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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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6603785/ https://www.ncbi.nlm.nih.gov/pubmed/31151288 http://dx.doi.org/10.3390/s19112483 |
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author | Urraca, Ruben Antonanzas, Javier Sanz-Garcia, Andres Martinez-de-Pison, Francisco Javier |
author_facet | Urraca, Ruben Antonanzas, Javier Sanz-Garcia, Andres Martinez-de-Pison, Francisco Javier |
author_sort | Urraca, Ruben |
collection | PubMed |
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. |
format | Online Article Text |
id | pubmed-6603785 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-66037852019-07-17 Analysis of Spanish Radiometric Networks with the Novel Bias-Based Quality Control (BQC) Method Urraca, Ruben Antonanzas, Javier Sanz-Garcia, Andres Martinez-de-Pison, Francisco Javier Sensors (Basel) Article 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. MDPI 2019-05-30 /pmc/articles/PMC6603785/ /pubmed/31151288 http://dx.doi.org/10.3390/s19112483 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Urraca, Ruben Antonanzas, Javier Sanz-Garcia, Andres Martinez-de-Pison, Francisco Javier 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 |
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_short | 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 |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6603785/ https://www.ncbi.nlm.nih.gov/pubmed/31151288 http://dx.doi.org/10.3390/s19112483 |
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