Laser & Optoelectronics Progress, Volume. 59, Issue 10, 1028001(2022)

Simulation of Cloud and Aerosol Detection Based on Spaceborne Lidar

Shujun Liao1,2, Haiyang Gao1,2、*, Leilei Kou1,2, Jiahui Kang2, Lingbing Bu1,2, and Zhen Wang1,2
Author Affiliations
  • 1Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing University of Information Science & Technology, Nanjing 210044, Jiangsu , China
  • 2School of Atmospheric Physics, Nanjing University of Information Science & Technology, Nanjing 210044, Jiangsu , China
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    In the design, development, and data inversion of spaceborne lidar, the forward model is critical. This study establishes a forward model for observing clouds and aerosols using spaceborne lidar. It can simulate ice clouds and aerosols, as well as other complex scenes. The model as a whole is made up of 8 sub-modules. The simulation results in the 532-nm channel show that in the deep convection scenarios, the clouds are deep and the signal attenuation is serious, thus, only the distribution of the cloud top can be distinguished. The influence of cloud microphysical characteristics on the effective detection of aerosols must be considered in the ice cloud and aerosol scenes. In terms of parameter sensitivity analysis, the relationship between telescope diameter, satellite orbit altitude, laser single pulse energy, and the signal-to-noise ratio can help with instrument design. The comparison of the attenuation backscattering coefficient calculated by the forward model with the actual detection results of CALIOP/CALIPSO shows a good consistency in the structure of spatial distribution. However, owing to the uncertainty in the CALIPSO inversion algorithm and the difference in parameter settings between the inversion and the forward model, some minor differences at different altitudes when comparing the average of all profiles remain.

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    Shujun Liao, Haiyang Gao, Leilei Kou, Jiahui Kang, Lingbing Bu, Zhen Wang. Simulation of Cloud and Aerosol Detection Based on Spaceborne Lidar[J]. Laser & Optoelectronics Progress, 2022, 59(10): 1028001

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    Paper Information

    Category: Remote Sensing and Sensors

    Received: Sep. 7, 2021

    Accepted: Nov. 16, 2021

    Published Online: May. 11, 2022

    The Author Email: Gao Haiyang (gaohy@nuist.edu.cn)

    DOI:10.3788/LOP202259.1028001

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