Title of article
Retrieval of mineral aerosol optical depth and size information from Meteosat Second Generation SEVIRI solar reflectance bands
Author/Authors
Brindley، نويسنده , , H.E. and Ignatov، نويسنده , , A.، نويسنده ,
Issue Information
روزنامه با شماره پیاپی سال 2006
Pages
20
From page
344
To page
363
Abstract
The current operational algorithm used to retrieve aerosol optical depth and Ångström exponent over ocean from the solar reflectance bands of the Advanced Very High Resolution Radiometer (AVHRR) flown onboard NOAA polar orbiting satellites was adapted to the corresponding channels of the Spinning Enhanced Visible and Infra-Red Imager (SEVIRI) flown onboard the Meteosat Second Generation (MSG) geostationary platform. By examining two specific dust events from 3–5 March and 12–13 October 2004 we show how a detailed description of the dust loading through the diurnal cycle can be obtained. Snapshot comparisons with spatially resolved retrievals from the MODerate resolution Imaging Spectrometer (MODIS) instruments flown on the Terra and Aqua polar platforms show qualitative agreement with SEVIRI retrievals. In addition to the generic aerosol model used in the NOAA/NESDIS algorithm, which was tuned to optimize retrievals over global ocean, three microphysical models, specifically proposed in the aerosol literature for desert dust, have also been tested. However, comparison of the diurnal variation seen in these SEVIRI retrievals with available ground based Aerosol Robotic Network (AERONET) observations from two coastal stations suggests that the phase functions associated with two of these dust representations, obtained under the assumption of particle sphericity, result in unrealistic time dependent behaviour. This tendency is removed when either the generic aerosol representation used in the NOAA/NESDIS algorithm is employed, or a more physically based non-spherical dust representation is used.
Keywords
Dust Aerosol , diurnal cycle , Microphysical aerosol models , Geostationary satellite observations
Journal title
Remote Sensing of Environment
Serial Year
2006
Journal title
Remote Sensing of Environment
Record number
1574893
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