Quantifying the response of the ORAC aerosol optical depth retrieval for MSG SEVIRI to aerosol model assumptions

Abstract

We test the response of the Oxford-RAL Aerosol and Cloud (ORAC) retrieval algorithm for Meteosat Second Generation Spinning Enhanced Visible and InfraRed Imager (MSG SEVIRI) to changes in the aerosol properties used in the dust aerosol model, using data from the Dust Outflow and Deposition to the Ocean (DODO) flight campaign in August 2006. We find that using the observed DODO free tropospheric aerosol size distribution and refractive index increases simulated top of the atmosphere radiance at 0.55 m assuming a fixed aerosol optical depth of 0.5 by 10-15%, reaching a maximum difference at low solar zenith angles. We test the sensitivity of the retrieval to the vertical distribution of the aerosol and find that this is unimportant in determining simulated radiance at 0.55 m. We also test the ability of the ORAC retrieval when used to produce the GlobAerosol data set to correctly identify continental aerosol outflow from the African continent, and we find that it poorly constrains aerosol speciation. We develop spatially and temporally resolved prior distributions of aerosols to inform the retrieval which incorporates five aerosol models: desert dust, maritime, biomass burning, urban, and continental. We use a Saharan Dust Index and the GEOS-Chem chemistry transport model to describe dust and biomass burning aerosol outflow and compare AOD using our speciation against the GlobAerosol retrieval during January and July 2006. We find AOD discrepancies of 0.2-1 over regions of intense biomass burning outflow, where AOD from our aerosol speciation and GlobAerosol speciation can differ by as much as 50-70%. Copyright 2011 by the American Geophysical Union.