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Proceedings Paper

Combination of one-directional and multiangle data processing techniques to reduce uncertainty in the elastic lidar measurement data
Author(s): Vladimir A. Kovalev; Cyle Wold; Jenny Newton; Wei Min Hao
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Paper Abstract

The lidar equation uncertainty, caused by the presence of two unknown functions (extinction and backscatter coefficients), is the main source of measurement errors in the elastic lidar searching of the atmosphere. The multiangle data-processing technique that applies the layer-integrated form of the angle-dependent lidar equation, allows one to avoid the a priori selection of the extinction-to-backscatter ratio. However, the practical use of the technique is impeded by atmospheric horizontal heterogeneity and distortions in real lidar data, which worsen the inversion accuracy of the retrieved extinction-coefficient profiles; in addition, the multiangle solution is extremely sensitive even to minor systematic distortions in the inverted data. A combination of the one-directional and multiangle data-processing technique improves the measurement accuracy of the retrieved data. Here no guesses are required about the vertical profile of the extinction-to-backscatter ratio. The technique was developed and tested with experimental data using a two-wavelength scanning lidar at the Fire Sciences Laboratory in Missoula, MT, USA. The specifics, advantages, and restrictions of this combined technique are discussed and illustrated by both synthetic and experimental data.

Paper Details

Date Published: 4 November 2004
PDF: 9 pages
Proc. SPIE 5575, Laser Radar Techniques for Atmospheric Sensing, (4 November 2004); doi: 10.1117/12.588424
Show Author Affiliations
Vladimir A. Kovalev, U.S. Dept. of Agriculture (United States)
Cyle Wold, U.S. Dept. of Agriculture (United States)
Jenny Newton, U.S. Dept. of Agriculture (United States)
Wei Min Hao, U.S. Dept. of Agriculture (United States)

Published in SPIE Proceedings Vol. 5575:
Laser Radar Techniques for Atmospheric Sensing
Upendra N. Singh, Editor(s)

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