Technical Note: Functional sliced inverse regression to infer temperature, water vapour and ozone from IASI data

Amato, U.; Antoniadis, A.; De Feis, I.; Masiello, G.; Matricardi, M.; Serio, C.

doi:https://doi.org/10.5194/acp-9-5321-2009

Articles | Volume 9, issue 14

Atmos. Chem. Phys., 9, 5321–5330, 2009

https://doi.org/10.5194/acp-9-5321-2009

© Author(s) 2009. This work is distributed under
the Creative Commons Attribution 3.0 License.

Special issue: The IASI instrument onboard the METOP satellite: first...

Atmos. Chem. Phys., 9, 5321–5330, 2009

https://doi.org/10.5194/acp-9-5321-2009

© Author(s) 2009. This work is distributed under
the Creative Commons Attribution 3.0 License.

Articles | Volume 9, issue 14

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.

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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

Received: 07 Jan 2009 – Discussion started: 23 Mar 2009 – Published: 29 Jul 2009

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.