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Analysis of Information Content in High-Spectral Resolution Sounders using Subset Selection AnalysisIn this paper, we summarize the results of the sensitivity analysis and data reduction carried out to determine the information content of AIRS and IASI channels. The analysis and data reduction was based on the use of subset selection techniques developed in the linear algebra and statistical community to study linear dependencies in high dimensional data sets. We applied the subset selection method to study dependency among channels by studying the dependency among their weighting functions. Also, we applied the technique to study the information provided by the different levels in which the atmosphere is discretized for retrievals and analysis. Results from the method correlate well with intuition in many respects and point out to possible modifications for band selection in sensor design and number and location of levels in the analysis process.
Document ID
20000032342
Acquisition Source
Headquarters
Document Type
Conference Paper
Authors
Velez-Reyes, Miguel
(Puerto Rico Univ. Mayaguez, Puerto Rico)
Joiner, Joanna
(NASA Goddard Space Flight Center Greenbelt, MD United States)
Date Acquired
August 19, 2013
Publication Date
February 22, 1998
Publication Information
Publication: NASA University Research Centers Technical Advances in Aeronautics, Space Sciences and Technology, Earth Systems Sciences, Global Hydrology, and Education
Volume: 2 and 3
Subject Category
Earth Resources And Remote Sensing
Funding Number(s)
CONTRACT_GRANT: NCCW-0088
Distribution Limits
Public
Copyright
Work of the US Gov. Public Use Permitted.
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