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Titel |
Semi-autonomous sounding selection for OCO-2 |
VerfasserIn |
L. Mandrake, C. Frankenberg, C. W. O'Dell, G. Osterman, P. Wennberg, D. Wunch |
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 ; 6, no. 10 ; Nr. 6, no. 10 (2013-10-25), S.2851-2864 |
Datensatznummer |
250085093
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Publikation (Nr.) |
copernicus.org/amt-6-2851-2013.pdf |
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Zusammenfassung |
Many modern instruments generate more data than may be fully processed in a
timely manner. For some atmospheric sounders, much of the raw data cannot be
processed into meaningful observations due to suboptimal viewing conditions,
such as the presence of clouds. Conventional solutions are quick,
empirical-threshold filters hand-created by domain experts to weed out
unlikely or unreasonable observations, coupled with randomized down sampling
when the data volume is still too high. In this paper, we describe a method
for the construction of a subsampling and ordering solution that maximizes
the likelihood that a requested data subset will be usefully processed. The
method can be used for any metadata-rich source and implicitly discerns
informative vs. non-informative data features while still permitting user
feedback into the final features selected for filter implementation. We
demonstrate the method by creating a selector for the spectra of the
Japanese GOSAT satellite designed to measure column averaged mixing ratios
of greenhouse gases including carbon dioxide (CO2). This is done within
the Atmospheric CO2 Measurements from Space (ACOS) NASA project with
the intention of eventual use during the early Orbiting Carbon Observatory-2
(OCO-2) mission. OCO-2 will have a 1.5 orders of magnitude larger data
volume than ACOS, requiring intelligent pre-filtration. |
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