http://www.cnr.it/ontology/cnr/individuo/prodotto/ID169234

Aerosol Characterization and Optical Thickness Retrievals Using GOME and METEOSAT Satellite Data (Articolo in rivista)

Type

Label

Aerosol Characterization and Optical Thickness Retrievals Using GOME and METEOSAT Satellite Data (Articolo in rivista) (literal)

Anno

Alternative label

M. J. Costa, M. Cervino, E. Cattani, F. Torricella, V. Levizzani, A. M. Silva, S. Melani (2002)
Aerosol Characterization and Optical Thickness Retrievals Using GOME and METEOSAT Satellite Data
in Meteorology and atmospheric physics (Print)
(literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori

M. J. Costa, M. Cervino, E. Cattani, F. Torricella, V. Levizzani, A. M. Silva, S. Melani (literal)

Pagina inizio

Pagina fine

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Rivista

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Metodologia per la stima di parametri ottici dell'atmosfera mediante dati da satelliti operativi (literal)

Note

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni

Unversidade de Evora, Portugal CNR-ISAC, Bologna CNR-IBIMET, Sesto Fiorentino (literal)

Titolo

Aerosol Characterization and Optical Thickness Retrievals Using GOME and METEOSAT Satellite Data (literal)

Abstract

Retrievals of atmospheric aerosol optical thickness are highly dependent on the choice of the class describing the aerosol properties leading to significant errors while using classes available in the literature. High spectral resolution measurements from GOME (Global Ozone Monitoring Experiment) between the ultraviolet and the near infrared can be used for an accurate characterization of the aerosol optical properties. The radiometer MVIRI (METEOSAT Visible and Infrared Imager) on board the geostationary satellite METEOSAT, while being equipped only with broadband VIS channel, ensures an adequate half-hourly monitoring of the atmospheric conditions over a large portion of the Earth. The present algorithm is based on a combination of data from both sensors for the retrieval of the aerosol optical thickness at the reference wavelength of 0.55 mm (AOT). A case of a desert dust outbreak from the African continent over the Atlantic Ocean is examined. AOT values obtained using a-priori fixed classes taken from literature are compared with those retrieved with this algorithm using the GOME-derived classes. Systematic differences of the order of a few tenths on average are found which remain significant also after considering the measurement errors. This represents a novelty introduced by the synergistic use of both sensors. (literal)

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