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| Titel |
Cloud mask via cumulative discriminant analysis applied to satellite infrared observations: scientific basis and initial evaluation |
| VerfasserIn |
U. Amato, L. Lavanant, G. Liuzzi, G. Masiello, C. Serio, R. Stuhlmann, S. A. Tjemkes |
| 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 ; 7, no. 10 ; Nr. 7, no. 10 (2014-10-07), S.3355-3372 |
| Datensatznummer |
250115923
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| Publikation (Nr.) |
 copernicus.org/amt-7-3355-2014.pdf |
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| Zusammenfassung |
| We introduce a classification method (cumulative discriminant analysis) of
the discriminant analysis type to discriminate between cloudy and clear-sky
satellite observations in the thermal infrared. The tool is intended for the
high-spectral-resolution infrared sounder (IRS) planned for the geostationary
METEOSAT (Meteorological Satellite) Third Generation platform and uses IASI
(Infrared Atmospheric Sounding Interferometer) data as a proxy. The
cumulative discriminant analysis does not introduce biases intrinsic with the
approximation of the probability density functions and is flexible enough to
adapt to different strategies to optimize the cloud mask. The methodology is
based on nine statistics computed from IASI spectral radiances, which exploit
the high spectral resolution of the instrument and which effectively
summarize information contained within the IASI spectrum. A principal
component analysis prior step is also introduced, which makes the problem more
consistent with the statistical assumptions of the methodology. An initial
assessment of the scheme is performed based on global and regional IASI real
data sets and cloud masks obtained from AVHRR (Advanced Very High Resolution
Radiometer) and SEVIRI (Spinning Enhanced Visible and Infrared Imager)
imagers. The agreement with these independent cloud masks
is generally well above 80 %, except at high latitudes in the winter seasons. |
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