Automated Classification of Non-Kolmogorov Turbulence Using a Higher-Order Surrogate Function

Kevin Lieb; Melissa Beason; Benjamin Wilson

doi:10.1364/PCAOP.2022.PTu4D.7

Imaging and Applied Optics Congress 2022 (3D, AOA, COSI, ISA, pcAOP)
Technical Digest Series (Optica Publishing Group, 2022),
paper PTu4D.7
•https://doi.org/10.1364/PCAOP.2022.PTu4D.7

Automated Classification of Non-Kolmogorov Turbulence Using a Higher-Order Surrogate Function

Kevin Lieb, Melissa Beason, and Benjamin Wilson

Propagation Through and Characterization of Atmospheric and Oceanic Phenomena 2022

Vancouver, British Columbia Canada
11–15 July 2022
ISBN: 978-1-957171-09-8

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K. Lieb, M. Beason, and B. Wilson, "Automated Classification of Non-Kolmogorov Turbulence Using a Higher-Order Surrogate Function," in Imaging and Applied Optics Congress 2022 (3D, AOA, COSI, ISA, pcAOP), Technical Digest Series (Optica Publishing Group, 2022), paper PTu4D.7.

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Abstract

A method of automated turbulence characterization has been developed for sonic anemometer data. We found that the structure function slope followed an exponential curve and used that observation to incorporate a surrogate function to simplify finding slopes and ranges of turbulence.

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