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| Titel |
Information operator approach applied to the retrieval of the vertical distribution of atmospheric constituents from ground-based high-resolution FTIR measurements |
| VerfasserIn |
C. Senten, M. Mazière, G. Vanhaelewyn, C. Vigouroux |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1867-1381
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| Digitales Dokument |
URL |
| Erschienen |
In: Atmospheric Measurement Techniques ; 5, no. 1 ; Nr. 5, no. 1 (2012-01-16), S.161-180 |
| Datensatznummer |
250002314
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| Publikation (Nr.) |
 copernicus.org/amt-5-161-2012.pdf |
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| Zusammenfassung |
| The analysis of high spectral resolution Fourier Transform infrared (FTIR)
solar absorption spectra is an important issue in remote sensing. If this is
done carefully, one can obtain information, not only about the total column
abundances, but also about the vertical distribution of various constituents
in the atmosphere. This work introduces the application of the information
operator approach for extracting vertical profile information from
ground-based FTIR measurements. The algorithm is implemented and tested
within the well-known retrieval code SFIT2, adapting the optimal estimation
method such as to take into account only the significant contributions to
the solution. In particular, we demonstrate the feasibility of the method in
an application to ground-based FTIR spectra taken in the framework of the
Network for the Detection of Atmospheric Composition Change (NDACC) at Ile
de La Réunion (21° S, 55° E). A thorough comparison is made
between the original optimal estimation method, Tikhonov regularization and
this alternative retrieval algorithm, regarding information content,
retrieval robustness and corresponding full error budget evaluation for the
target species ozone (O3), nitrous oxide (N2O), methane
(CH4), and carbon monoxide (CO). It is shown that the information
operator approach performs well and in most cases yields both a better
accuracy and stability than the optimal estimation method. Additionally, the
information operator approach has the advantage of being less sensitive to
the choice of a priori information than the optimal estimation method and
Tikhonov regularization. On the other hand, in general the Tikhonov
regularization results seem to be slightly better than the optimal
estimation method and information operator approach results when it comes to
error budgets and column stability. |
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