Estimation of optical turbulence in the atmospheric surface layer from routine meteorological observations:
an artificial neural network approach

Yao Wang; Sukanta Basu

doi:10.1117/12.2063168

7 October 2014 Estimation of optical turbulence in the atmospheric surface layer from routine meteorological observations: an artificial neural network approach

Yao Wang, Sukanta Basu

Author Affiliations +

Proceedings Volume 9224, Laser Communication and Propagation through the Atmosphere and Oceans III; 92240X (2014) https://doi.org/10.1117/12.2063168
Event: SPIE Optical Engineering + Applications, 2014, San Diego, California, United States

Abstract

The focus of this paper is on the estimation of optical turbulence (commonly characterized by C²_n ) 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 C²_n dataset from a recent field experiment in Texas, USA to evaluate the accuracy of the proposed approach.

Citation Download Citation

Yao Wang and Sukanta Basu "Estimation of optical turbulence in the atmospheric surface layer from routine meteorological observations: an artificial neural network approach", Proc. SPIE 9224, Laser Communication and Propagation through the Atmosphere and Oceans III, 92240X (7 October 2014); https://doi.org/10.1117/12.2063168

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