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Proceedings Paper

Estimation of optical turbulence in the atmospheric surface layer from routine meteorological observations: an artificial neural network approach
Author(s): Yao Wang; Sukanta Basu
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Paper Abstract

The focus of this paper is on the estimation of optical turbulence (commonly characterized by C2n ) near the land-surface using routinely measured meteorological variables (e.g., temperature, wind speed). We demonstrate that an artificial neural network-based approach has the potential to be effectively utilized for this purpose. We use an extensive scintillometer-based C2n dataset from a recent field experiment in Texas, USA to evaluate the accuracy of the proposed approach.

Paper Details

Date Published: 7 October 2014
PDF: 8 pages
Proc. SPIE 9224, Laser Communication and Propagation through the Atmosphere and Oceans III, 92240X (7 October 2014); doi: 10.1117/12.2063168
Show Author Affiliations
Yao Wang, North Carolina State Univ. (United States)
Sukanta Basu, North Carolina State Univ. (United States)

Published in SPIE Proceedings Vol. 9224:
Laser Communication and Propagation through the Atmosphere and Oceans III
Alexander M. J. van Eijk; Christopher C. Davis; Stephen M. Hammel, Editor(s)

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