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

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

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...

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Main Authors: I. De Feis, A. Antoniadis, U. Amato, C. Serio, M. Matricardi, G. Masiello
Format: Article
Language:English
Published: Copernicus Publications 2009-07-01
Series:Atmospheric Chemistry and Physics
Online Access:http://www.atmos-chem-phys.net/9/5321/2009/acp-9-5321-2009.pdf
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spelling doaj-83f19ab2868c4bb1a4dbeb209c2de0212020-11-25T01:54:58ZengCopernicus PublicationsAtmospheric Chemistry and Physics1680-73161680-73242009-07-0191453215330Technical Note: Functional sliced inverse regression to infer temperature, water vapour and ozone from IASI dataI. De FeisA. AntoniadisU. AmatoC. SerioM. MatricardiG. MasielloA 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. http://www.atmos-chem-phys.net/9/5321/2009/acp-9-5321-2009.pdf
collection DOAJ
language English
format Article
sources DOAJ
author I. De Feis
A. Antoniadis
U. Amato
C. Serio
M. Matricardi
G. Masiello
spellingShingle I. De Feis
A. Antoniadis
U. Amato
C. Serio
M. Matricardi
G. Masiello
Technical Note: Functional sliced inverse regression to infer temperature, water vapour and ozone from IASI data
Atmospheric Chemistry and Physics
author_facet I. De Feis
A. Antoniadis
U. Amato
C. Serio
M. Matricardi
G. Masiello
author_sort I. De Feis
title Technical Note: Functional sliced inverse regression to infer temperature, water vapour and ozone from IASI data
title_short Technical Note: Functional sliced inverse regression to infer temperature, water vapour and ozone from IASI data
title_full Technical Note: Functional sliced inverse regression to infer temperature, water vapour and ozone from IASI data
title_fullStr Technical Note: Functional sliced inverse regression to infer temperature, water vapour and ozone from IASI data
title_full_unstemmed Technical Note: Functional sliced inverse regression to infer temperature, water vapour and ozone from IASI data
title_sort technical note: functional sliced inverse regression to infer temperature, water vapour and ozone from iasi data
publisher Copernicus Publications
series Atmospheric Chemistry and Physics
issn 1680-7316
1680-7324
publishDate 2009-07-01
description 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.
url http://www.atmos-chem-phys.net/9/5321/2009/acp-9-5321-2009.pdf
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