Aerosol retrievals from METEOSAT-8 - CM SAF

SAF on Climate Monitoring Visiting Scientists Report Doc. No: 1.0
Issue : 1.0
Date : 4 October 2006
Previous generations of geostationary meteorological satellites, such as METEOSAT and GOES
have been widely used to monitor aerosol properties over oceans (Moulin et al., 1997). However,
the spectral channels of the first generation METEOSAT were rather limited for accurate retrievals
of aerosol parameters. More advanced aerosol retrievals have been done with polar orbiting
satellites such as NOAA-AVHRR, MERIS, SEAWIFS and MODIS (Ramon 2001, Ramon
2004,and Kaufman and Tanre, 1997). The Spinning Enhanced Visible and Infrared Imager
(SEVIRI) onboard Meteosat Second Generation operates channels in the visible and near IR
wavelength regions that are similar to e.g. NOAA-AVHRR and MODIS. Therefore, the launch of
the MSG family is a great opportunity to test new ideas for filling the gap between retrievals from
geostationary and polar orbiting satellites, as SEVIRI combines the specific advantages of the
geostationary orbit and geometric, radiometric and spectroscopic capabilities of the
NOAA/AVHRR family.
The objective of this Visiting Scientist activity is to perform a user requirement and feasibility study
to catch the main steps of a future operational algorithm for retrieving the aerosol optical properties
over land from the MSG/SEVIRI instrument. For the feasibility study we kept the shortest time
resolution available from MSG i.e. 15 minutes. This constraint could be relaxed in the future but we
wanted to start with the strongest constraint. The short time for this study forced us to restrict
ourselves to the main difficulty of all aerosol retrieval algorithms that are applied over land
surfaces, i.e. the removal of the surface contribution to the satellite signal. This is needed for all
existing sensors and aerosol retrieval algorithms. In this study our approach is to demonstrate,
mainly through real data analysis, that the core idea of this future algorithm is correct and that
significant results are achievable with very simple assumptions. However, the output of this study
should not be taken neither as an Algorithm Theoretical Basis Document nor an algorithm
specification document. A lot of crude assumptions have to be refined in order to reach a complete
and robust algorithm. A very recent paper under press and not available at the beginning of the
work draws very similar conclusions as ours but for the GOES sensor (Knapp et al. 2005).
The user requirements for an aerosol product over land from SEVIRI are detailed in chapter 3. In
chapter 4 the main algorithm classes and performances are briefly reviewed. Then we will explain
in chapter 5 our methodology and show some first results. We will end in chapter 6 with giving
some research directions and list all potential improvements we foresee at the moment.
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