Abstract
To investigate the atmosphere of Earth and to detect changes in its environment, the Environmental Satellite will be launched by the European Space Agency in a polar orbit in October 2001. One of its payload instruments is a Fourier spectrometer, the Michelson Interferometer for Passive Atmospheric Sounding, designed to measure the spectral thermal emission of molecules in the atmosphere in a limb-viewing mode. The goal of this experiment is to derive operationally vertical profiles of pressure and temperature as well as of trace gases O3, H2O, CH4, N2O, NO2, and HNO3 from spectra on a global scale. A major topic in the analysis of the computational methodology for obtaining the profiles is how available a priori knowledge can be used and how this a priori knowledge affects corresponding results. Retrieval methods were compared and it was shown that an optimal estimation formalism can be used in a highly flexible way for this kind of data analysis. Beyond this, diagnostic tools, such as estimated standard deviation, vertical resolution, or degrees of freedom, have been used to characterize the results. Optimized regularization parameters have been determined, and a great effect from the choice of regularization and discretization on the results was demonstrated. In particular, we show that the optimal estimation formalism can be used to emulate purely smoothing constraints.