基于国产高分5号卫星观测的气溶胶成分遥感反演研究

大气气溶胶在气候变化和空气质量等方面发挥着重要作用。当前大气气溶胶的辐射强迫仍是气候变化评估中不确定性最大的因子之一，其中关键的原因之一是大空间尺度上对气溶胶成分含量的观测和反演还存在很大不确定性。本项目拟采用多项最小二乘法对耦合了气溶胶光学-成分模型的大气辐射传输模型进行最优化求解，利用我国多波段、多角度、偏振卫星的观测数据，开展气溶胶成分和关键光学参数的反演研究。首先，基于气溶胶成分吸收和散射特性的光谱特征构建气溶胶光学-成分模型，并通过敏感性和不确定性分析、地面数据验证等手段分析气溶胶特性参数反演的误差来源，提高算法的反演精度。最后，定量评估气溶胶成分混合规则对卫星遥感反演气溶胶特性的影响，揭示气溶胶成分含量及关键光学参数的时空演变规律。项目成果将为减小气溶胶气候效应评估的不确定性提供基础数据，也为我国重污染天气过程的区域尺度监测和分析提供更丰富的研究手段和科学支撑。

Atmospheric aerosols play an important role in global climate change and air quality. Because of the large uncertainty in the observation and estimation of aerosol composition and optical characteristics on a large scale, aerosol radiative forcing remains the most uncertain factor in the climate change assessment. Based on the spectral differences among the absorption and scattering properties of aerosol compositions, this project proposes an aerosol optical-composition conversion module, which is incorporated into the atmospheric radiation transfer model to retrieve aerosol composition and optical parameters from the multi-spectral, multi-angle, and polarized satellite observation using the multi-term least squares method. The analysis of sensitivity and uncertainty, as well as the verification of retrievals are conducted to find the error sources of inversion and to improve the accuracy and reliability of the inversion algorithm. At last, the algorithm is employed to quantitatively evaluate the influence of aerosol composition mixing rules on the inversion of aerosol properties from satellite remote sensing and to reveal the spatial and temporal evolution of aerosol compositions and the key optical parameters. The algorithm can provide basic data for reducing the uncertainty of aerosol effects on the climate change assessments and it also provides more techniques for monitoring of aerosol compositions on regional scale during the occurrence of heavy pollution.