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Proceedings Paper

The use of hyperspectral data in numerical weather prediction
Author(s): J. Le Marshall; J. Jung; Li Bi
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Paper Abstract

The Atmospheric Infrared Sounder (AIRS) (Chahine et al., 2006) was launched in 2002 on AQUA, the second of the EOS polar-orbiting satellites. The AIRS was the first of a new generation of meteorological advanced sounders able to provide hyperspectral (sometimes referred to as ultraspectral) data for operational and research use. The improved spectral resolution it provided compared to earlier passive infrared sounders, led to a significant increase in vertical resolution and accuracy in determining thermal and moisture fields, increased accuracy in the determination of the concentrations of absorbers such as ozone and improved numerical weather prediction (NWP), (Le Marshall et al. 2006). It was also shown that expanded use of the information content of infrared hyperspectral radiance data resulted in an increase in the benefit of these data to NWP. Experiments which have shown the benefit of improved spatial coverage, spectral coverage and the use of moisture channel data, are summarised in this paper. In addition, an experiment which has recorded the benefit of using hyperspectral radiance data from fields of view containing clouds is also described. Again it is demonstrated that a more complete use of the information content in the observations available from hyperspectral sounders has resulted in improved benefits to numerical weather prediction. This conclusion is also supported by early experiments reporting the benefits from using IASI data. Overall, the results indicate the significant benefits to be derived from hyperspectral data assimilation and the benefits to be gained from an enhanced use of the information content contained in hyperspectral radiance observations.

Paper Details

Date Published: 11 December 2008
PDF: 9 pages
Proc. SPIE 7149, Multispectral, Hyperspectral, and Ultraspectral Remote Sensing Technology, Techniques, and Applications II, 714903 (11 December 2008); doi: 10.1117/12.809203
Show Author Affiliations
J. Le Marshall, Bureau of Meteorology (Australia)
Joint Ctr. for Satellite Data Assimilation (United States)
J. Jung, Joint Ctr. for Satellite Data Assimilation (United States)
Univ. of Wisconsin, Madison (United States)
Li Bi, Univ. of Wisconsin, Madison (United States)


Published in SPIE Proceedings Vol. 7149:
Multispectral, Hyperspectral, and Ultraspectral Remote Sensing Technology, Techniques, and Applications II
Allen M. Larar; Mervyn J. Lynch; Makoto Suzuki, Editor(s)

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