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Proceedings Paper

Retrieval of atmospheric parameters with neural network inversion of infrared high-resolution sensor spectra
Author(s): Antonio Luchetta; Peter Schluessel; Carmine Serio; Mariassunta Viggiano
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Paper Abstract

It is presented a neural network methodology to retrieve atmospheric parameters of meteorological interest such as temperature, water vapor and ozone profiles from upwelling high resolution infrared sensor spectra. Neural network approach has been developed on basis of the specification of the Infrared Atmospheric Sounding Interferometer (IASI), which is planned to be flown on the first European Meteorological Operational Satellite Metop in 2005. The performance of the neural network based inversion methodology has been evaluated by considering a suitable set of inversion exercises in which test cases are retrieved.

Paper Details

Date Published: 18 April 2003
PDF: 9 pages
Proc. SPIE 4882, Remote Sensing of Clouds and the Atmosphere VII, (18 April 2003); doi: 10.1117/12.463073
Show Author Affiliations
Antonio Luchetta, Univ. di Firenze (Italy)
Peter Schluessel, EUMETSAT (Germany)
Carmine Serio, Instituto di Metodologie per l'Analisi Ambientale-CNR (Italy)
Mariassunta Viggiano, Instituto di Metodologie per l'Analisi Ambientale-CNR (Italy)

Published in SPIE Proceedings Vol. 4882:
Remote Sensing of Clouds and the Atmosphere VII
Klaus P. Schaefer; Olga Lado-Bordowsky; Adolfo Comeron; Richard H. Picard, Editor(s)

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