基于转动拉曼散射和星载CALIOP数据的气溶胶高精度反演方法

发布时间：2018-04-11 22:37

本文选题：气溶胶 + 大气温度　；参考：《北京理工大学》2015年博士论文

【摘要】：大气气溶胶来源广泛,化学组分复杂,其理化特性也有很大的变化范围,气溶胶的光学特性是气溶胶辐射效应的重要因素,而且气溶胶粒子对环境、气候以及人体健康都有重要的影响。在众多的气溶胶的探测方法中,激光雷达以其光源的良好单色性、定向性和高功率,使得激光雷达在探测大气气溶胶方面有着较高的时空分辨率和探测精度,对大气气溶胶的反演研究具有重要的科学意义和应用价值。本文基于拉曼-米激光雷达系统,主要致力于大气气溶胶反演方法的改进,在对系统的仿真计算和误差溯源分析的基础上,首次考虑大气温度的影响,使用转动拉曼散射对米散射反演大气气溶胶进行了优化,提出Raman-Mie新算法,与不考虑大气温度影响的Raman-Mie方法相比,米散射反演大气气溶胶后向散射系数的精度优化了1.1×10-4km-1sr-1,相对反演精度优化了15.8%;同时结合星载CALIOP激光雷达数据对地基米散射激光雷达反演大气气溶胶进行优化,与地基Raman-Mie新算法相比,气溶胶后向散射系数反演精度优化了1.6×10-3 km-1sr-1,相对反演精度优化了8.6%,并提出一种星载-地基激光雷达数据标定地基激光雷达几何因子的新方法;最后使用系统测量的北京2012年和2013年气溶胶数据对以上优化方法进行验证,对北京气溶胶季节性分布特征分析的结果表明北京2012年秋夏两季卷云消光后向散射比月均值为23.85±3.05sr,大气温度对云层气溶胶反演的影响要高于非云层气溶胶16.5%,北京2013年冬夏季反演数据表明大气温度对气溶胶反演的影响,夏季要高出冬季20%左右。论文主要研究内容如下:(1)针对实验室已有的拉曼-米激光雷达系统对系统信噪比进行仿真计算,给出技术参数选取的依据;完成了对系统仪器常数及几何因子的标定;根据仿真计算结果对系统探测误差进行溯源分析并给出相应的解决方案;(2)分析拉曼-米激光雷达系统信号噪声的来源,对其进行分类;提出了5点滑动平滑与小波变换结合的方法对系统探测原始数据进行滤波和去噪,可有效保留突变数据的信息;(3)针对大气温度对气溶胶反演的影响,提出了Raman-Mie新算法,使用转动拉曼散射对米散射反演大气气溶胶进行优化,利用大气分子后向散射系数实际计算值替代标准大气消光模式参数,采用实际数据进行验证,在此基础上完成了拉曼-米激光雷达大气气溶胶反演软件;(4)结合星载CALIOP激光雷达Level1B数据对地基米散射激光雷达反演气溶胶进行优化,相对于地基Raman-Mie新算法,进一步提高了地基激光雷达气溶胶的反演精度,采用实际数据进行验证,同时提出一种结合星载-地基激光雷达数据反演地基激光雷达几何因子的新方法;(5)使用2012年和2013年北京气溶胶观测数据对以上优化方法进行了验证,并计算了北京地区冬夏季PM2.5-AOD(Aerosol Optical Depth)经验公式;从北京地区气溶胶的光学厚度、卷云的消光后向散射比以及大气温度对气溶胶的影响三个层面对北京地区气溶胶季节性分布特征进行了研究。
[Abstract]:The source of atmospheric aerosol, chemical component is complex, its physicochemical properties have great range, the optical properties of the aerosols is an important factor in aerosol radiative effect, and aerosol particles on the environment, has important influence on the climate and human health. The detection method of numerous aerosol, lidar with good monochromaticity the light source, directional and high power, the laser radar has a high temporal resolution and the detection accuracy in the detection of atmospheric aerosol, inversion of atmospheric aerosol has important scientific significance and application value. In this paper, the Raman Mie lidar system based on improved focuses on atmospheric aerosol inversion method, based on Simulation Analysis on the system calculation and error tracing, first consider the effect of atmospheric temperature, the use of rotational Raman scattering on the inversion of atmospheric aerosol scattering meter The glue is optimized, put forward a new algorithm of Raman-Mie, compared with the Raman-Mie method does not consider the influence of atmospheric temperature, Mie scattering inversion of aerosol backscatter coefficient precision optimization 1.1 * 10-4km-1sr-1, the relative inversion precision optimized 15.8%; combined with the foundation of lidar inversion of atmospheric aerosol optimized laser radar satellite data CALIOP, the new algorithm is compared with the Raman-Mie foundation, aerosol backscattering coefficient inversion accuracy optimization 1.6 * 10-3 km-1sr-1, the relative inversion precision 8.6% optimization, and put forward a kind of spaceborne lidar data foundation - a new method for calibration of lidar geometrical factor foundation; verification of the above optimization method finally use the measurement system of Beijing in 2012 and in 2013, according to the analysis of aerosol data, the seasonal distribution characteristics of aerosol in Beijing Beijing as a result of the fall of 2012 summer two season after the extinction of cirrus The monthly mean scattering ratio was 23.85 + 3.05sr. The effect of atmospheric temperature on cloud aerosol is higher than that of the cloud aerosol 16.5%, Beijing 2013 summer and winter inversion data showed that the effect of atmospheric temperature on the aerosol, summer is up to about 20%. In winter the main research contents are as follows: (1) according to the Raman - M laser radar system on the SNR of the simulation, the selection of technical parameters are given according to the calibration of the system; complete the instrument constant and geometric factor; according to the simulation results of the system detection error source analysis and gives the corresponding solutions; (2) analysis of the sources of Raman Mie lidar system signal noise, the classification method is proposed; 5 point smoothing and wavelet transform to the detection system of original data filtering and denoising, can effectively retain the mutation data channel Interest; (3) the effect of atmospheric temperature on the aerosol retrieval, put forward a new algorithm of Raman-Mie, the use of rotating on the Mie scattering of atmospheric aerosol inversion optimization using Raman scattering, atmospheric molecular backscattering coefficient of actual calculation instead of standard atmospheric extinction model parameters is verified by the actual data, based on the Raman Mie Lidar atmospheric aerosol retrieval software; (4) combined with the star on the foundation of Mie scattering lidar aerosol loading optimization CALIOP laser radar Level1B data, compared with the new algorithm foundation Raman-Mie, to further improve the accuracy of laser radar ground inversion of the aerosol, verified by the actual data, and proposes a combination of satellite ground laser radar data inversion of Ground Lidar geometrical factor method; (5) the above optimization using 2012 and 2013 Beijing Aerosol Observation Data The verification method, the Beijing area in summer and winter was calculated by PM2.5-AOD (Aerosol Optical Depth) empirical formula; from the aerosol optical depth in Beijing area, the lidar ratio of clouds and aerosol effects of atmospheric temperature on the three level of Beijing aerosol seasonal distribution characteristics were studied.

【学位授予单位】：北京理工大学
【学位级别】：博士
【学位授予年份】：2015
【分类号】：TN958.98

【参考文献】