The Ciemat Solar Radiation Group has been working over 20 years in the treatment of satellite images for calculating solar radiation. This activity has led to five doctoral theses and the publication of numerous scientific articles, many informative articles and training courses.
This website intends to offer solar radiation information available to any interested user. ADRASE allows viewing and downloading representative data of monthly average solar radiation over a long period, with a resolution of 5x5 km.
This project has its origins from the request of the Spanish Photovoltaic Union -UNEF- to Ciemat. Thus, in March 2012 the two institutions signed a cooperation agreement establishing the objectives of a first development to allow access to maps developed by Ciemat solar radiation from satellite imagery estimations.
IrSOLaV collaboration on this project has been critical and it has been focused on information management and architecture of the website.
The overall objective of the project is to estimate the spatial distribution of solar radiation representative of a long period. This objective is subdivided into two:
- Estimation of the likely daily solar radiation (monthly and annual average) for a long term period in each pixel. This objective is addressed through the treatment of satellite imagery developed and implemented by CIEMAT.
- Expected variability of monthly daily values estimation. This objective is addressed through the processing of measured data in more than 50 AEMET stations for over 10 years and the extrapolation of spatial variability found.
The relationship between these two sources of information is displayed in the "Validation" page. The results can be viewed and a comparison of Ciemat map data and AEMET measured data is made. Charts show sites with 10 or more years of measures, since they have been the most important for the development work, except in the case of locations in the Canary Islands.
Thus, users can access to solar radiation data, the value of the estimated long-term in a particular location and the estimated range of values most likely of "monthly average of the daily values" in a month and a specific year (between the 25 and 75 percentiles)
If a location has an average daily value for a particular month bigger than P75, it may consider a HIGH month from the average;
If a location has an average daily value of a particular month less than P25, it may consider a LOW month from the average;
Methodology for estimating global radiation
To characterize the spatial variability of solar radiation has been used the methodology to estimate solar radiation from satellite imagery. This methodology has been proven an excellent tool for performing solar resource maps and to supply temporary series of various components of solar irradiance [Zelenka, 1999], [Vignola, 2007], [Hoyer-Klick, 2009].
The methodology is based on processing geostationary satellites imagery [Polo, 2012]. In particular, a methodology developed in CIEMAT [Zarzalejo, 2005] is applied, [Polo, 2009], [Zarzalejo, 2009].
A satellite image in the visible channel is a measure of the short-wave radiance emitted from the Earth-atmosphere system at a given time and space, i.e., it is a measure of the emerging short-wave radiation. The radiance values collected by the radiometer on the satellite may vary according to the state of the atmosphere, from situations of clear to completely overcast sky, and the reflectivity characteristics of the Earth. In this sense, satellite imagery provides information about the cloudiness in an instant and certain location. Thus, it is possible to reproduce most of the variability associated with attenuation by clouds, establishing a functional relationship between the index of cloudiness (as an estimator of cloudiness) and the rate of clear sky (as an estimator of solar irradiance on the surface).
The method is based on estimating the index of cloudiness in each pixel (basic unit) of the image, from the determination of ρ (instant planetary albedo, i.e., the reflectance collected by the radiometer aboard the satellite), ρg and ρc (ground albedo and cloud albedo, respectively). Next, it is also estimated the global irradiance clear sky and finally the global horizontal irradiance.
Methodology for estimating the expected variability
To estimate the expected variability in each location, measured global horizontal irradiation data have been used (all data are registered with thermopile pyranometers). Distribution values for each month are analyzed, and estimated distance to the 25th and 75th to the central value is calculated. Thus, it is considered that these values give information about where 50% of daily data can be found in the distribution, although it may find data beyond these values.
From the calculated distance, a map is generated for all the extension through an IDW interpolation and the variability is applied to the radiation values estimated from satellite imagery.
Zelenka, A., Perez, R., Seals, R. and Renne, D., 1999. Effective accuracy of satellite-derived hourly irradiances. Theoretical and Applied Climatology. 62, 199-207.
Vignola, F., Harlan, P., Perez, R. and Kmiecik, M., 2007. Analysis of satellite derived beam and global solar radiation data. Solar Energy. 81, 768-772.
Hoyer-Klick, C., Beyer, H. G., Dumortier, D., Schroedter Homscheidt, M., Wald, L., Martinoli, M., Schillings, C., Gschwind, B. t., Menard, L., Gaboardi, E., Polo, J., Cebecauer, T., Huld, T., Suri, M., de Blas, M., Lorenz, E., Kurz, C., Remund, J., Ineichen, P., Tsvetkov, A. and Hofierka, J., 2009. MESoR - Management and exploitation of solar resource knowledge. Proceedings of: SolarPACES 2009, Berlin.
Polo, J. 2012. Generación de Mapas de Radiación Solar a partir de Satélites Geoestacionarios. Informes Técnicos CIEMAT num.1259. ISSN: 1135 – 9420. NIPO: 721-12-030-0.
Zarzalejo, L. F., 2005. Estimación de la irradiancia global horaria a partir de imágenes de satélite. Desarrollo de modelos empíricos. PhD presented at Universidad Complutense de Madrid.
Polo, J., 2009. Optimización de modelos de estimación de la radiación solar a partir de imágenes de satélite. PhD presented at Universidad Complutense de Madrid.
Zarzalejo, L. F., Polo, J., Martín, L., Ramírez, L. and Espinar, B., 2009. A new statistical approach for deriving global solar radiation from satellite images. Solar Energy. 83, 480-484.