Polarized Laser Backscattering of Atmospheric Cloud Distribution Based on Simulated Annealing Algorithm

Meteorological forecasting can not only reduce the losses caused by natural disasters to human society but also has a very important significance in the fields of water conservancy, aviation, and transportation. In order to improve the accuracy of meteorological forecasting, we should focus on the in-depth optical analysis of atmospheric cloud distribution. Compared with forward-scattered laser light, backscattered laser light can save more optical information. Therefore, this paper studies the backscattering of polarized laser light distributed in atmospheric clouds. In this study, a simulated annealing algorithm was used to invert the data of spaceborne lidar to obtain the depolarization degree and backscattering coefficient of atmospheric clouds and aerosols at different heights. Finally, based on the radar measurement example, the simulated annealing algorithm was used to analyze the atmospheric information of sunny, cloudy, and hazy weather in summer and winter, and the atmospheric depolarization and backscattering coefficients corresponding to different weather heights were obtained. The corresponding cloud layer type was judged. The research results prove the feasibility of the simulated annealing algorithm in the study of polarized laser backscattering in atmospheric cloud distribution. This study provides new ideas for radar data processing methods and provides a theoretical basis for further research in the field of meteorological forecasting.