Optimal estimation applied to the retrieval of aerosol load using MSG/SEVIRI observations

Using the principle of reciprocity, observations acquired by the SEVIRI radiometer on-board the Meteosat Second Generation satellites provide multi-angular and multi-spectral measurements that can be used for retrieving information on both the atmospheric aerosol load, and the Earth surface. The purpose of the presented new Land Daily Aerosol algorithm developed at EUMETSAT is to derive simultaneously the mean daily tropospheric aerosol load and the land surface properties from the SEVIRI observations. The algorithm is based on the Optimal Estimation theory. The aerosol load is calculated through the optical depth parameter, for various classes of aerosols over land surfaces, and is inferred from the inversion of a forward radiative transfer model against daily-accumulated observations in the 0.6, 0.8 and 1.6 SEVIRI bands. These daily time series provide the angular sampling used to discriminate the radiative effects that result from the surface anisotropy, from those caused by the aerosol scattering. Results of comparisons with AERONET data are presented to validate the modelling approach and the algorithm that resolves the inversion problem. The retrieval error is analysed, together with the effects on the retrieval quality of updating in time the prior information.

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