Solar radiation derived from satellite images

Abstract

The accurate knowledge of solar radiation at the earths surface is of great interest in solar energy, meteorology, and many climatic applications. Ground solar irradiance data is the most accurate method for characterising the solar resource of a given site. However, despite the availability of ground databases is growing up through different measuring networks, its spatial density is usually far too low. In consequence, satellite-derived solar radiation has become a valuable tool for quantifying the solar irradiance at ground level for a large area. Thus, derived hourly values have proven to be at least as good as the accuracy of interpolation from ground stations at a distance of 25 km (Zelenka et al. 1999). Several algorithms and models have been developed during the last two decades for estimating the solar irradiance at the earth surface from satellite images (Gautier et al. 1980; Tarpley 1979; Hay 1993). They can be generally grouped into physical and pure empirical or statistical models (Noia et al. 1993a, 1993b). Statistical models are simpler, since they do not need extensive and precise information on the composition of the atmosphere, and rely on simple statistical regression between satellite information and solar ground measurements. On the contrary, the physical models require as input the information of the atmospheric parameters that model the solar radiation attenuation through the earths atmosphere. On the other hand, the statistical approach needs ground solar data and the models suffer of lack of generality Satellites observing the earth can be grouped, according to its orbit, in polar orbiting and geostationary satellites. The former, with an orbit of about 800 km have high spatial resolution but a limited temporal coverage. The geostationary satellites, orbiting at about 36000 km, can offer a temporal resolution of up to 15 minutes and a spatial resolution of up to 1 km. Most of the methods for deriving solar radiation from satellite information make use of geostationary satellite images. © 2008 Springer-Verlag Berlin Heidelberg. All rights are reserved.