29 Jul 2009
29 Jul 2009
Technical Note: Functional sliced inverse regression to infer temperature, water vapour and ozone from IASI data
U. Amato1, A. Antoniadis2, I. De Feis1, G. Masiello3, M. Matricardi4, and C. Serio3
U. Amato et al.
U. Amato1, A. Antoniadis2, I. De Feis1, G. Masiello3, M. Matricardi4, and C. Serio3
- 1Istituto per le Applicazioni del Calcolo "Mauro Picone" CNR, Napoli, Italy
- 2Laboratoire Jean Kuntzmann, Université Joseph Fourier, Grenoble, France
- 3Dipartimento di Ingegneria e Fisica dell'Ambiente, Università della Basilicata, Potenza, Italy
- 4European Centre for Medium-Range Weather Forecasts (ECMWF), Reading, UK
- 1Istituto per le Applicazioni del Calcolo "Mauro Picone" CNR, Napoli, Italy
- 2Laboratoire Jean Kuntzmann, Université Joseph Fourier, Grenoble, France
- 3Dipartimento di Ingegneria e Fisica dell'Ambiente, Università della Basilicata, Potenza, Italy
- 4European Centre for Medium-Range Weather Forecasts (ECMWF), Reading, UK
Hide author details
Received: 07 Jan 2009 – Discussion started: 23 Mar 2009 – Published: 29 Jul 2009
A retrieval algorithm that uses a statistical strategy based on dimension reduction is proposed. The methodology and details of the implementation of the new algorithm are presented and discussed. The algorithm has been applied to high resolution spectra measured by the Infrared Atmospheric Sounding Interferometer instrument to retrieve atmospheric profiles of temperature, water vapour and ozone. The performance of the inversion strategy has been assessed by comparing the retrieved profiles to the ones obtained by co-locating in space and time profiles from the European Centre for Medium-Range Weather Forecasts analysis.