Mie-scattering lidar is an active remote sensing tool for inverting atmospheric properties by detecting the interaction between lasers and various molecules and aerosol particles in the atmosphere. It has become a powerful detection tool for atmospheric aerosols. However, whether it is a coaxial or parallel-axis laser radar, the accuracy of measurement and inversion in the blind zone and transition zone needs to be improved. This paper studies and establishes a new method of the Mie scattering lidar extinction profile correction based on the UAV-borne aerosol radiosonde. In this method, the UAV (unmanned aerial vehicle) is equipped with an optical aerosol radiosonde (Portable Optical Particle Profiler, POPS), and measures particle spectrum information and related meteorological parameters in the same detection path as lidar. Therefore, by using the Mie scattering theory simulation, the aerosol extinction profile in the lidar short-range blind zone and transition zone can be derived from the UAV-borne aerosol radiosonde data. The horizontal measurement verification test shows that the near-ground extinction coefficient by the new UAV method is in good agreement with that obtained by the lidar Collis slope method.
The altitude of atmospheric medium involved in atmospheric optics has a height range of 100km, and the most complicated variation of atmospheric properties is mainly in the atmospheric boundary layer (ABL). The variety of ABL height is of considerable significance to the distribution of aerosol, cloud, and other processes. Since the research of Chinese marine ABL analysis is limited, in this study, we improved the algorithm by using 532nm total attenuated backscattering (TAB) for retrieving atmospheric boundary layer height (ABLH) from Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) and verified the results gained from micro-pulse lidar (MPL) and radiosonde over the South China Sea. Finally, we used the validated ABLH algorithm model to retrieve the ABLH against CALIPSO data from Mar. 2018 to Feb.2019 over the South China Sea.
Lidar has been widely used in remote sensing of atmospheric environment because of its high spatial-temporal resolution and detection sensitivity. As the main noise source in lidar detection, solar background radiation is an important factor to determine target from background. The background noise, which is estimated by taking the average value of the lidar echo signal at a certain height, is usually removed directly. However, the background noise also contains some useful information on the whole layer of the atmosphere. In this paper, atmospheric radiation transmission model software MODTRAN 5.0 was used to simulate the lidar background noise under clear sky condition, combined with micro-pulse lidar (MPL) and meteorological element sounding data. The daytime background noise received by lidar were simulated by standard model method and user-defined model method. The standard model method uses standard atmospheric and aerosol model, which is the common way in traditional background radiation simulation. The user-defined model method uses aerosol and meteorological data measured in Maoming, Guangdong Province in October 2018 to build a user-defined atmospheric model. Results shows that the overall trends of the simulated background radiation from two methods are quite similar to the MPL observation. The user-defined model method can produce more consistent results with the observation than the standard model method, mainly due to that standard model cannot be completely consistent with the real experimental environment. The simulation results in this paper can be used to improve the daytime MPL retrieval, and can also be applied to the retrieving of aerosol particle size information and optical characteristics of cloud in further study.
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