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.
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