Atmos. Chem. Phys., 9, 5321-5330, 2009
www.atmos-chem-phys.net/9/5321/2009/
doi:10.5194/acp-9-5321-2009
© Author(s) 2009. This work is distributed
under the Creative Commons Attribution 3.0 License.
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
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

Abstract. 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.

Citation: Amato, U., Antoniadis, A., De Feis, I., Masiello, G., Matricardi, M., and Serio, C.: Technical Note: Functional sliced inverse regression to infer temperature, water vapour and ozone from IASI data, Atmos. Chem. Phys., 9, 5321-5330, doi:10.5194/acp-9-5321-2009, 2009.
 
Search ACP
Final Revised Paper
PDF XML
Citation
Discussion Paper
Share