@article{Du2026, 
author = {Xiaoyong Du and Shudao Zhou and Yudi Liu and Zheng Sheng and Shijun Zhao and Qingwei Zeng and Yi Wang and Xijie Yang and Yunshu Hao},
title = {Current status and analysis of atmospheric turbulence kinetic energy dissipation rate retrieval by meteorological radar},
year = {2026},
journal = {Acta Aerodynamica Sinica},
volume = {44},
number = {9},
pages = {1-20},
keywords = {atmospheric turbulence, turbulent kinetic energy, dissipation rate, meteorological radar, velocity structure function, power spectral density, doppler spectral width},
url = {https://www.sciopen.com/article/10.7638/kqdlxxb-2025.0111},
doi = {10.7638/kqdlxxb-2025.0111},
abstract = {Atmospheric turbulence is the key process of regulating the exchange of atmospheric materials and energy. As one of the core parameters of atmospheric turbulence, the turbulent energy dissipation rate (ε) is critical, and its accurate retrieval is very important for the fields of weather forecast, remote sensing communication, aviation safety, wind energy development and so on. Through tracing the K41 theory, which is the theoretical basis of meteorological radar retrieval of ε, the development of the main retrieval technologies such as the structure function method, the power spectrum method, the spectral width method and the power method in the past few decades is reviewed in detail, including the application conditions, advantages and disadvantages, application scenarios and technical improvements of the methods. The application characteristics, detection cases and comparison verification of the retrieval of ε by wind profiler radar, weather radar, cloud radar and lidar are analyzed and summarized. In addition, the effects of anisotropy, scattering mechanism and spectral width broadening on retrieval accuracy are discussed. Finally, this study identifies that future technological development will focus on multi-band radar collaborative observation, multi-source data fusion driven by deep learning, improved retrieval models for non-uniform and non-isotropic turbulence, and integrated space-air-ground detection. This work aims to provide theoretical and technical references for the optimization and innovation of ε retrieval methods.}
}