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Proceedings Paper

Alternative cloud clearing methodologies for the Atmospheric Infrared Sounder (AIRS)
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Paper Abstract

Traditional cloud clearing methods utilize a clear estimate of the atmosphere inferred from a microwave sounder to extrapolate cloud cleared radiances (CCR's) from a spatial interpolation of multiple cloudy infrared footprints. Unfortunately, sounders have low information content in the lower atmosphere due to broad weighting functions, interference from surface radiance and the microwave radiances can also suffer from uncorrected side-lobe contamination. Therefore, scenes with low altitude clouds can produce errant CCR's that, in-turn, produce errant sounding products. Radiances computed from the corrupted products can agree with the measurements within the error budget making detection and removal of the errant scenes impractical; typically, a large volume of high quality retrievals are rejected in order to remove a few errant scenes. In this paper we compare and contrast the yield and accuracy of the traditional approach with alternative methods of obtaining CCR's. The goal of this research is three-fold: (1) to have a viable approach if the microwave instruments fail on the EOS-AQUA platform; (2) to improve the accuracy and reliability of infrared products derived from CCR's; and (3) to investigate infrared approaches for geosynchronous platforms where microwave sounding is difficult. The methods discussed are (a) use of assimilation products, (b) use of a statistical regression trained on cloudy radiances, (c) an infrared multi-spectral approach exploiting the non-linearity of the Planck function, and (d) use of clear MODIS measurements in the AIRS sub-pixel space. These approaches can be used independently of the microwave measurements; however, they also enhance the traditional approach in the context of quality control, increased spatial resolution, and increased information content.

Paper Details

Date Published: 29 August 2005
PDF: 12 pages
Proc. SPIE 5890, Atmospheric and Environmental Remote Sensing Data Processing and Utilization: Numerical Atmospheric Prediction and Environmental Monitoring, 58900S (29 August 2005); doi: 10.1117/12.615238
Show Author Affiliations
C. D. Barnet, NOAA/NESDIS/ORA (United States)
M. Goldberg, NOAA/NESDIS/ORA (United States)
Thomas King, QSS Group Inc. (United States)
Nicholas Nalli, QSS Group Inc. (United States)
Walter Wolf, QSS Group Inc. (United States)
Lihang Zhou, QSS Group Inc. (United States)
Jennifer Wei, QSS Group Inc. (United States)

Published in SPIE Proceedings Vol. 5890:
Atmospheric and Environmental Remote Sensing Data Processing and Utilization: Numerical Atmospheric Prediction and Environmental Monitoring
Hung-Lung Allen Huang; Hal J. Bloom; Xiaofeng Xu; Gerald J. Dittberner, Editor(s)

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