Sources of uncertainty in annual global horizontal irradiance data

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)(+)(1)(8.)(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 (+6.)(9)(-5.4)%, 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.Peer reviewe

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 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.Peer reviewe

Quantifying the amplified bias of PV system simulations due to uncertainties in solar radiation estimates

Solar radiation databases used for simulating PV systems are typically selected according to their annual bias in global horizontal irradiance (G(H)) because this bias propagates proportionally to plane-of-array irradiance (G(POA)) and module power (P-DC). However, the bias may get amplified through the simulations due to the impact of deviations in estimated irradiance on parts of the modeling chain depending on irradiance. This study quantifies these effects at 39 European locations by comparing simulations using satellite-based (SARAH) and reanalysis (COSMO-REA6 and ERAS) databases against simulations using station measurements. SARAH showed a stable bias through the simulations producing the best Pp c predictions in Central and South Europe, whereas the bias of reanalyses got substantially amplified because their deviations vary with atmospheric transmissivity due to an incorrect prediction of clouds. However, SARAH worsened at the northern locations covered by the product (55-65 degrees N) underestimating both G(POA) and P-DC. On the contrary, ERAS not only covers latitudes above 65 degrees but it also obtained the least biased P-DC estimations between 55 and 65 degrees N, which supports its use as a complement of satellite-based databases in high latitudes. The most significant amplifications occurred through the transposition model ranging from +/- 1% up to +/- 6%. Their magnitude increased linearly with the inclination angle, and they are related to the incorrect estimation of beam and diffuse irradiance. The bias increased around + 1% in the PV module model because the PV conversion efficiency depends on irradiance directly, and indirectly via module temperature. The amplification of the bias was similar and occasionally greater than the bias in annual G(H), so databases with the smallest bias in G(H) may not always provide the least biased PV simulations.Peer reviewe

Evaluation of global horizontal irradiance estimates from ERA5 and COSMO-REA6 reanalyses using ground and satellite-based data

This study examines the progress made by two new reanalyses in the estimation of surface irradiance: ERAS, the new global reanalysis from the ECMWF, and COSMO-REA6, the regional reanalysis from the DWD for Europe. Daily global horizontal irradiance data were evaluated with 41 BSRN stations worldwide, 294 stations in Europe, and two satellite-derived products (NSRDB and SARAH). ERAS achieves a moderate positive bias worldwide and in Europe of + 4.05 W/m 2 and + 4.54 W/m 2 respectively, which entails a reduction in the average bias ranging from 50% to 75% compared to ERA-Interim and MERRA-2. This makes ERAS comparable with satellite-derived products in terms of the mean bias in most inland stations, but ERAS results degrade in coastal areas and mountains. The bias of ERAS varies with the cloudiness, overestimating under cloudy conditions and slightly underestimating under clear-skies, which suggests a poor prediction of cloud patterns and leads to larger absolute errors than that of satellite-based products. In Europe, the regional COSMO-REA6 underestimates in most stations (MBE = -5.29 W/m(2)) showing the largest deviations under clear-sky conditions, which is most likely caused by the aerosol climatology used. Above 45 degrees N the magnitude of the bias and absolute error of COSMO-REA6 are similar to ERAS while it outperforms ERA5 in the coastal areas due to its high-resolution grid (6.2 km). We conclude that ERAS and COSMO-REA6 have reduced the gap between reanalysis and satellite-based data, but further development is required in the prediction of clouds while the spatial grid of ERAS (31 km) remains inadequate for places with high variability of surface irradiance (coasts and mountains). Satellite-based data should be still used when available, but having in mind their limitations, ERAS is a valid alternative for situations in which satellite-based data are missing (polar regions and gaps in times series) while COSMO-REA6 complements ERA5 in Central and Northern Europe mitigating the limitations of ERA5 in coastal areas.Peer reviewe

Active learning and social commitment projects as a teaching-learning intervention in engineering degrees

[EN] The purpose of universities, apart from produce qualified professionals with problem-solving capabilities and soft-skills, should be to develop the social responsibility sense on their students. In this context, our proposal combines project based learning (PBL) and service based learning (SBL) along with gamming and the use of open-source machines, with the aim to increase student’s motivation and their social commitment with an affordable budget. The strategy, from now on named OS-PBL-SR (Open-Source-based PBL projects with Social Responsibility), mainly includes three important aspects: (i) assignment with projects orientated towards a social benefit; (ii) development of the projects using open-source Do It Yourself desktop machines (DIY-DkM); and (iii) include gamming in the evaluation method. The strategy was applied in the subject Manufacturing Technology but it might be easily exportable to other technical subjects. The results from the last academic year are presented. Also, a new OS-PBL-SR proposal aimed to the design and fabrication of autonomy-oriented products for people in a dependency situation is presented. The results showed the beneficial impact on undergraduate students by keeping high levels of motivation reflected on excellent success rates and scores. In addition, essential advantages in the use of DIY-DkM were found regarding the implementation of this kind of PBL strategy.The authors would like to acknowledge the financial support received from the University of La Rioja through the programs ‘Proyectos de Innovación Docente 2018/2019’. The authors also want to express their gratitude to the Instituto de Estudios Riojanos (IER). One of the authors, A.S.G., would also like to acknowledge the financial support from the Academy of Finland No. 273689.Pernía-Espinoza, A.; Sanz-Garcia, A.; Martinez-De-Pison-Ascacibar, FJ.; Peciña-Marqueta, S.; Blanco-Fernandez, J. (2019). Active learning and social commitment projects as a teaching-learning intervention in engineering degrees. En HEAD'19. 5th International Conference on Higher Education Advances. Editorial Universitat Politècnica de València. 281-288. https://doi.org/10.4995/HEAD19.2019.9605OCS28128

Assessment of microproject-based teaching/learning (MicroPBL) experience in industrial engineering degrees

An assessment program to evaluate microproject-based teaching/ learning (MicroPBL) methodology on the technical subject Manufacturing Technology was implemented for four consecutive academic years. Students from three engineering degrees were involved providing feedback through various surveys that allowed us to perform a proper evaluation. More specifically, students' surveys were anonymous after each academic year, except the last one, which included both non-anonymous pre and postsurveys. The polls were mainly meant to evaluate the acquisition of specific competences (using technical questions about the subject) as well as generic ones (using questions concerning soft-skills). Students' satisfaction with the methodology and with the signature, in general, were also checked. Nonanonymous surveys enabled us to study the correlation between polls results and students' final scores. Note that students' self-assessment concerning their knowledge about technical aspects drastically changed after the course. The average final score of this subject from student's perception was slightly higher than the real value. Moreover, student's self-perception on soft-skills increased at the end of the course. In general, the proposed MicroPBL methodology demonstrated a beneficial impact on students of Manufacturing Technology keeping high-motivation levels in students as well as high success rates and scores.Peer reviewe

Quality control of global solar radiation data with satellite-based products

Several quality control (QC) procedures are available to detect errors in ground records of solar radiation, mainly range tests, model comparison and graphical analysis, but most of them are ineffective in detecting common problems that generate errors within the physical and statistical acceptance ranges. Herein, we present a novel QC method to detect small deviations from the real irradiance profile. The proposed method compares ground records with estimates from three independent radiation products, mainly satellite-based datasets, and flags periods of consecutive days where the daily deviation of the three products differs from the historical values for that time of the year and region. The confidence intervals of historical values are obtained using robust statistics and errors are subsequently detected with a window function that goes along the whole time series. The method is supplemented with a graphical analysis tool to ease the detection of false alarms. The proposed QC was validated in a dataset of 313 ground stations. Faulty records were detected in 31 stations, even though the dataset had passed the Baseline Surface Radiation Network (BSRN) range tests. The graphical analysis tool facilitated the identification of the most likely causes of these errors, which were classified into operational errors (snow over the sensor, soiling, shading, time shifts, large errors) and equipment errors (miscalibration and sensor replacements), and it also eased the detection of false alarms (16 stations). These results prove that our QC method can overcome the limitations of existing QC tests by detecting common errors that create small deviations in the records and by providing a graphical analysis tool that facilitates and accelerates the inspection of flagged values.Peer reviewe

Tree-based ensembles unveil the microhabitat suitability for the invasive bleak (Alburnus alburnus L.) and pumpkinseed (Lepomis gibbosus L.): Introducing XGBoost to eco-informatics

[EN] Random Forests (RFs) and Gradient Boosting Machines (GBMs) are popular approaches for habitat suitability modelling in environmental flow assessment. However, both present some limitations theoretically solved by alternative tree-based ensemble techniques (e.g. conditional RFs or oblique RFs). Among them, eXtreme Gradient Boosting machines (XGBoost) has proven to be another promising technique that mixes subroutines developed for RFs and GBMs. To inspect the capabilities of these alternative techniques, RFs and GBMs were compared with: conditional RFs, oblique RFs and XGBoost by modelling, at the micro-scale, the habitat suitability for the invasive bleak (Alburnus alburnus L.) and pumpkinseed (Lepomis gibbosus L). XGBoost outperformed the other approaches, particularly conditional and oblique RFs, although there were no statistical differences with standard RFs and GBMs. The partial dependence plots highlighted the lacustrine origins of pumpkinseed and the preference for lentic habitats of bleak. However, the latter depicted a larger tolerance for rapid microhabitats found in run-type river segments, which is likely to hinder the management of flow regimes to control its invasion. The difference in the computational burden and, especially, the characteristics of datasets on microhabitat use (low data prevalence and high overlapping between categories) led us to conclude that, in the short term, XGBoost is not destined to replace properly optimised RFs and GBMs in the process of habitat suitability modelling at the micro-scale.This project had the support of Fundacion Biodiversidad, of Spanish Ministry for Ecological Transition. We want to thank the volunteering students of the Universitat Politecnica de Valencia, Marina de Miguel, Carlos A. Puig-Mengual, Cristina Barea, Rares Hugianu, and Pau Rodriguez. R. Munoz-Mas benefitted from a postdoctoral Juan de la Cierva fellowship from the Spanish Ministry of Science, Innovation and Universities (ref. FJCI-2016-30829). This research was supported by the Government of Catalonia (ref. 2017 SGR 548).Muñoz-Mas, R.; Gil-Martínez, E.; Oliva-Paterna, FJ.; Belda, E.; Martinez-Capel, F. (2019). Tree-based ensembles unveil the microhabitat suitability for the invasive bleak (Alburnus alburnus L.) and pumpkinseed (Lepomis gibbosus L.): Introducing XGBoost to eco-informatics. Ecological Informatics. 53:1-12. https://doi.org/10.1016/j.ecoinf.2019.100974S1125