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.
In this paper, we present an analytical scheme for the computation of Hessian for skin temperature, temperature profile and water vapor profile. It is possible to retrieve atmospheric parameters from IR radiance achieving the quadratic convergence for a pure Newton algorithm.
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