基于粒子偏振特性的雾霾区分算法研究

摘要/Abstract

摘要： 雾、霾粒子的组成成分不同,雾滴具有大粒子特性,霾的成分复杂,小粒子居多。偏振观测对小粒子具有很强的敏感性,基于该特性利用矢量辐射传输模型(Vector linearized discrete ordinate radiative transfer, VLIDORT) 计算雾粒子和霾粒子的偏振辐射特性,模拟结果经公式计算可得到雾、霾粒子的偏振反射率。模拟结果表明: 在散射角125$^\circ\sim150^\circ$范围内,雾粒子和霾粒子的偏振反射率随散射角分布有明显不同的变化趋势。利用该偏振辐射特性结合雾霾粒子的辐射特性,基于2008年3月11日的多角度偏振成像观测的卫星载荷 (Polarization and directionality of the earth's reflectances, POLDER)数据对雾和霾进行区分。将区分结果与中分辨率成像光谱仪(Moderate-resolution imaging spectroradiometer, MODIS)图像及地面站观测资料进行对比,验证了算法的有效性。这对高分五号大气气溶胶多角度偏振探测仪(Directional polarimetric camera, DPC) 遥感数据的应用具有重要的参考价值和科学意义。

关键词: 大气光学, 雾霾粒子, 矢量辐射传输, 区分算法

Abstract: The compositions of fog and haze particles are different. The droplets have the characteristics of large particles, while the composition of haze is complex, and small particles are mostly present. Polarization observation has very great sensitivity to small particles. Based on this characteristic, the polarized radiation characteristics of fog and haze particles are calculated using the vector linearized discrete ordinate radiative transfer(VLIDORT) model. The simulation results can be used to obtain the polarization reflectance of fog and haze particles. In the range of scattering angles of 125$^\circ$ to 150$^\circ$, the polarization reflectance of fog and haze particles varies significantly with the scattering angle distribution. By taking advantage of the radiation characteristics of fog and haze particles, fog and haze have been distinguished based on the polarization and directionality of the earth's reflectances(POLDER)data on March 11, 2008. The distinguished results were compared with moderate-resolution imaging spectroradiometer (MODIS) images and ground station observation data to verify the effectiveness of the algorithm. It is believed that the alogorithm has great reference value and scientific significance for China's GF-5 of directional polarimetric camera(DPC) remote sensing data.

Key words: atmospheric optics, haze particles, vector radiation transmission, distinguishing algorithm

中图分类号:

TP79

吴时超1,2,麻金继1,2,章群英1,2,余海啸1,2,安源1,2. 基于粒子偏振特性的雾霾区分算法研究[J]. 大气与环境光学学报.

WU Shichao1,2, MA Jinji1,2, ZHANG Qunying1,2, YU Haixiao1,2, AN Yuan1,2. Research on Haze and Fog Distinguishing Algorithm Based on\\[0.2cm] Particle Polarization Characteristics[J]. Journal of Atmospheric and Environmental Optics.

参考文献

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