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ISSN 2070-7401 (Print), ISSN 2411-0280 (Online)
Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa
CURRENT PROBLEMS IN REMOTE SENSING OF THE EARTH FROM SPACE

  

Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2024, Vol. 21, No. 5, pp. 20-35

Method of quantitative rainfall estimation based on Himawari-8/9 measurements

A.I. Andreev 1, 2 , A.A. Filey 1, 2 , S.I. Malkovsky 1 , S.P. Korolev 1 
1 Computing Center FEB RAS, Khabarovsk, Russia
2 Far Eastern Center of SRC "Planeta", Khabarovsk, Russia
Accepted: 30.09.2024
DOI: 10.21046/2070-7401-2024-21-5-20-35
The paper presents an algorithm for precipitation estimation based on data from Himawari-8/9 satellite. The algorithm is based on two neural networks of visual transformer and convolutional architectures for preliminary precipitation mask calculation and rain rate estimation. The data from the Global Precipitation Measurements (GPM) international project were used as a reference value of precipitation. These data are based on measurements from various active and passive microwave and infrared satellite instruments. The algorithm takes into account spectral, textural and microphysical parameters of clouds. An accuracy assessment was carried out using GPM data and ground-based rain gauges. The results of a comparison between the algorithm and regional numerical weather prediction model ComsoRu-6 are also given. It is shown that the presented algorithm most accurately estimates the amount of accumulated precipitation sums but it has a tendency to overestimate this value. On the other hand, GPM and CosmoRu-6 often underestimate precipitation. The comparison with GPM product showed a root mean squared error of about 2.19 mm/h.
Keywords: precipitation, rain rate, neural network, Himawari
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