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Solar irradiance data from high-quality ground-based measurements are primordial for different solar energy applications. In order to achieve the required accuracy, quality control procedures are of great benefit. A variety of approaches have been proposed. In this sense, some approaches propose a visual representation of the routine, while others only provide a time series of binary flag values, and do not propose any specific visualization of the flagged data as opposed to non-flagged ones. In this regard, the present paper puts forward a complete routine including several quality control procedures for solar irradiance measurements by providing visual support for these different approaches. The visual tool in question was validated using five years research data with 10 minutes resolution of the global, diffuse and direct components of solar irradiation collected from three ground-based weather stations in Morocco. This visual tool puts forth a more precise idea of the measurement quality by detecting various errors, such as time shifts, outliers identification; either with one or two components, or consistency tests between the three components of solar radiation when available. The proposed tool can be regarded as a means of improving the detection rate of abnormal data as a first step in diagnosing the prominent causes of error. [ABSTRACT FROM AUTHOR]

A database containing 10 min means of downward surface solar irradiance measured on a horizontal plane in several ultraviolet and visible bands from July 2014 to December 2016 at three stations in the area of the city of Ostrava (Czech Republic) is presented. The database contains time series of 10 min average irradiances or photosynthetic photon flux densities measured in the following spectral bands: [280, 315] nm (UVB); [315, 380] nm (UVA); [400, 700] nm (photosynthetically active radiation, PAR); [510, 700] nm; [600, 700] nm; [610, 680] nm; [690, 780] nm; [400, 1100] nm. A series of meteorological variables including relative air humidity and air temperature at surface is also provided at the same 10 min time step at all three stations, and in addition air pressure, wind speed and wind direction at two stations. These two stations offer additional data: PM10, SO2, NOx, NO, NO2 concentrations. The details of the experimental sites and instruments used for the measurements are given. Special attention is given to the data quality, and the process applied to label suspicious or erroneous measurements is described in detail. About 130 000 records for all three stations are available in the database. This database offers a unique ensemble of variables having a high temporal resolution and it is a reliable source on radiation in relation with environment and vegetation in highly polluted areas of industrial cities in the middle of Europe. [ABSTRACT FROM AUTHOR]

A new method has been developed to estimate the global and direct solar irradiance in the UV-A and UV-B at ground level in cloud-free conditions. It is based on a resampling technique applied to the results of the k- distribution method and the correlated-k approximation of Kato et al. (1999) over the UV band. Its inputs are the aerosol properties and total column ozone that are produced by the Copernicus Atmosphere Monitoring Service (CAMS). The estimates from this new method have been compared to instantaneous measurements of global UV irradiances made in cloud-free conditions at five stations at high latitudes in various climates. For the UV-A irradiance, the bias ranges between -0.8Wm-2 (-3% of the mean of all data) and -0.2Wm-2 (-1 %). The root mean square error (RMSE) ranges from 1.1Wm-2 (6 %) to 1.9Wm-2 (9 %). The coefficient of determination R2 is greater than 0.98. The bias for UV-B is between -0.04Wm-2 (-4 %) and 0.08Wm-2 (±13 %) and the RMSE is 0.1Wm-2 (between 12 and 18 %). R2 ranges between 0.97 and 0.99. This work demonstrates the quality of the proposed method combined with the CAMS products. Improvements, especially in the modeling of the reflectivity of the Earth's surface in the UV region, are necessary prior to its inclusion into an operational tool. [ABSTRACT FROM AUTHOR]

This study investigates the characteristic time-scales of variability found in long-term time-series of daily means of estimates of surface solar irradiance (SSI). The study is performed at various levels to better understand the causes of variability in the SSI. First, the variability of the solar irradiance at the top of the atmosphere is scrutinized. Then, estimates of the SSI in cloud-free conditions as provided by the McClear model are dealt with, in order to reveal the influence of the clear atmosphere (aerosols, water vapour, etc.). Lastly, the role of clouds on variability is inferred by the analysis of in-situ measurements. A description of how the atmosphere affects SSI variability is thus obtained on a time-scale basis. The analysis is also performed with estimates of the SSI provided by the satellite-derived HelioClim-3 database and by two numerical weather reanalyses: ERA-Interim and MERRA2. It is found that HelioClim-3 estimates render an accurate picture of the variability found in ground measurements, not only globally, but also with respect to individual characteristic time-scales. On the contrary, the variability found in re-analyses correlates poorly with all scales of ground measurements variability. [ABSTRACT FROM AUTHOR]

This study is concerned with the intrinsic temporal scales of the variability of the surface solar irradiance (SSI). The data consist of decennial time-series of daily means of the SSI spanning ten years, obtained from high quality measure- ments of the broadband solar radiation impinging on a horizontal plane at ground level, issued from different Baseline Surface Radiation Network (BSRN) ground stations around the world. First, embedded oscillations roughly sorted by ranges of in- creasing time-scales of the data are extracted by empirical mode decomposition. Next, Hilbert spectral analysis is applied to obtain an amplitude modulation-frequency-modulation (AM-FM) representation of the data. The time-varying nature of the characteristic time-scales of variability, along with the variations of the signal intensity, are thus revealed. A novel, adaptive null-hypothesis based on the general statistical characteristics of noise is employed, in order to discriminate between the different features of the data, those that have a deterministic origin and those being realisations of various stochastic processes. The data has a significant spectral peak corresponding to the yearly variability cycle and features quasi-stochastic high-frequency "weather noise", irrespective of the geographical location or of the local climate. Moreover, the amplitude of this latter feature is shown to be modulated by variations of the yearly cycle, indicative of non-linear multiplicative cross-scale couplings. The study has possible implications on the modelling and the forecast of the surface solar radiation, by clearly discriminating the deterministic from the quasi-stochastic character of the data, at different local time-scales. [ABSTRACT FROM AUTHOR]

The integration of massive solar energy supply in the existing grids requires an accurate forecast of the solar resources to manage the energetic balance. In this context, we propose a new approach to forecast the Global Horizontal Irradiance at ground level from satellite images and ground based measurements. The training of spatio-temporal multidimensional autoregressive models with HelioClim-3 data along with 15-min averaged GHI times series is tested with respect to a ground based station from the BSRN network. Forecast horizons from 15 min to 1 h provided very promising results validated on a one year ground-based pyranometric data set. The performances have been compared to another similar method from the literature by means of relative metrics. The proposed approach paves the way of the use of satellite-based surface solar irradiance (SSI) estimation as an SSI map nowcasting method that enables to capture spatio-temporal correlation for the improvement of a local SSI forecast. [ABSTRACT FROM AUTHOR]

Meteosat satellite images are processed to yield values of the incoming surface solar irradiance (SSI), one of the Essential Climate Variables. Two HelioClim databases, HC-1 and HC-3, were constructed covering Europe, Africa and the Atlantic Ocean, and contain daily and monthly means of SSI. The HC-1 database spans from 1985 to 2005; HC-3 began in 2004 and is updated daily. Their quality and limitations in retrieving monthly means of SSI have been studied by a comparison between eleven stations offering long time-series of measurements. A good agreement was observed for each site: bias was less than 10 W/m² in absolute value (5% in relative value) for HC-3. HC-1 offers a similar quality, though it underestimates the SSI for latitudes greater than 45° and less than −45°. Time-series running from 1985 to date can be created by concatenating the HC-1 and HC-3 values and could help in assessing SSI and its changes. [ABSTRACT FROM AUTHOR]

Natural daylight is recognized as an important variable in the energy performance of buildings. A method that estimates the global illuminance received on a horizontal surface at ground level and its direct component at normal incidence under cloudless conditions is presented. The method uses the k-distribution method and the correlated-k approximation to compute a set of clearness indices integrated over 13 spectral bands covering the range 380–780 nm. A spectral resampling technique, including a spectral disaggregation and a spectral linear interpolation, is applied to these indices for providing a detailed set of solar irradiances at 1 nm in spectral resolution over the whole range. Then, these are weighted by the standardized CIE action spectrum for human eye for assessing the illuminance. Inputs to the method include the total column contents of ozone and water vapor as well as aerosol optical properties produced by the Copernicus Atmosphere Monitoring Service. Estimates of illuminance were compared to high-quality 1 min measurements of illuminance that were collected from two experimental sites located in two different climatic zones. A slight overestimation is observed for the global illuminance: the bias is between +1 klx and +3 klx, i.e., between +1% and +4% in relative value. The root mean square error varies between 5 klx (8%) and 6 klx (9%). The squared correlation coefficient ranges between 0.95 and 0.97. At the site providing the direct illuminance at normal incidence, the performance of the method is lower compared to global illuminance with a lower squared correlation coefficient of 0.53. The bias, relative bias, RMSE, and rRMSE are +7 klx, +9%, 12 klx, and 15%, respectively. The uncertainty of the method is of the order of the uncertainty of the measurements. The method offers accurate estimates of illuminance in cloudless conditions at high spatial and temporal resolutions useful for construction industries and operators as well as thermal simulation tools for optimal building design strategies. [ABSTRACT FROM AUTHOR]