Sources of uncertainty in annual global horizontal irradiance data. (August 2018) - Urraca, Ruben; Huld, Thomas; Martinez-de-Pison, Francisco Javier; Sanz-Garcia, Andres
Highlights: Operational errors introduce the largest uncertainties in annual radiation data. Operational errors are frequent in low-quality monitoring networks. Satellite-based products provide the estimations with the lowest uncertainty. The annual uncertainty of SIAR photodiodes is close to that of SARAH-1. SIAR photodiodes are probably uncorrected or inadequately corrected. Abstract: The major sources of uncertainty in short-term assessment of global horizontal radiation ( G ) are the pyranometer type and their operation conditions for measurements, whereas the modeling approach and the geographic location are critical for estimations. The influence of all these factors in the uncertainty of the data has rarely been compared. Conversely, solar radiation data users are increasingly demanding more accurate uncertainty estimations. Here we compare the annual bias and uncertainty of all the mentioned factors using 732 weather stations located in Spain, two satellite-based products and three reanalyses. The largest uncertainties were associated to operational errors such as shading (bias = −8.0%) or soiling (bias = −9.4%), which occurred frequently in low-quality monitoring networks but are rarely detected because they pass conventional QC tests. Uncertainty in estimations greatly changed from reanalysis to satellite-based products, ranging from the gross accuracy of ERA-Interim ( + 6.1 - 6.7 + 18.8 %) to the high quality and spatial homogeneity of SARAH-1 ( + 1.4 - 5.3 + 5.6 %). Finally, photodiodes from the Spanish agricultural network SIAR showed an uncertainty of - 5 . 4 + 6 . 9 %, which is far greater than that of secondary standards ( ± 1.5%) and similar to SARAH-1. This is probably caused by the presence of undetectable operational errors and the use of uncorrected photodiodes. Photodiode measurements from low-quality monitoring networks such as SIAR should be used with caution, because the chances of adding extra uncertainties due to poor maintenance or inadequate calibration considerably increase.