Abstract

The atmosphere’s surface layer (first 50–100 m above the ground) is extremely dynamic and is influenced by surface radiative properties, roughness, and atmospheric stability. Understanding the distribution of turbulence in the surface layer is critical to many applications, such as directed energy and free space optical communications. Several measurement campaigns in the past have relied on weather balloons or sonic detection and ranging (SODAR) to measure turbulence up to the atmospheric boundary layer. However, these campaigns had limited measurements near the surface. We have developed a time-lapse imaging technique to profile atmospheric turbulence from turbulence-induced differential motion or tilts between features on a distant target, sensed between pairs of cameras in a camera bank. This is a low-cost and portable approach to remotely sense turbulence from a single site without the deployment of sensors at the target location. It is thus an excellent approach to study the distribution of turbulence in low altitudes with sufficiently high resolution. In the present work, the potential of this technique was demonstrated. We tested the method over a path with constant turbulence. We explored the turbulence distribution with height in the first 20 m above the ground by imaging a 30 m water tower over a flat terrain on three clear days in summer. In addition, we analyzed time-lapse data from a second water tower over a sloped terrain. In most of the turbulence profiles extracted from these images, the drop in turbulence with altitude in the first 15 m or so above the ground showed a ${h^m}$ dependence, where the exponent $m$ varied from ${-}{0.3}$ to ${-}{1.0}$, quite contrary to the widely used value of ${-}{4/3}$.

© 2024 Optica Publishing Group

Measuring the turbulence profile in the lower atmospheric boundary layer

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Estimation of modified Zernike coefficients from turbulence-degraded multispectral imagery using deep learning

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J. Opt. Soc. Am. A 41(6) B32-B39 (2024)

Estimation of behavior of optical turbulence during summer in the surface layer above the Antarctic Plateau using the Polar WRF model

Qike Yang, Xiaoqing Wu, Yajuan Han, and Chun Qing
Appl. Opt. 60(14) 4084-4094 (2021)