World Radiation Data Centre Research Articles

Empirical sunshine-based models vs online estimators for solar resources

Monthly averaged daily global solar irradiation data collected from four online platforms (NASA POWER, MERRA2, ERA5 and CAMS) are compared with ground measured data retrieved from World Radiation Data Center and Baseline Surface Radiation Network. Similarly, monthly averaged daily global solar irradiation estimated by five different Ångström-Prescott-type equations have been compared with the same ground measured data. The accuracy of the online platforms and Ångström – Prescott equations, respectively, is largely comparable, although some differences are noticed. Both the platforms and the Ångström-Prescott equations are sensitive to climates. A tendency of the Ångström-Prescott equations to exceed the platforms performance in the tropical and continental climates was noticed. Without exception the platforms and models perform better in summer than in winter. No Ångström – Prescott equation outperforms the platforms during all seasons, and, mutually, no platform outperforms the Ångström – Prescott equations during all seasons.

Open-Source Satellite-Derived Solar Resource Databases Comparison and Validation for Indonesia

Solar resource data derived from satellite imagery are widely available nowadays, either as an open-source or paid database. This article is intended to assess open-source databases, which cover the region of Indonesia. Here, four known solar resource databases, which spatially cover the Indonesian archipelago, have been used, namely, Prediction of Worldwide Energy Resource (POWER), Surface Solar Radiation–Heliosat-East (SARAH-E), CM SAF Cloud, Albedo, Radiation edition 2 (CLARA-A2), and SolarGIS. In addition, a minor portion of the Meteonorm database by Meteotest, around five sample points across Indonesia, has been assessed in terms of coherency to the four mentioned databases. Correlation coefficient and relative bias of the multiyear monthly mean annual cycle global horizontal irradiation (GHI) between pairs of databases are inspected. Three out of four databases are then validated through the available irradiation ground measurement data provided by the World Radiation Data Centre (WRDC). The correlation between each pair varies mostly between 0.7 and 1, which shows that the four databases to a certain extent agree on how the intermonthly variation would behave throughout the year. On the other hand, the validation result reveals that the three databases, i.e., POWER, CLARA-A2, and SARAH-E, are suffering from positive bias error ranging from 3% to 7%. Despite that fact, the correlation between measured and estimated values is still acceptable with SARAH-E showing the best performance among the three. Careful selections and adjustment enable the possibility of these databases to be utilized as a tool for depicting interannual and intermonthly variations of solar irradiation throughout the Indonesian archipelago.

Surface Diffuse Solar Radiation Determined by Reanalysis and Satellite over East Asia: Evaluation and Comparison

Recently, surface diffuse solar radiation (Rdif) has been attracting a growing interest in view of its function in improving plant productivity, thus promoting global carbon uptake, and its impacts on solar energy utilization. To date, very few radiation products provide estimates of Rdif, and systematic validation and evaluation are even more scare. In this study, Rdif estimates from Reanalysis Fifth Generation (ERA5) of European Center for Medium-Range Weather Forecasts and satellite-based retrieval (called JiEA) are evaluated over East Asia using ground measurements at 39 stations from World Radiation Data Center (WRDC) and China Meteorological Administration (CMA). The results show that JiEA agrees well with measurements, while ERA5 underestimates Rdif significantly. Both datasets perform better at monthly mean scale than at daily mean and hourly scale. The mean bias error and root-mean-square error of daily mean estimates are −1.21 W/m2 and 20.06 W/m2 for JiEA and −17.18 W/m2 and 32.42 W/m2 for ERA5, respectively. Regardless of over- or underestimation, correlations of estimated time series of ERA5 and JiEA show high similarity. JiEA reveals a slight decreasing trend at regional scale, but ERA5 shows no significant trend, and neither of them reproduces temporal variability of ground measurements. Data accuracy of ERA5 is more robust than JiEA in time but less in space. Latitudinal dependency is noted for ERA5 while not for JiEA. In addition, spatial distributions of Rdif from ERA5 and JiEA show pronounced discrepancy. Neglect of adjacency effects caused by horizontal photon transport is the main cause for Rdif underestimation of ERA5. Spatial analysis calls for improvements to the representation of clouds, aerosols and water vapor for reproducing fine spatial distribution and seasonal variations of Rdif.

Оценка солнечных ресурсов Кыргызстана с использованием программы «Meteonorm»

There are four actinometric stations (AS) in Kyrgyzstan located in the north-eastern part of the country, for which there is no information in open sources for the last 40 years. Databases (DBs) formed on the basis mathematical modeling and results of satellite sensing of the Earth's atmosphere and surface can be used to estimate the solar resources in the other regions of the country. Among the developed global and regional DBs in the field of solar energy, the Swiss Meteonorm DB is most widely used around the world, the adequacy of which can be verified by comparison with the data of actinometric stations. The long-term monthly solar radiation (SR) data contained in the Meteonorm DB are compared with the data of seven actinometric stations of Kyrgyzstan and neighboring countries from two available DBs: the World Radiation Data Center (WRDC) and the Scientific and Applied Reference Book on the Climate in the Soviet Union (SARB). The considered DBs are briefly described. It is shown based on the obtained analysis results that the values of data contained in the Meteonorm DB are higher than the data contained in the WRDC and SARB databases compiled using information from the actinometric stations. Moreover, this exceeding varies not only within the year, but also depending on the terrain latitude. An analysis of the long-term variability of the total SR according to the data of three ASs in the territory of countries neighboring with Kyrgyzstan from the WRDC DB has not revealed any trend of its change. The methods used for the newly developed mathematical model to restore the long-term average annual and monthly values of the total SR in Kyrgyzstan from the Meteonorm DB with taking the terrain latitude into account are described. An updated theoretical potential of solar energy in Kyrgyzstan is presented, and it is shown that the long-term average annual arrival of total solar energy varies insignificantly: from 1656 to 1856 kW-h/m2. Its average value is 1756 kW-h/m2.

Results of applicability analysis of satellite observations and reanalysis data for autonomous photovoltaic unit simulation

The accuracy analysis of energy performance prediction of autonomous photovoltaic units using various climate databases (NASA POWER, SARAH-E, CLARA-A, ERA5, Meteonorm, etc.) for some geographic points in Russia was performed by comparing with calculations using data of World Radiation Data Center. It is shown that the considered databases provide a spread of predictions of the required power of solar battery at the level of 10-20% only when solar fraction is less than 70%. For larger solar fraction, the prediction error of the required power of solar battery can reach hundreds of percent.

Results of Analysis of the Applicability of Satellite Observations and Reanalysis Data for Simulations of Autonomous Solar Power Systems

An accuracy of predicting energy performance of autonomous photovoltaic systems using various climatic databases (NASA POWER, SARAH-E, CLARA-A, ERA5, Meteonorm, etc.) has been analyzed for some geographic points in Russia by comparison with calculations based on data from the World Radiation Data Center. It has been showed that the databases considered provide a spread of predictions for required rated solar battery power at a level of 10–20% only when solar fraction is less than 70%. For a larger solar fraction prediction error of required rated solar battery power can reach several hundred percent.

Prediction and performance assessment of global solar radiation in Indian cities: A comparison of satellite and surface measured data

The design and performance assessment of solar photovoltaic/thermal system requires the knowledge of global solar radiation. Generalised models to assess the monthly average global solar radiation of twelve locations in India were established using sunshine hours available for 14 years (2000–2014) obtained from the World Radiation Data Centre (WRDC), Russia. Statistical analysis is carried out to assess the accurate model to estimate the global solar radiation which includes mean bias error, root mean square error, mean absolute percentage error, the coefficient of determination and uncertainty at 95%. Also, the assessment of the global radiation values obtained from satellite data by the National Renewable Energy Laboratory (NREL) is performed. Further, Global Performance Indicator (GPI) is introduced to find the ranking of models from the overall performance of the investigated models by scaling statistical indicators. The comparison of the NREL estimated data and WRDC data shows that the satellite data overestimates the surface measured data between 10 and 15% for seven locations, whereas, for the remaining four stations, it is between 7 and 9.5%.

The Global Energy Balance Archive (GEBA) version 2017: a database for worldwide measured surface energy fluxes

Abstract. The Global Energy Balance Archive (GEBA) is a database for the central storage of the worldwide measured energy fluxes at the Earth's surface, maintained at ETH Zurich (Switzerland). This paper documents the status of the GEBA version 2017 dataset, presents the new web interface and user access, and reviews the scientific impact that GEBA data had in various applications. GEBA has continuously been expanded and updated and contains in its 2017 version around 500 000 monthly mean entries of various surface energy balance components measured at 2500 locations. The database contains observations from 15 surface energy flux components, with the most widely measured quantity available in GEBA being the shortwave radiation incident at the Earth's surface (global radiation). Many of the historic records extend over several decades. GEBA contains monthly data from a variety of sources, namely from the World Radiation Data Centre (WRDC) in St. Petersburg, from national weather services, from different research networks (BSRN, ARM, SURFRAD), from peer-reviewed publications, project and data reports, and from personal communications. Quality checks are applied to test for gross errors in the dataset. GEBA has played a key role in various research applications, such as in the quantification of the global energy balance, in the discussion of the anomalous atmospheric shortwave absorption, and in the detection of multi-decadal variations in global radiation, known as global dimming and brightening. GEBA is further extensively used for the evaluation of climate models and satellite-derived surface flux products. On a more applied level, GEBA provides the basis for engineering applications in the context of solar power generation, water management, agricultural production and tourism. GEBA is publicly accessible through the internet via http://www.geba.ethz.ch. Supplementary data are available at https://doi.org/10.1594/PANGAEA.873078.

Generalized clearness index frequency curves for the Russian Federation

Actinometric data of World Radiation Data Center and NASA POWER were used to get daily clearness index frequencies for Russia. The results obtained provide the opportunity to estimate more accurately the output of various types of solar power plants. Frequencies determined using the data sources indicated correlate well and differ from universal dependences that were recommended earlier for the entire globe.

MATHEMATICAL MODEL OF SOLAR RADIATION INCIDENT ON AN ARBITRARILY ORIENTED SURFACE FOR ANY REGION IN RUSSIA

The paper deals with an original model of solar radiation incident on an arbitrarily oriented surface. This model has been designed to predict the main characteristics of solar radiation for any geographical point in Russia. The model is based on the isotropic model developed by Liu and Jordan and enables the researches to determine the values of solar radiation incident on an arbitrarily oriented surface at any given time period with the sampling interval of one second. The model implies the use of numerical values of the atmospheric transparency index and the surface albedo obtained from the NASA SSE (Surface meteorology and Solar Energy) database as initial data to ensure precise modeling of the incident solar radiation values including those for regions with no systematic actinometric observations. The paper presents the results of modeling the average daily values of solar radiation for ten Russian settlements located in the region between latitude of 43–62oN and longitude of 50–158oE. In order to verify the adequacy of the model, the results of instrumental terrestrial actinometric measurements are taken from meteorological stations included in the World Meteorological Organization network. The verification results show that the average relative model error for the considered meteorological stations does not exceed 11.7% for total solar radiation and 24.5% for scattered radiation. The authors developed the histograms of modeling errors in comparison with data from the World Radiation Data Center and NASA SSE. The analysis of the histograms revealed no systematic errors in the model since the errors were distributed uniformly and symmetrically with respect to the zero level. The paper compares the results of modeling the diurnal variation of solar radiation for 4 typical months of the year in Yekaterinburg with data from the World Radiation Data Center published in the periodic bulletin “Solar Radiation and Radiation Balance Data (The World Network)”. The developed model is implemented as a separate subsystem in MatLab/Simulink to enable its integration into the general model of the energy complex of an arbitrary configuration. The model can be used for studies concerned with the design, development and improvement of the energy systems including solar energy installations.

Solar global horizontal and direct normal irradiation maps in Spain derived from geostationary satellites

Solar radiation derived from satellite imagery is a powerful and highly accurate technique for solar resource assessment due to its maturity and to the long term database of observation images available. This work presents the methodology developed at CIEMAT for mapping solar radiation from geostationary satellite information and it also shows solar irradiation maps of global horizontal and direct normal components elaborated for Spain. The maps presented here have been developed from daily solar irradiation estimated for eleven years of satellite images (2001–2011). An attempt to evaluate the uncertainty of the presented maps is made using ground measurements from 27 meteorological stations available in Spain for global horizontal irradiation obtained from the World Radiation Data Centre. In the case of direct normal irradiation the ground measurement database was scarce, having available only six ground stations with measurements for a period of 4 years. Yearly values of global horizontal irradiation are around 1800kWhm−2 in most of the country and around 1950–2000kWhm−2 for annual direct normal irradiation. Root mean square errors in monthly means were of 11% and of 29% for global horizontal and direct normal irradiation, respectively.

Multi-location model for the estimation of the horizontal daily diffuse fraction of solar radiation in Europe

Hourly and daily solar radiation data are crucial for the design of energy systems based on the solar source. Global irradiance, measured on the horizontal plane, is, generally, available from weather station databases. The direct and diffuse fractions are measured rarely and should be analytically calculated for many geographical locations. Aim of this paper is to present a multi-location model to estimate the expected profiles of the horizontal daily diffuse component of solar radiation. It focuses on the European (EU) geographical area joining data from 44 weather stations located in 11 countries. Data are collected by the World Radiation Data Centre (WRDC) between 2004 and 2007. Different analytic functions, correlating the daily diffuse fraction of solar radiation to the clearness index, are calculated and compared to outline the analytic expressions of the best fitting curves. The effect of seasonality on solar irradiance is considered developing summer and winter scenarios together with annual models. Similarities among the trends for the 4years are, further, discussed. The most adopted statistical indices are used as key performance factors. Finally, data from three locations not included in the dataset considered for model development allow to test the proposed approach against an independent dataset. Obtained results show the effectiveness of adopting a multi-location approach to estimate solar radiation components on the horizontal surface instead of developing several single location models. This is due to the increase of the geographical range of applicability without a significant decrease of the accuracy. The percentage gap between single and multi-location model performances is lower than 20% for the most of the statistical indices adopted for both the model development and ex-post validation through the three independent datasets.

Applying spaceborne reflectivity measurements for calculation of the solar ultraviolet radiation at ground level

Abstract. Long-term analysis of cloud effects on ultraviolet (UV) radiation on the ground using spaceborne observations requires the use of instruments that have operated consecutively. The longest data record can be built from the reflectivity measurements produced by the instruments Total Ozone Mapping Spectrometers (TOMS) flown on Nimbus 7 from 1979 to 1992, TOMS on Earth Probe from 1996 to 2005, and the Ozone Monitoring Instrument (OMI) flown on EOS Aura since 2004. The reflectivity data produced by TOMS on Earth Probe is only included until 2002. A comparison is made with cloud effects inferred from ground-based pyranometer measurements at over 83 World Radiation Data Centre stations. Modelled UV irradiances utilizing the standard reflectivity are compared with measurements of UV irradiances at eight European low-elevation stations. The reflectivity data of the two TOMS instruments shows a consistent agreement, and the required corrections are of low percentage, i.e. 2–3%. In contrast, the reflectivity product of OMI requires correction of 7–10%, and a solar angle dependency therein is more pronounced. These corrections were inferred from a comparison with pyranometer data, and tested using the UV measurements. The average reduction of UV radiation due to clouds for all sites together indicates a small trend: a diminishing cloudiness, in line with ground-based UV observations. Uncorrected implementation of the reflectivity data would have indicated the opposite. An optimal area was established for reflectivity data for the calculation of daily sums of UV radiation. It measures approximately 1.25° in latitudinal direction for square-shaped areas overhead the ground-based UV stations. Such an area can be traversed within 5 to 7 h at the average wind speeds found for the West European continent.

Solar radiation estimations over India using Meteosat satellite images

India is endowed with good solar energy resource due to its geographic position in the equatorial Sun Belt of the earth, but its atmosphere can have eventual large presence of aerosols with the subsequent negative feedback to the solar radiation available. Therefore, solar resource assessment studies over India are of high interest for potential solar energy applications. In this work daily estimations of global horizontal and direct normal irradiation are presented for six locations in India covering the years from 2000 till 2007. These computations have been performed with IrSOLaV/CIEMAT method for computing solar radiation components from Meteosat images with a spatial resolution of less than 5 × 5 km. A brief assessment exercise of the model output have been made with ground measurements available from the World Radiation Data Centre database, which consists only of daily sums of global horizontal irradiation. The daily global horizontal irradiation estimated by the model has shown a general positive bias with the ground measurements in the range of 5%, being the root mean square deviation around 12%, excepting for Trivandrum location where there are evidences of higher uncertainty in the ground measurements. In addition, the dynamical behavior of daily global irradiation is quite well reproduced by the model as a consequence of adding to the input the daily turbidity values estimated from MODIS Terra satellite information. Estimations of direct normal irradiation are also exposed but no assessment was made due to the lack of ground measurements. The importance and need of accurate daily aerosol data with high spatial resolution for solar radiation estimations is pointed out in this work.

A test of Suehrcke’s sunshine–radiation relationship using a global data set

In this paper we investigate a new relationship between duration of sunshine and solar radiation on the earth’s surface that was derived recently by Suehrcke (Solar Energy, 68(5) (2000) 417). We test the relationship using over 70,000 measured monthly sunshine and radiation data from nearly 700 sites compiled by the World Radiation Data Center. We show that Suehrcke’s equation accounts adequately for the sunshine–radiation relationship on an average sense. There is a large dispersion (12% on average) in the values of solar radiation calculated by the new equation, however it is unclear how much of this dispersion could be accounted for by a better model. The predictive capabilities of the new model are actually roughly equivalent to those of older models such as Ångström–Prescott when the peculiarities of local climatic conditions are not taken into account.

Baseline Surface Radiation Network (BSRN/WCRP): New Precision Radiometry for Climate Research

To support climate research, the World Climate Research Programme (WCRP) initiated a new radiometric network, the Baseline Surface Radiation Network (BSRN). The network aims at providing validation material for satellite radiometry and climate models. It further aims at detecting long-term variations in irradiances at the earth's surface, which are believed to play an important role in climate change. The network and its instrumentation are designed 1) to cover major climate zones, 2) to provide the accuracy required to meet the objectives, and 3) to ensure homogenized standards for a long period in the future. The limits of the accuracy are defined to reach these goals. The suitable instruments and instrumentations have been determined and the methods for observations and data management have been agreed on at all stations. Measurements of irradiances are at 1 Hz, and the 1-min statistics (mean, standard deviation, and extreme values) with quality flags are stored at a centralized data archive at the WCRP's World Radiation Monitoring Center (WRMC) in Zurich, Switzerland. The data are quality controlled both at stations and at the WRMC. The original 1-min irradiance statistics will be stored at the WRMC for 10 years, while hourly mean values will be transferred to the World Radiation Data Center in St. Petersburg, Russia. The BSRN, consisting of 15 stations, covers the earth's surface from 80°N to 90°S, and will soon be joined by seven more stations. The data are available to scientific communities in various ways depending on the communication environment of the users. The present article discusses the scientific base, organizational and technical aspects of the network, and data retrieval methods; shows various application possibilities; and presents the future tasks to be accomplished.