Data correction of temperature and water vapor measurements using the combined lateral scanning Raman scattering lidar and backward Raman scattering lidar

A combined lateral scanning Raman scattering lidar (LSRSL) and backward Raman scattering lidar (BWRSL) is built in Xi'an, which can achieve accurate measurements of atmospheric temperature and water vapor from the ground to the concerned height. In this paper, we report a method to correct the atmospheric transmittance in the return path, which is due to the wavelength difference between the high- and low-quantum-number transitions of PRRSS for temperature measurements and between the VRSS of N<sub>2</sub> and H<sub>2</sub>O for water vapor measurements. The correction function of atmospheric transmittance is optimized by considering the effect of aerosols from nearby industry and local urban traffic on atmospheric transmittance. With the advantages of the LSRSL system in the atmospheric detection without overlap effect, the atmospheric transmittance in the slant path of the LSRSL system is calculated from the real-time measured aerosol extinction from the lateral vibrational Raman scattering signal of N<sub>2</sub>, while the atmospheric transmittance in the return path of the BWRSL system is calculated from the glued aerosol extinction from both LSRSL system and BWRSL system. The retrieval results after data correction show that the combined lidar system can realize the detection of atmospheric temperature and water vapor from the ground to the height of 4.30 km under complex weather conditions, with a temperature deviation of less than 1.05 K and the water vapor deviation less than 0.61 g/kg compared with radiosonde data.

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Publication Details

Journal
Optics Express
Published
2025-06-06
DOI
https://doi.org/10.1364/oe.565001
Primary Topic
Atmospheric aerosols and clouds
Type
article
Field-Weighted Citation Impact
0.00

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article

Data correction of temperature and water vapor measurements using the combined lateral scanning Raman scattering lidar and backward Raman scattering lidar

Yan Qing, Fei Gao, Fan Yang, Liangliang Qi et al.
Optics Express
Atmospheric aerosols and clouds
article

Data correction of temperature and water vapor measurements using the combined lateral scanning Raman scattering lidar and backward Raman scattering lidar

Yan Qing, Fei Gao, Fan Yang, Liangliang Qi, Meng Wang, Shun Li, Yuehui Song, Dengxin Hua, Samo Stanič
article en

Abstract

A combined lateral scanning Raman scattering lidar (LSRSL) and backward Raman scattering lidar (BWRSL) is built in Xi'an, which can achieve accurate measurements of atmospheric temperature and water vapor from the ground to the concerned height. In this paper, we report a method to correct the atmospheric transmittance in the return path, which is due to the wavelength difference between the high- and low-quantum-number transitions of PRRSS for temperature measurements and between the VRSS of N<sub>2</sub> and H<sub>2</sub>O for water vapor measurements. The correction function of atmospheric transmittance is optimized by considering the effect of aerosols from nearby industry and local urban traffic on atmospheric transmittance. With the advantages of the LSRSL system in the atmospheric detection without overlap effect, the atmospheric transmittance in the slant path of the LSRSL system is calculated from the real-time measured aerosol extinction from the lateral vibrational Raman scattering signal of N<sub>2</sub>, while the atmospheric transmittance in the return path of the BWRSL system is calculated from the glued aerosol extinction from both LSRSL system and BWRSL system. The retrieval results after data correction show that the combined lidar system can realize the detection of atmospheric temperature and water vapor from the ground to the height of 4.30 km under complex weather conditions, with a temperature deviation of less than 1.05 K and the water vapor deviation less than 0.61 g/kg compared with radiosonde data.

Optics ExpressVol. 33(13)
University of Nova Gorica (SI), North Minzu University (CN), Institute of State Administration (RU)
National Natural Science Foundation of China
Openalex Percentile: Top 87%
Atmospheric aerosols and clouds
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