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Titel |
Detecting physically unrealistic outliers in ACE-FTS atmospheric measurements |
VerfasserIn |
P. E. Sheese, C. D. Boone, K. A. Walker |
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 ; 8, no. 2 ; Nr. 8, no. 2 (2015-02-12), S.741-750 |
Datensatznummer |
250116132
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Publikation (Nr.) |
copernicus.org/amt-8-741-2015.pdf |
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Zusammenfassung |
The ACE-FTS (Atmospheric Chemistry Experiment – Fourier Transform
Spectrometer) instrument on board the Canadian satellite SCISAT has been
observing the Earth's limb in solar occultation since its launch in 2003.
Since February 2004, high resolution (0.02 cm−1) observations in the
spectral region of 750–4400 cm−1 have been used to derive volume mixing
ratio profiles of over 30 atmospheric trace species and over 20 atmospheric
isotopologues. Although the full ACE-FTS level 2 data set is available to
users in the general atmospheric community, until now no quality flags have
been assigned to the data. This study describes the two-stage procedure for
detecting physically unrealistic outliers within the data set for each
retrieved species, which is a fixed procedure across all species. Since the
distributions of ACE-FTS data across regions (altitude/latitude/season/local
time) tend to be asymmetric and multimodal, the screening process does not
make use of the median absolute deviation. It makes use of volume mixing
ratio probability density functions, assuming that the data, when
sufficiently binned, are at most tri-modal and that these modes can be
represented by the superposition of three normal, or log-normal,
distributions. Quality flags have been assigned to the data based on
retrieval statistical fitting error, the physically unrealistic outliers
described in this study, and known instrumental/processing errors. The
quality flags defined and discussed in this study are now available for all
level 2 versions 2.5 and 3.5 data and will be made available as a standard
product for future versions. |
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