Neural Network Algorithms for Ozone Profile Retrieval from ESA-Envisat SCIAMACHY and NASA-Aura OMI Satellite Data

In this paper we report on the design of Neural Networks algorithms to retrieve height resolved ozone information from Envisat SCIAMACHY and Aura OMI Level 1 data. We defined as input-output pairs the matching of (a) SCIAMACHY UV/VIS reflectances with ozonesondes concentrations, and(b) OMI UV/VIS reflectances with MLS concentrations. Design issues, as input vector dimensionality reduction, vertical resolution problems and topology selection are here analyzed. The inversion results are presented and discussed, with a special emphasis to retrievals at tropospheric height levels.