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21 June 2024 Analysis of extreme rainstorm process using multi-source remote sensing data: a case study of Shenyang
Dian Li, Jinglin Cui, Shuai Zhang, Yang Lu, Wanting Hou
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Proceedings Volume 13167, International Conference on Remote Sensing, Mapping, and Image Processing (RSMIP 2024); 1316706 (2024) https://doi.org/10.1117/12.3029627
Event: International Conference on Remote Sensing, Mapping and Image Processing (RSMIP 2024), 2024, Xiamen, China
Abstract
Using the data from GNSS-PWV, FY-2G Satellite detection products, wind profile radar and conventional observation data, an extreme rainstorm process on 7th August 2018 in Shenyang was analyzed. The results show that PWV values decreased first and then increased 2-3 hours before the start of heavy rainfall. There is a consistent correspondence between the decrease in TBB Value and the enhancement of rainfall intensity, but the center of high precipitation is slightly westward compared to the center of low TBB Value. There are two peaks for vertical speed and signal to noise ratio (SNR) during the main period of rainstorm. The first peak time is corresponding to the peak time of the storm relative helicity (SRH) and refractive index structure constant, it shows that the storm system is under favorable environmental conditions. Peak rain intensity appears within 1~2 h after the first peak time. The second peak time is corresponding to the time of cold air intrusion. The refractive index structure constant and storm relative helicity can forecast strong precipitation.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
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Dian Li, Jinglin Cui, Shuai Zhang, Yang Lu, and Wanting Hou "Analysis of extreme rainstorm process using multi-source remote sensing data: a case study of Shenyang", Proc. SPIE 13167, International Conference on Remote Sensing, Mapping, and Image Processing (RSMIP 2024), 1316706 (21 June 2024); https://doi.org/10.1117/12.3029627
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KEYWORDS
Rain
Signal to noise ratio
Refractive index
Radar sensor technology
Remote sensing
Satellites
Signal detection
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