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Abstract

Aerosols including soil dust, organic carbon, black carbon, sea salt, aerosol water, sulfate, and nitrate are essential atmospheric components. The interaction of these aerosols with radiation is critical to weather and climate studies. However, accurate representation of aerosol-radiation interactions in atmospheric models is a challenging research subject. In this talk, we will present a new aerosol-optics model, followed with comprehensive assessments in radiative transfer and atmospheric models. The new aerosol-optics model has incorporated the particle nonsphericity and inhomogeneity as well as the aerosol mixing variations, which have significant impact on light scattering and absorption. The single-scattering optical properties of aerosol particles were computed based on the Lorenz-Mie theory, the state-of-the-art invariant imbedding T-matrix method and the physical-geometric optics methods. In particular, a machine-learning approach was developed to parameterize the aerosol optical properties, which can be efficiently implemented in the radiative transfer and atmospheric models. Finally, in this talk, representative results will be given to illustrate the performance of this new aerosol model in remote sensing, weather and climate studies.