The meteorological satellite images as data source to evaluate the ground irradiance components become the state of the art in the field of solar energy systems. The strongest argument is the high spatial coverage, and the fifteen minutes temporal granularity when using images from MSG. They also have the advantage to provide «real time» data used for example to assess the proper operation of a solar plant. On the other hand, long-term ground data are very scarce concerning the beam irradiance. The use of secondary inputs such as polar satellite data and ground information increases significantly the precision of the algorithms, mainly for the beam component. Following a paper from Zelenka concerning the nuggets effect, the interpolation distance to the nearest ground measurement site is limited to 10 to 30 km, depending on the irradiance parameter. This strengths the satellite derived data argument. The use of data derived from models or interpolated between nearby measurements sites are strongly related to the quality of the ground measurements used in the deriving process. This means that the preparatory steps are essential to ensure the quality of the data to be used as input to system simulations. Our approach is to first apply a stringent quality control, including time stamp of the data, absolute and relative calibration coefficient of the sensors, long term stability, components coherence etc., on the both the ground and modeled data.