Last update: Oct. 2016


Heliosat-2 has been exploited to generate the HelioClim-1 database, and is launched in real time to generate HelioClim-3, our current database.

The Heliosat-2 method converts images acquired by meteorological geostationary satellites, such as Meteosat (Europe), GOES (USA) or GMS (Japan), into data and maps of solar radiation received at ground level. There is a wealth of publications on the various versions of the Heliosat-2 method. The original method is described in Cano et al. (1986), and the reference article is Rigollier et al. (2004) (see "publications" with the keyword "heliosat-2").

MINES ParisTech produced the method Heliosat-2 in November 2002, partly with the support of the European Commission (project SoDa, contract DG "INFSO" IST-1999-12245). More info and complete software (in C) and documentation are available for Heliosat-2.

Example of processing of Heliosat-2

Meteosat Second Generation raw image

Derived cloud index (or "clearness index")

Derived hourly irradiation


Input images

The method has originally been designed to process broadband images, i.e. 0.4-1.1 µm. It was thus perfectly suited to the Visible (VIS) band (0.45 to 1.0 µm) of Meteosat First Generation, the channel exploited to generate HelioClim-1

In the case of Meteosat second Generation (HelioClim-3), the High Resolution Visible (HRV - 0.4-1.1 µm) of the SEVIRI instrument doesn't cover the whole Meteosat disk. To generate HC3 on the whole Meteosat disk, we decided to process VIS0.6 (nominal spectral band: 0.56-0.71 µm) and VIS0.8 (0.74-0.88 µm) of Meteosat. The two images are merged into a synthetic image normalized according to the sensor and the sun elevation.

NB: The field of view is restricted to the pixels belonging to the Earth and for which an observer located on these pixels sees the satellite with an elevation angle above horizon larger than 12 degrees. This restriction generates missing values, in particular in winter time in the northern countries and reciprocally in summer time in the southern countries.

Principle: clear-sky model and cloud index

"Heliosat-2 combines a clear-sky model with a "cloud index". The cloud index approach is based on the assumption that the appearance of a cloud over a pixel results in an increase of reflectance in visible imagery; the attenuation of the downwelling shortwave irradiance by the atmosphere over a pixel is related to the magnitude of change between the reflectance that should be observed under a cloud-free sky and that currently observed. This magnitude of change is quantified by the cloud index.

HelioClim-3 version 4 (HC3v4) and version 5 (HC3v5) are the two most advanced versions of the HelioClim-3 database. HC3v4 uses the ESRA clear-sky model (Rigollier et al. 2000, Scharmer et al. 2000) with the climatological database of the Linke turbidity factor of Remund et al. (2003) as input. The major drawback of this database is that it is never updated to take into account changes in the atmosphere turbidity due to local effects such as maritime inputs, volcanoes, fires, evolution of the water vapor content, pollution…

The McClear clear sky model (Lefèvre et al. 2013) is an outcome of the European-funded MACC (Monitoring Atmospheric Composition & Climate - MACC-I, MACC-II and MACC-II) projects and is now operated by the CAMS (Copernicus Atmosphere Monitoring Service) projects. It takes as input updated information on the properties of the cloud-free atmosphere updated every 3 h and provides estimates of the Surface Solar Irradiance that should be observed if the sky were cloud-free for any site in the world since 2004. HC3v5 is an attempt to overcome the limitation of the climatological database of Remund et al. by combining HC3v4 and the McClear model (Qu et al. 2014)." extracted from Thomas et al. 2016