An algorithm based on satellite observations to quality control ground solar sensors: analysis of Spanish meteorological networks

Abstract

We present a hybrid quality control (QC) for identifying defects in ground sensors of solar radiation. The method combines a window function that flags potential defects in radiation time series with a visual decision support system that eases the detection of false alarms and the identification of the causes of the defects. The core of the algorithm is the window function that filters out groups of daily records where the errors of several radiation products, mainly satellite-based models, are greater than the typical values for that product, region and time of the year. The QC method was tested in 748 Spanish ground stations finding different operational errors such as shading or soiling, and some equipment errors related to the deficiencies of silicon-based photodiode pyranometers. The majority of these errors cannot be detected by traditional QC methods based on physical or statistical limits, and hence produce problems in most of the applications that require solar radiation data. Besides, these results manifest the low-quality of Spanish networks such as SIAR, Meteocat, Euskalmet and SOS Rioja, which show defects in more than a 50% of the stations and should be consequently avoided.