In this paper we introduce new variables that can be used to retrieve the atmospheric continuum emission in the inversion of remote sensing measurements. This modification tackles the so-called sloppy model problem. We test this approach on an extensive set of real measurements from the Michelson Interferometer for Passive Atmospheric Sounding. The newly introduced variables permit to achieve a more stable inversion and a smaller value of the minimum of the cost function.

The Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) is a mid-infrared emission spectrometer which is part of the core payload of the Envisat satellite, launched by ESA in March 2002. It provides unique observations of the atmospheric spectral radiances in the 4.15 -14.6 ?m spectral interval with innovative limb scanning capabilities for the three dimensional observation of the atmospheric composition and processes. The species, the processes and events that have been studied with this instrument in its 10 years of operation are briefly reviewed.

MIPAS measurements on ENVISAT represents a unique database for the study of atmospheric composition and of the time variation of atmospheric constituents and trends, in combination with other data. With the end of the ENVISAT mission, the importance of this decadal set of measurements justifies any efforts for their full exploitation. The maintenance and the upgrade of the ESA processor are made in the frame of the Quality Working Group, where a fruitful collaboration between L1, L2 and validation teams can be exploited.

The MIPAS instrument on the ENVISAT satellite has provided vertical profiles of the atmospheric composition on a global scale for almost ten years.

The MIPAS (Michelson Interferometer for Passive Atmospheric Sounding) instrument on the Envisat (Environmental satellite) satellite has provided vertical profiles of the atmospheric composition on a global scale for almost ten years. The MIPAS mission is divided in two phases: the full resolution phase, from 2002 to 2004, and the optimized resolution phase, from 2005 to 2012, which is characterized by a finer vertical and horizontal sampling attained through a reduction of the spectral resolution.

A common problem, arising in many different applied contexts, consists in estimating the number of exponentially damped sinusoids whose weighted sum best fits a finite set of noisy data and in estimating their parameters. Many different methods exist to this purpose. The best of them are based on approximate Maximum Likelihood estimators, assuming to know the number of damped sinusoids, which can then be estimated by an order selection procedure.