Mr. Ren Chao Profile

Ren Chao

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Proceedings Article | 24 July 2018 Paper

Wind field monitoring performance analysis of all-fiber coherent wind Lidar in coastal regions

Fan Qi, Ren Chao, Fengli Tian, Dingfu Zhou, Jiafeng Zheng, Keyun Zhu, Shu Qian, Jie Zhang

Proceedings Volume 10827, 108273L (2018) https://doi.org/10.1117/12.2501169

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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

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