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Geostationary Imaging FTS (GIFTS) Data Processing: Measurement Simulation and CompressionGIFTS (Geostationary Imaging Fourier Transform Spectrometer), a forerunner of next generation geostationary satellite weather observing systems, will be built to fly on the NASA EO-3 geostationary orbit mission in 2004 to demonstrate the use of large area detector arrays and readouts. Timely high spatial resolution images and quantitative soundings of clouds, water vapor, temperature, and pollutants of the atmosphere for weather prediction and air quality monitoring will be achieved. GIFTS is novel in terms of providing many scientific returns that traditionally can only be achieved by separate advanced imaging and sounding systems. GIFTS' ability to obtain half-hourly high vertical density wind over the full earth disk is revolutionary. However, these new technologies bring forth many challenges for data transmission, archiving, and geophysical data processing. In this paper, we will focus on the aspect of data volume and downlink issues by conducting a GIFTS data compression experiment. We will discuss the scenario of using principal component analysis as a foundation for atmospheric data retrieval and compression of uncalibrated and un-normalized interferograms. The effects of compression on the degradation of the signal and noise reduction in interferogram and spectral domains will be highlighted. A simulation system developed to model the GIFTS instrument measurements is described in detail.
Document ID
20010100556
Acquisition Source
Langley Research Center
Document Type
Conference Paper
Authors
Huang, Hung-Lung
(Wisconsin Univ. Madison, WI United States)
Revercomb, H. E.
(Wisconsin Univ. Madison, WI United States)
Thom, J.
(Wisconsin Univ. Madison, WI United States)
Antonelli, P. B.
(Wisconsin Univ. Madison, WI United States)
Osborne, B.
(Wisconsin Univ. Madison, WI United States)
Tobin, D.
(Wisconsin Univ. Madison, WI United States)
Knuteson, R.
(Wisconsin Univ. Madison, WI United States)
Garcia, R.
(Wisconsin Univ. Madison, WI United States)
Dutcher, S.
(Wisconsin Univ. Madison, WI United States)
Li, J.
(Wisconsin Univ. Madison, WI United States)
Date Acquired
August 20, 2013
Publication Date
January 4, 2001
Publication Information
Publication: Hyperspectral Remote Sensing of the Land and Atmosphere
Volume: 4151
Subject Category
Earth Resources And Remote Sensing
Distribution Limits
Public
Copyright
Other

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