Modeling of horizontally inhomogeneous cloudiness using bounded cascade method

Tatiana Russkova; Ilya Tkachev

doi:10.1117/12.2643827

7 December 2022 Modeling of horizontally inhomogeneous cloudiness using bounded cascade method

Tatiana Russkova, Ilya Tkachev

Proceedings Volume 12341, 28th International Symposium on Atmospheric and Ocean Optics: Atmospheric Physics; 1234108 (2022) https://doi.org/10.1117/12.2643827
Event: 28th International Symposium on Atmospheric and Ocean Optics: Atmospheric Physics, 2022, Tomsk, Russia

Abstract

The current algorithm for retrieval of the optical and microphysical properties of clouds from satellite measurement data involves the use of independent pixel approximation and a model of plane-parallel horizontally and vertically homogeneous clouds for each pixel of satellite image, that in some situations can lead to large retrieval errors. The paper describes an alternative approach based on applying neural networks trained using the results of 3D simulation of solar radiation transfer in the Earth’s atmosphere in the presence of a field of broken horizontally inhomogeneous clouds. To generate a cloud field realization, the fractal multiplicative bounded cascade model is used. The examples of modeling the stratocumulus clouds by means of the bounded cascade model are considered. The model is successfully tested using the MODIS image of stratocumulus cloud scene.

Citation Download Citation

Tatiana Russkova and Ilya Tkachev "Modeling of horizontally inhomogeneous cloudiness using bounded cascade method", Proc. SPIE 12341, 28th International Symposium on Atmospheric and Ocean Optics: Atmospheric Physics, 1234108 (7 December 2022); https://doi.org/10.1117/12.2643827

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