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Statistical models of aerosols and polar stratospheric clouds (PSC) for remote sensing

机译:遥感气溶胶和极地平流层云(PSC)的统计模型

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Algorithms to simulate the statistical microphysical and optical models for aerosol and polar stratospheric cloud (PSC) are described. Examples of such models for stratospheric and tropospheric aerosols and PSC are given. Different ways of applying the statistical aerosol and cloud models are discussed: 1. optimal parameterization of spectral dependences of aerosol extinction coefficient using the natural orthogonal basis; 2. multiple regression for estimating the optical parameter from measured one (for example, estimation of scattering coefficients from SAGE Ⅲ multiwavelength measurements of aerosol extinction coefficients); 3. retrieval of microphysical properties of stratospheric aerosol and PSC from SAGE Ⅲ extinction measurements; 4. lidar sounding.
机译:描述了模拟气溶胶和极地平流层云(PSC)统计微物理和光学模型的算法。给出了平流层和对流层气溶胶和PSC的这种模型的实例。讨论了应用统计气溶胶和云模型的不同方式:1。使用自然正交基础的气溶胶消光系数的光谱依赖性的最佳参数化; 2.用于估计来自测量的多元回归(例如,从气溶胶消光系数的SageⅢ多波长测量的散射系数估计); 3.从SageⅢ消光测量检索平流层气溶胶和PSC的微神科性质; 4.激光乐队。

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