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Wind field monitoring performance analysis of all-fiber coherent wind Lidar in coastal regions
Author(s): Fan Qi; Ren Chao; Fengli Tian; Dingfu Zhou; Jiafeng Zheng; Keyun Zhu; Shu Qian; Jie Zhang
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Paper Abstract

Water vapor content and aerosol concentration will affect detection capability of wind lidar. Types and concentrations of aerosols in coastal region are different from those in inland, and the air is more humid, which makes the wind field monitoring capability of lidar in coastal region deeply concerned. In this paper, the Chinese new all-fiber coherent lidar and radiosonde dataset was collected from the First wind field joint monitoring test in coastal region, and meteorological and aerosol dataset came from Local Meteorological Bureau. By comparing detection results of lidar and radiosonde, analyzing detection precision and maximum detection distance of lidar, and validating capture capability of lidar for typical wind field characteristics in coastal region, reliability and performances of this new wind lidar under clear-air, cloudy, foggy, hazy and precipitation conditions were analyzed in detail. The results show: In different weather conditions, lidar have high detection precision. Horizontal wind speed accuracy of lidar is not greater than 0.5 m/s, and horizontal wind direction accuracy of which is not greater than 5 degrees. Maximum detection distance of lidar are different, best in hazy conditions, and worst in precipitation because of attenuation; In different weather conditions, the dataset correlation coefficient between lidar and radiosonde can reach up to more than 0.95; High data resolution and strong sensitivity make lidar stably monitor typical wind field in coastal region, such as formation and disappearing of haze and foggy

Paper Details

Date Published: 24 July 2018
PDF: 8 pages
Proc. SPIE 10827, Sixth International Conference on Optical and Photonic Engineering (icOPEN 2018), 108273L (24 July 2018); doi: 10.1117/12.2501169
Show Author Affiliations
Fan Qi, Southwest Institute of Technical Physics (China)
Ren Chao, Beijing Aviation Meteorological Institute (China)
Fengli Tian, Chengdu Univ. of Information and Technology (China)
Dingfu Zhou, Southwest Institute of Technical Physics (China)
Jiafeng Zheng, Chengdu Univ. of Information and Technology (China)
Keyun Zhu, Chengdu Univ. of Information and Technology (China)
Shu Qian, Chengdu Univ. of Information and Technology (China)
Jie Zhang, Chengdu Univ. of Information and Technology (China)


Published in SPIE Proceedings Vol. 10827:
Sixth International Conference on Optical and Photonic Engineering (icOPEN 2018)
Yingjie Yu; Chao Zuo; Kemao Qian, Editor(s)

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