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.
Retrieval of atmospheric parameters with neural network inversion of infrared high-resolution sensor spectra
Mariassunta Viggiano
2003
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.File in questo prodotto:
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