Validation of an AOT product over land at the 0.6 μm channel of the SEVIRI sensor onboard MSG

Abstract. The Spinning Enhanced Visible and InfraRed Imager (SEVIRI) aboard Meteosat Second Generation (MSG) launched in 2003 by EUMETSAT is dedicated to the Nowcasting applications and Numerical Weather Prediction and to provide information for climate monitoring and research. We use the data in visible and near infrared channels to derive the Aerosol Optical Thickness (AOT) over land. The algorithm is based on the assumption that the Top Of the Atmosphere (TOA) reflectance increases with the aerosol load. This is a reasonable assumption except in case of absorbing aerosols above bright surfaces. We assume that the minimum in a 14-day time series of the TOA reflectance is, once corrected from gaseous scattering and absorption, representative of the surface reflectance. The AOT and the aerosol model (a set of 5 models are used), are retrieved by matching the simulated TOA reflectance with the TOA reflectances measured by SEVIRI in its visible and Near Infra-Red (NIR) spectral bands. The high temporal resolution of the data acquisition by SEVIRI allows to retrieve the AOT every 15 min with a spatial resolution of 3km at sub-satellite point, over the whole SEVIRI disk which covers Europe, Africa and part of South America. The resulting AOT, a Level 2 product at the same temporal and spatial resolution than SEVIRI, is presented and evaluated in this paper. The AOT has been validated using ground based measurements from AERONET, a sun-photometer network, focusing over Europe for 3 months in 2006. The SEVIRI estimates correlate well with the AERONET measurements, r = 0.64, with a slight underestimate, bias = −0.017. The sources of errors are mainly the cloud contamination and the bad estimation of the surface reflectance. The temporal evolutions exhibited by both dataset show very good agreement which allows to conclude that the AOT Level 2 product from SEVIRI can be used to quantify the aerosol content and to monitor its daily evolution with a high temporal frequency. The comparison with daily maps of MODIS AOT level 3 product shows qualitative good agreements in the retrieved geographic patterns of AOT. Given the high spatial and temporal resolutions obtained with this approach, our results have clear potential for applications ranging from air quality monitoring to climate studies.