Application of neural algorithms for a real time estimation of ozone profiles from GOME measurements

The distribution of trace gases in the atmosphere, its thermal structure and its circulation mechanisms result from a complex interplay between radiative, physical and dynamical processes. Neural networks algorithms can be a useful tool with such complexities in retrieval operations. In this paper their potentialities have been exploited to design on-line procedures for the estimation of vertical profiles of ozone from spectral radiances measured by GOME. Investigations on the November 1999 mini hole condition have been considered as an example of application of the algorithm.