In desert regions, dust is the most critical atmospheric parameter for irradiance assessment and solar resource conversion. Nowadays, atmospheric communities – chemical transport and re-analysis models – provide aerosols information, including dust, but with a spatial resolution greater than 100 km. This low spatial resolution makes the prediction of aerosol loads in a small scale very difficult, considering the possible high spatial variability of this aerosol loads in such desert regions. It has been indeed established in the United Arab Emirates that the variation of aerosol optical depth (AOD) within 100 km can lead to 18% deviation on Direct Normal Irradiance (DNI) estimations. Therefore, the MACC AOD, which is provided at a spatial resolution of 125 km, has to be corrected before being used for DNI estimation, as well as any other publicly available AOD database. In this work, images from the High Resolution Visible channel data of the SEVIRI instrument on board Meteosat Second Generation satellite are used to downscale the MACC AOD. The first results of the downscaling approach are tested with one year datasets of AOD from two AERONET ground stations showing that this downscaling leads to a decrease of the mean absolute error on AOD and on the corresponding estimated DNIs.