Preprints
https://doi.org/10.5194/amt-2023-249
https://doi.org/10.5194/amt-2023-249
11 Dec 2023
 | 11 Dec 2023
Status: a revised version of this preprint was accepted for the journal AMT and is expected to appear here in due course.

Directly Measuring Atmospheric Turbulence Parameters Using Coherent Doppler Wind Lidar

Jinhong Xian, Chao Lu, Xiaolin Lin, Honglong Yang, Ning Zhang, and Li Zhang

Abstract. Atmospheric turbulence parameters, such as turbulent kinetic energy and dissipation rate, are of great significance in weather prediction, meteorological disasters, and forecasting. Due to the lack of ideal direct detection methods, traditional structure function methods are mainly based on Kolmogorov’s assumption of local isotropic turbulence and the well-known −5/3 power law within the inertial subrange, which limits their application. Here, we propose a method for directly measuring atmospheric turbulence parameters using coherent Doppler wind lidar, which can directly obtain atmospheric turbulence parameters and vertical structural features, breaking the limitations of traditional methods. The first published spatiotemporal distribution map of the power-law exponent of the inertial subrange is provided in this study, which indicates the heterogeneity of atmospheric turbulence at different altitudes, and also indicates that the power-law exponent at high altitudes does not fully comply with the −5/3 power law, proving the superiority of our method. We analyze the results under different weather conditions, indicating that the method still holds. The turbulent kinetic energy and power-law index obtained by this method are continuously compared with the results obtained with an ultrasonic anemometer for a month-long period. The results of the two have high consistency and correlation, verifying the accuracy and applicability of the proposed method. The proposed method has great significance in studying the vertical structural characteristics of atmospheric turbulence.

Jinhong Xian, Chao Lu, Xiaolin Lin, Honglong Yang, Ning Zhang, and Li Zhang

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on amt-2023-249', Anonymous Referee #1, 20 Dec 2023
    • AC1: 'Reply on RC1', Jinhong Xian, 19 Jan 2024
  • RC2: 'Comment on amt-2023-249', Anonymous Referee #2, 03 Jan 2024
    • AC2: 'Reply on RC2', Jinhong Xian, 19 Jan 2024

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on amt-2023-249', Anonymous Referee #1, 20 Dec 2023
    • AC1: 'Reply on RC1', Jinhong Xian, 19 Jan 2024
  • RC2: 'Comment on amt-2023-249', Anonymous Referee #2, 03 Jan 2024
    • AC2: 'Reply on RC2', Jinhong Xian, 19 Jan 2024
Jinhong Xian, Chao Lu, Xiaolin Lin, Honglong Yang, Ning Zhang, and Li Zhang
Jinhong Xian, Chao Lu, Xiaolin Lin, Honglong Yang, Ning Zhang, and Li Zhang

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Short summary
Improving the monitoring capability of atmospheric turbulence can help unravel the mystery of turbulence. Based on some assumptions, scientists have proposed various detection methods. However, these assumptions limit their applicability. We abandoned these assumptions and proposed a more accurate method, revealing some new results. Our method can provide more accurate three-dimensional features of turbulence, which will have a huge driving effect on the development of turbulence.