Improved total atmospheric water vapour amount determination from near-infrared filter measurements with sun photometers

International audienceIn this work we explore the effect of the contribution of the solar spectrum to the recorded signal in wavelengths outside the typical 940-nm filter's bandwidth. We use gaussian-shaped filters as well as actual filter transmission curves to study the implications imposed by the non-zero out-of-band contribution to the coefficients used to derive precipitable water from the measured water vapour band transmittance. The moderate-resolution SMARTS radiative transfer code is used to predict the incident spectrum outside the filter bandpass for different atmospheres, solar geometries and aerosol optical depths. The high-resolution LBLRTM radiative transfer code is used to calculate the water vapour transmittance in the 940 nm band. The absolute level of the out-of-band transmittance has been chosen to range from 10?6 to 10?4, and typical response curves of commercially available silicon photodiodes are included into the calculations. It is shown that if the out-of-band transmittance effect is neglected, as is generally the case, then the derived columnar water vapour is systematically underestimated by a few percents. The actual error depends on the specific out-of-band transmittance, optical air mass of observation and water vapour amount. We apply published parameterized transmittance functions to determine the filter coefficients. We also introduce an improved, three-parameter, fitting function that can describe the theoretical data accurately, with significantly less residual effects than with the existing functions. Further investigations will use experimental data from field campaigns to validate these findings

Technical Note: Improved total atmospheric water vapour amount determination from near-infrared filter measurements with sun photometers

International audienceIn this work we explore the effect of the contribution of the solar spectrum to the recorded signal in wavelengths outside the typical 940-nm filter's bandwidth. We employ gaussian-shaped filters as well as actual filter transmission curves, mainly AERONET data, to study the implications imposed by the non-zero out-of-band contribution to the coefficients used to derive precipitable water from the measured water vapour band transmittance. Published parameterized transmittance functions are applied to the data to determine the filter coefficients. We also introduce an improved, three-parameter, fitting function that can describe the theoretical data accurately, with significantly less residual effects than with the existing functions. The moderate-resolution SMARTS radiative transfer code is used to predict the incident spectrum outside the filter bandpass for different atmospheres, solar geometries and aerosol optical depths. The high-resolution LBLRTM radiative transfer code is used to calculate the water vapour transmittance in the 940-nm band. The absolute level of the out-of-band transmittance has been chosen to range from 10?6 to 10?4, and typical response curves of commercially available silicon photodiodes are included into the calculations. It is shown that if the out-of-band transmittance effect is neglected, as is generally the case, then the derived columnar water vapour is mainly underestimated by a few percents. The actual error depends on the specific out-of-band transmittance, optical air mass of observation and water vapour amount. Further investigations will use experimental data from field campaigns to validate these findings

Solar irradiance component separation benchmarking: The critical role of dynamically-constrained sky conditions

The decomposition of global horizontal irradiance into its direct and diffuse components is critical in many applications. To guarantee accurate results in practice, the existing separation techniques need to be validated against reference ground measurements from a variety of stations. Here, four versions of the recent GISPLIT model are compared to a strong benchmark constituted from nine leading models of the literature. The validation database includes ≈24 million data points and is constituted of one calendar year of 1-min high-quality data from 118 research-class world stations covering all continents and all five major Ko¨ppen-Geiger climates. The results are analyzed with various statistical metrics to be as generalizable and explicative as possible. It is found that even the simpler GISPLIT version reduces the mean site RMSE of the best benchmark model by ≈11 % for the direct component and ≈17 % for the diffuse component. The improvement reaches ≈17 % and ≈25 %, respectively, when using the best GISPLIT version. The improvements are more important in cases of highly variable sky cloudiness, per the CAELUS sky classification scheme. A ranking analysis shows that all four versions of GISPLIT ranked higher than the benchmark models, and that the use of machine learning significantly im- proves the separation performance. In contrast, only marginal improvements are obtained through preliminary conditioning by Ko¨ppen-Geiger climate class. Overall, it is concluded that GISPLITv3, which is not dependent on climate class but makes use of machine learning for the most challenging sky conditions, can be asserted as the new high-performance quasi-universal separation model.This work was supported by the project PID2019-107455RB-C21 funded by MCIN/AEI/10.13039/501100011033 and the project UMA20-FEDERJA-134 jointly funded by the FEDER 2014–2020 Oper- ative Program and the Consejería de Economía, Conocimiento, Empre- sas y Universidad of the Junta de Andalucía. The University of Málaga/ CBUA provided the funding for open access. The authors would like to thank the scientists and personnel in charge of the BSRN stations for acquiring, processing and kindly sharing their datasets, which have been central to this study. Moreover, the authors acknowledge the scientists and personnel of the Global Modelling and Assimilation Office at NASA Goddard Space Flight Center who provided the MERRA-2 atmospheric data that were advantageously used to calculate the clear-sky solar irradiance at all sites. This work has been stimulated in great part by the authors’ participation to Task 16 of the International Energy Agency’s Photovoltaic Power Systems Programme. The other Task participants were instrumental in developing the robust quality-control algorithm prominently used here to improve the measured irradiance database

Recherches analytiques du platine dans les Alpes .- Quatriéme mémoire

Mes trois premiers mémoires appartiennent aujourd'hui au domaine public. Le quatrième est connu par ma correspondance particulière avec quelques membres du Corps impérial des mines, plusieurs membres de l'Institut et quelques savants étrangers. J'ai demandé à tous des avis, une direction; Cinq années de laborieuses recherches n'ont pu suffire pour la solution du problème le plus intéressant que les Alpes peuvent offrir. Je vais exposer rapidement les résultats que j'ai obtenus en 1852. Le nombre de pages accordées par le conseil général du département ne me permet pas de donner plus de détails

Recherches analytiques du platine dans les Alpes françaises - 3° mémoire

Mon premier Mémoire sur la découverte du platine, lu à l'Institut le 31 décembre 1849 par M, Arago, donna lieu à une mission scientifique de la part do M. le Ministre des travaux publics. A la suite de divers voyages pour étudier des gîtes, j'ai pris des échantillons sur un grand nombre de points. Je les ai classés par espèces, et j'ai pu commencer mes analyses vers le 1er novembre dernier. Cette division par espèces m'a paru peut-être plus commode pour mes lecteurs, que celle que j'avais adoptée dans mon second Mémoire, en exposant les résultats d'analyses par cantonnements

Recherche analytique du platine dans les Alpes - 2° mémoire

Document publié chez Allier -GrenobleMon premier mémoire sur la découverte du platine a élé lu à l'Institut, le 31 décemhre 1849, paMr Arago. La présence d'un métal si précieux dans nos Alpes fut accueillie avec empressement par tous les savants et de suite le Gouvernement me donna une mission scientifique, en 1850, pour continuer mes études. J 'ai adressé à M. le Ministre des travaux publics, le 18 avril 1851, mes Mémoires sur les recherches faites en 1850. Les résultats obtenus sont d'un grand intérêt scientifique et la mission qui m'avait été confiée continuera en 1851. Je vais donner l'extrait de mes travaux, exécutes au laboratoire du département. Toutefois, je dois indiquer que les frais ont été supportés par l'État. Je suivrai l'ordre de mes Mémoires, dont l'insertion dans les Annales des Mines vient d'être ordonnée par le Ministre des travaux publics

A bankable method of assessing the performance of a CPV plant

Concentrating Photovoltaics (CPV) is an alternative to flat-plate module photovoltaic (PV) technology. The bankability of CPV projects is an important issue to pave the way toward a swift and sustained growth in this technology. The bankability of a PV plant is generally addressed through the modeling of its energy yield under a baseline loss scenario, followed by an on-site measurement campaign aimed at verifying its energy performance. This paper proposes a procedure for assessing the performance of a CPV project, articulated around four main successive steps: Solar Resource Assessment, Yield Assessment, Certificate of Provisional Acceptance, and Certificate of Final Acceptance. This methodology allows the long-term energy production of a CPV project to be estimated with an associated uncertainty of ≈5%. To our knowledge, no such method has been proposed to the CPV industry yet, and this critical situation has hindered or made impossible the completion of several important CPV projects undertaken in the world. The main motive for this proposed method is to bring a practical solution to this urgent problem. This procedure can be operated under a wide range of climatic conditions, and makes it possible to assess the bankability of a CPV plant whose design uses any of the technologies currently available on the market. The method is also compliant with both international standards and local regulations. In consequence, its applicability is both general and international

An all-sky radiative transfer method to predict optimal tilt and azimuth angle of a solar collector

This paper describes a radiative transfer method for calculating radiances in all-sky conditions and performing an integration over the view hemisphere of an arbitrary plane to calculate tilted irradiance. The advantage of this method is the combination of cloud parameters inside the radiative transfer model with a tilt procedure. For selected locations this method is applied with cloud, ozone, water vapour and aerosol input data to determine tilted irradiance, horizontal irradiance and optimal tilt angle. A validation is performed for horizontal and tilted irradiance against high-quality pyranometer data. For 27 sites around the world, the annual horizontal irradiation predicted by our model had a mean bias difference of +0.56% and a root-mean-squared difference of 6.69% compared to ground measurements. The difference between the annual irradiation estimates from our model and the measurements from one site that provides tilted irradiance were within ±6% for all orientations except the north-facing vertical plane. For European and African sites included in the validation, the optimal tilt from our model is typically a few degrees steeper than predictions from the popular PVGIS online tool. Our model is generally applicable to any location on the earth’s surface as the satellite cloud and atmosphere data and aerosol climatology data are available globally. Furthermore, all of the input data are standard variables in climate models and so this method can be used to predict tilted irradiance in future climate experiments

GISPLIT: High-performance global solar irradiance component-separation model dynamically constrained by 1-min sky conditions

The separation of global horizontal irradiance (GHI) into its direct and diffuse components is necessary in a variety of applications, most specially in solar energy utilization, where knowledge of direct normal irradiance (DNI) is of paramount importance. Here a novel and efficient model, referred to as GISPLIT, is presented to perform this task accurately, using time series of measured data at 1-min resolution. To better describe the radiative effects of different cloud situations, the model takes advantage of a preliminary classification of the sky conditions into six sky types. An empirical submodel is assigned to each sky class to split GHI into its components, using a limited number of predictors that are related to GHI’s magnitude and variability, and to coincident estimates of the clear-sky irradiance components. Those submodels are trained and validated using rigorously quality-assessed measurements from 120 radiometric stations over all continents and all five major Köppen-Geiger (KG) climate classes, totaling ≈64 million valid data points. Four model versions are evaluated using training data for either all KG climate regions combined or conditioned by KG climate, and either with or without additional support from machine learning. The validation of the four versions suggests that the conditioning by KG climate does not add any significant benefit over the “all-climates” training approach and that, overall, the model version trained with data from all KG climates combined and supported by machine learning generally predicts DNI with the best RMSE results at unseen sites, although with little difference over the other versions.Funding for open Access charge: Universidad de Málaga / CBUA. This work was supported by the project PID2019-107455RB-C21 funded by MCIN/AEI/ 10.13039/501100011033, the project UMA20-FEDERJA-134 jointly funded by the FEDER 2014-2020 Operative Program and the Consejería de Economía, Conocimiento, Empresas y Universidad of the Junta de Andalucía, and by Solargis s.r.o. through the collaboration agreement 2021-124 with the University of M´alaga. The authors would like to thank the scientists and personnel in charge of the BSRN stations for acquiring, processing and kindly sharing their datasets, which have been central to this study. Moreover, the authors acknowledge the scientists and personnel of the Global Modelling and Assimilation Office at NASA Goddard Space Flight Center who provided the MERRA-2 atmospheric data that were advantageously used to calculate the clear-sky solar irradiance at all sites. This work has been stimulated in great part by the authors’ participation to Task 16 of the International Energy Agency’s Photovoltaic Power Systems Programme. The other Task participants were instrumental in developing the robust quality-control algorithm prominently used here to improve the measured irradiance databases