ISSN 2070-7401 (Print), ISSN 2411-0280 (Online)
Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa


Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2022, Vol. 19, No. 2, pp. 43-56

Using CALIOP data to estimate the cloud base height on MODIS images

A.V. Skorokhodov 1 , K.V. Kuryanovich 1 
1 V.E. Zuev Institute of Atmospheric Optics SB RAS, Tomsk, Russia
Accepted: 25.03.2022
DOI: 10.21046/2070-7401-2022-19-2-43-56
We present an analysis of the results of using active remote sensing of Earth from space in developing an algorithm for estimating the cloud base height by passive observations. The images and data products of CALIOP (CALIPSO) and MODIS (Aqua) were considered. The algorithm for estimating the cloud base height is based on the use of an adapted Kohonen self-organizing map. The data of both instruments are used at the stage of training the neural network, and when clustering images, and only MODIS images and data products of their processing are taken for image clustering. We propose an approach to reduce the Kohonen map by selectively removing neurons with similar values of some weight coefficients. The key features of clustering are determined, one of which is the cloud geometric thickness. We discuss the results of estimating the cloud base height of single-layer cloudiness by satellite images of the Western Siberia obtained in the summer from May to September. The limitations of the developed algorithm and promising trends for its improvement with the involvement of additional information are given. The results of estimating the cloud base height according to MODIS data are in good agreement with the CALIOP measurements over the region under study for optically thin low- and high-level clouds with <15.
Keywords: CALIOP, cloud base height, cluster analysis, image processing, neural network, satellite data, MODIS
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