7374]
author Urraca, Ruben [0000-0003-0453-1143]
author_facet Urraca, Ruben [0000-0003-0453-1143]
Antonanzas, Javier [0000-0002-8042-9207]
Sanz-Garcia, Andres [0000-0003-0413-4965]
Martinez-de-Pison, Francisco Javier [0000-0002-3063-7374]
author_role author
author2 Antonanzas, Javier [0000-0002-8042-9207]
Sanz-Garcia, Andres [0000-0003-0413-4965]
Martinez-de-Pison, Francisco Javier [0000-0002-3063-7374]
author2_role author
author
author
description Different types of measuring errors can increase the uncertainty of solar radiation measurements, but most common quality control (QC) methods do not detect frequent defects such as shading or calibration errors due to their low magnitude. We recently presented a new procedure, the Bias-based Quality Control (BQC), that detects low-magnitude defects by analyzing the stability of the deviations between several independent radiation databases and measurements. In this study, we extend the validation of the BQC by analyzing the quality of all publicly available Spanish radiometric networks measuring global horizontal irradiance (9 networks, 732 stations). Similarly to our previous validation, the BQC found many defects such as shading, soiling, or calibration issues not detected by classical QC methods. The results questioned the quality of SIAR, Euskalmet, MeteoGalica, and SOS Rioja, as all of them presented defects in more than 40% of their stations. Those studies based on these networks should be interpreted cautiously. In contrast, the number of defects was below a 5% in BSRN, AEMET, MeteoNavarra, Meteocat, and SIAR Rioja, though the presence of defects in networks such as AEMET highlights the importance of QC even when using a priori reliable stations.
publishDate 2019
dc.date.none.fl_str_mv 2019
dc.type.none.fl_str_mv info:eu-repo/semantics/article
Subtype: Article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://investigacion.unirioja.es/documentos/5d31765a2999521056384985
url https://investigacion.unirioja.es/documentos/5d31765a2999521056384985
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.3390/S19112483
info:eu-repo/semantics/altIdentifier/pmid/31151288
info:eu-repo/semantics/altIdentifier/eissn/1424-8220
Analysis of Spanish Radiometric Networks with the Novel Bias-Based Quality Control (BQC) Method, 2019, vol. 19, núm. 11
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv NLM (Medline)
publisher.none.fl_str_mv NLM (Medline)
dc.source.none.fl_str_mv reponame:RIUR. Repositorio Institucional de la Universidad de La Rioja
instname:Universidad de La Rioja (UR)
instname_str Universidad de La Rioja (UR)
reponame_str RIUR. Repositorio Institucional de la Universidad de La Rioja
collection RIUR. Repositorio Institucional de la Universidad de La Rioja
repository.name.fl_str_mv
repository.mail.fl_str_mv
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