High Precision Aerosol Inversion Using Rotational Raman Scatter And Spaceborne CALIOP Data

Source of atmospheric aerosol is extensive, which also has a complex chemical composition. What is more, the physical and chemical properties of atmospheric aerosol have great scope changes. It is an important influence factor for aerosol radiative effect that the optical properties of aerosol. Meanwhile, the environment, climate and the health of human are influenced by aerosol particles significantly. In the methods of detecting aerosol,lidar has higher spatial and temporal resolution and detecting accuracy for the perfect monochromaticity, directivity and high power of laser. So it has an important meaning for scientific research and application that detecting atmospheric aerosol by a lidar.In this paper, we are devoted to study the improvement of inversion algorithm for atmospheric aerosol using a Raman-Mie lidar system. Based on simulating for the system and analysising the error tracing, we have considered the influence of atmospheric temperature on atmospheric aerosol for the first time and corrected the atmospheric aerosol inversion by using rotational Raman scatter. A new algorithm of Raman-Mie has been presented. Compared with the Raman-Mie method without considering effect of atmospheric temperature, the new algorithm improves the precision of Mie scattering inversing atmospheric aerosol scattering coefficient by 1.1×10-4 km-1sr-1 and 15.8% for relative inversion accuracy. Meanwhile, combining the airborne lidar, we have corrected the inversion of atmospheric aerosol detected by a ground-based Mie lidar. Compared with the new ground-based Raman-Mie method, the corrected method improves the precision of Mie scattering inversing atmospheric aerosol scattering coefficient by 1.6×10-3 km-1sr-1 and8.6% for relative inversion accuracy. And a new method of calibrating the overlap factor by the airborne and ground-based lidar is presented. At last, based on the new algorithm and corrected method; we have analysised and dicussed the seasonal properties of aerosol of Beijing in 2012 and 2013. The results show that the mean value of cirrus’ lidar ratio by month is 23.85±3.05 sr in summer and autumn of 2012 in Beijing. The effect of atmospheric temperature on cloud aerosol inversion is higher than non-cloud aerosol by16.5%. The inversion results of summer and winter of 2013 in Beijing show that the effect of atmospheric temperature on aerosol inversion, summer is higher than winter by about20%.The main research contents of this paper are shown as follows:(1) For the existing Raman-Mie lidar system in our laboratory, we have simulated andcalculated the signal-to-noise ratio of the system for choosing the proper technical parameters. The calibration of instrument numerical constant and overlap factor is completed in this paper. Based on the simulated and calculated results, we have analysised the error tracing for detecting aerosol and put forward the corresponding solutions.(2) We have analysised the source of noise signals in the Raman-Mie lidar system and classified the noise signals in this paper. It is used to denoise and filter the noise signals for the receiving datas of system that the method combining wavelet transforms and smoothing in 5points. As a result, the informations of mutation datas have been retained effectively.(3) Based on the effect of the atmospheric temperature on the atmospheric aerosol inversion, a new algorithm of Raman-Mie has been presented. We have corrected the atmospheric aerosol inversion by using rotational Raman scatter. And the real calculated value of atmospheric molecular scattering coefficient is used to substitute the atmospheric extinction model parameters, which is verified with the real data. On the basis of that, the software for inversing atmospheric aerosol detected by the Raman-Mie lidar is developed.(4) Combining the Level1 B data of the spaceborne CALIOP lidar, we have corrected the method of atmospheric aerosol inversion using the ground-based Raman-Mie lidar.Compared with the new ground-based Raman-Mie method, the inversion precision of atmospheric aerosol by using the ground-based lidar is improved furtherly, which is verified with the real data. At the same time, a new method of calibrating the overlap factor combining ground-based Mie lidar and spaceborne lidar is presented.(5) We have verified the corrected method above by using the aerosol detecting data of Beijing area in 2012 and 2013. It is shown that the empirical formula of PM2.5-AOD(Aerosol Optical Depth) in summer and winter in Beijing area. Furtherly, it is studied that the seasonal distribution characteristics of aerosol in Beijing area from three aspects which are the optical depth of aerosol, the extinction to scattering ratio of cirrus clouds and the impact of atmospheric temperature on aerosol.