Acta Optica Sinica, Volume. 43, Issue 18, 1899901(2023)

Spaceborne High Spectral Resolution Lidar for Atmospheric Aerosols and Clouds Profiles Measurement

Jianbo Hu1,2, Xiong Wang1,3, Shaohua Zhao4, Zhongting Wang4, Juxin Yang1,2,5, Guangyao Dai6, Yuan Xie1, Xiaopeng Zhu1,2,5, Dong Liu7, Xia Hou1,2,5,8, Jiqiao Liu1,2,5,8、*, and Weibiao Chen2,5,8、**
Author Affiliations
  • 1Space Laser Engineering Department, Shanghai Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Shanghai 201800, China
  • 2Center of Materials Science and Optoelectronics Engineering, University of Chinese Academy of Sciences, Beijing 100049, China
  • 3School of Optical and Electronic Information, Huazhong University of Science and Technology, Wuhan 430074, Hubei, China
  • 4Satellite Application Center for Ecology and Environment, Ministry of Ecology and Environment, Beijing 100094, China
  • 5Key Laboratory of Space Laser Communication and Detection Technology, Shanghai Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Shanghai 201800, China
  • 6College of Marine Technology, Faculty of Information Science and Engineering, Ocean University of China, Qingdao 266100, Shandong, China
  • 7College of Optical Science and Engineering, Zhejiang University, Hangzhou 310027, Zhejiang, China
  • 8Laoshan Laboratory, Qingdao 266237, Shandong, China
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    Objective

    On April 16, 2022, the aerosol and carbon dioxide detection lidar (ACDL) was successfully launched with the atmospheric environment monitoring (DQ-1) satellite. The high spectral resolution lidar (HSRL) system of ACDL, which is responsible for measuring atmospheric aerosol and cloud profiles, has successfully worked in orbit for more than one year and provided accurate global aerosol and cloud profiles. Aerosols have a significant impact on the global radiation balance and climate change. The biggest unknown when it comes to predicting climate is the radiative effect between aerosols and clouds. Therefore, in order to determine the distribution and the change of aerosols in the atmosphere, it is important to make high-precision observations of aerosols in the atmosphere with high temporal and spatial resolution. As an active remote sensing instrument, lidar is widely used in atmospheric aerosol profiles with high temporal and spatial resolution and continuous observation during the day and night. High spectral resolution lidar has the advantage of separating atmospheric aerosols Mie scattering signal and molecular Rayleigh scattering signal, compared with traditional elastic scattering lidar. Therefore, HSRL can directly obtain the backscattering coefficient, extinction coefficient, depolarization ratio, and lidar ratio of aerosols, without assuming the lidar ratio. It significantly improves the accuracy of aerosol optical parameters which would be used widely in environment monitoring and climate study.

    Methods

    The spaceborne HSRL system of ACDL based on an iodine molecular filter is implemented in orbit to measure aerosol and cloud profiles with high accuracy. Combined with the temperature and pressure data of the atmospheric reanalysis dataset (ERA5) of the European Centre for Medium-Range Weather Forecasts (ECMWF), the optical parameters such as backscattering coefficient, extinction coefficient, depolarization ratio, and lidar ratio of aerosols are obtained through data inversion. Aerosols are classified by reference values of optical parameters of different aerosol types. In this paper, cases of measurement data over Sahara Desert and Canadian wildfires region are selected to analyze the dust aerosols and smoke aerosols, respectively.

    Results and Discussions

    The optical properties of dust aerosols and smoke aerosols are analyzed by selecting the observation data of spaceborne high spectral resolution lidar over the Sahara Desert and the Canadian wildfires. These optical parameters include the backscattering coefficient, extinction coefficient, depolarization ratio, and lidar ratio of aerosols. The trajectory of ACDL and the attenuated backscatter coefficients at 532 nm of the parallel channel, perpendicular channel, and molecular channel over the Sahara Desert (Figs. 3-4) and the Canadian wildfires (Figs.7-8) are presented. The results show that the aerosols within 5 km near the ground in the selected Sahara Desert area are mainly dust aerosols (Fig. 6), and the depolarization ratio is concentrated in 0.2-0.4; the lidar ratio is concentrated in 40-60 sr (Fig. 5). The selected Canadian wildfire region is dominated by smoke aerosols (Fig. 10), whose depolarization ratio is concentrated in the range of 0.02-0.15, and lidar ratio is in the range of 50-70 sr (Fig. 9). The unique high spectral resolution detection technique of lidar has important applications in the fine detection and classification of aerosols and clouds and will play an important role in environmental monitoring.

    Conclusions

    In this paper, the high spectral resolution system based on the iodine molecular filter of Chinese spaceborne lidar ACDL and the inversion method of aerosol optical parameters are presented. Dust aerosols over the Sahara Desert and smoke aerosols generated by Canadian wildfires are selected as typical aerosol events for analysis. Accurate aerosol optical parameters are obtained by ACDL, and aerosols are classified according to those parameters. The spatial and temporal distribution characteristics and formation causes of aerosols in these areas are analyzed. The research in this paper shows the advantages of spaceborne high spectral resolution lidar in large-scale continuous and accurate observation of global aerosol distribution and provides a powerful means for accurate measurement and scientific application of global aerosol.

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    Jianbo Hu, Xiong Wang, Shaohua Zhao, Zhongting Wang, Juxin Yang, Guangyao Dai, Yuan Xie, Xiaopeng Zhu, Dong Liu, Xia Hou, Jiqiao Liu, Weibiao Chen. Spaceborne High Spectral Resolution Lidar for Atmospheric Aerosols and Clouds Profiles Measurement[J]. Acta Optica Sinica, 2023, 43(18): 1899901

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    Paper Information

    Category:

    Received: Aug. 17, 2023

    Accepted: Aug. 22, 2023

    Published Online: Sep. 14, 2023

    The Author Email: Liu Jiqiao (wbchen@siom.ac.cn), Chen Weibiao (liujiqiao@siom.ac.cn)

    DOI:10.3788/AOS231437

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