Simulation analysis of the Non-Kolmogorov atmospheric turbulence detected by a Mie-scattering lidar based on fractal method

Menglong Bai 1 School of Electrical and Information Engineering, North Minzu University, North Wenchang Road, Yinchuan 750021, China
2 Key Laboratory of Atmospheric Environment Remote Sensing of Ningxia Province, North Wenchang Road, Yinchuan 750021, China

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Jiandong Mao 1 School of Electrical and Information Engineering, North Minzu University, North Wenchang Road, Yinchuan 750021, China
2 Key Laboratory of Atmospheric Environment Remote Sensing of Ningxia Province, North Wenchang Road, Yinchuan 750021, China

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Juan Li 1 School of Electrical and Information Engineering, North Minzu University, North Wenchang Road, Yinchuan 750021, China
2 Key Laboratory of Atmospheric Environment Remote Sensing of Ningxia Province, North Wenchang Road, Yinchuan 750021, China

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Hu Zhao 1 School of Electrical and Information Engineering, North Minzu University, North Wenchang Road, Yinchuan 750021, China
2 Key Laboratory of Atmospheric Environment Remote Sensing of Ningxia Province, North Wenchang Road, Yinchuan 750021, China

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Abstract

Atmospheric turbulence, characterized by irregular motions across various scales, poses significant challenges for accurate description using conventional methods due to its inherent complexity. This paper evaluates the reliability of detecting atmospheric turbulence using Mie-scattering lidar. We simulate non-Kolmogorov turbulence phase screens through both fractal and power spectrum methods, considering different internal and external scales. The impact of varying parameters on simulation accuracy is analyzed. By comparing the obtained phase structure function curves with theoretical curves and conducting error analysis for different methods, we verify the simulation speed and accuracy of the fractal method. A Mie-scattering lidar system is designed for detecting atmospheric turbulence, and the Gaussian laser beam is numerically simulated using the fractal method. Results indicate that the phase screen generated by this method possesses adequate high and low-frequency components, offering faster simulation speeds and higher precision. The simulated scintillation index aligns with theoretical trends. Moreover, by employing Mie-scattering lidar for the actual detection of non-Kolmogorov turbulence profiles, the feasibility of these simulations has been validated, providing new insights into the multi-scale structure and spatial distribution of atmospheric turbulence.

© 2025 American Meteorological Society. This is an Author Accepted Manuscript distributed under the terms of the default AMS reuse license. For information regarding reuse and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

* Correspondence: mao_jiandong@163.com, Fax: +86-0951-2066815

Abstract

Atmospheric turbulence, characterized by irregular motions across various scales, poses significant challenges for accurate description using conventional methods due to its inherent complexity. This paper evaluates the reliability of detecting atmospheric turbulence using Mie-scattering lidar. We simulate non-Kolmogorov turbulence phase screens through both fractal and power spectrum methods, considering different internal and external scales. The impact of varying parameters on simulation accuracy is analyzed. By comparing the obtained phase structure function curves with theoretical curves and conducting error analysis for different methods, we verify the simulation speed and accuracy of the fractal method. A Mie-scattering lidar system is designed for detecting atmospheric turbulence, and the Gaussian laser beam is numerically simulated using the fractal method. Results indicate that the phase screen generated by this method possesses adequate high and low-frequency components, offering faster simulation speeds and higher precision. The simulated scintillation index aligns with theoretical trends. Moreover, by employing Mie-scattering lidar for the actual detection of non-Kolmogorov turbulence profiles, the feasibility of these simulations has been validated, providing new insights into the multi-scale structure and spatial distribution of atmospheric turbulence.

© 2025 American Meteorological Society. This is an Author Accepted Manuscript distributed under the terms of the default AMS reuse license. For information regarding reuse and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

* Correspondence: mao_jiandong@163.com, Fax: +86-0951-2066815
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