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    Título
    Analysis of Spanish Radiometric Networks with the Novel Bias-Based Quality Control (BQC) Method
    Autor(es)
    Urraca, Ruben
    Antonanzas, Javier
    Sanz García, AndrésAutoridad USAL
    Martinez-de-Pison, Francisco Javier
    Palabras clave
    quality control
    solar radiation
    satellite-based data
    reanalysis; pyranometer
    weather stations
    Spain
    Fecha de publicación
    2019-05
    Citación
    Urraca R, Antonanzas J, Sanz-Garcia A, Martinez-de-Pison FJ. Analysis of Spanish Radiometric Networks with the Novel Bias-Based Quality Control (BQC) Method. Sensors. 2019; 19(11):2483. https://doi.org/10.3390/s19112483
    Resumen
    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.
    URI
    http://hdl.handle.net/10366/146889
    DOI
    10.3390/s19112483
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