Paper
27 November 2024 Spatial and temporal characterization of extreme precipitation in the Liaohe River Basin, China
Yunzhi Fang, Jiale Xu, Xuan Wang
Author Affiliations +
Proceedings Volume 13402, International Conference on Remote Sensing, Mapping, and Geographic Information Systems (RSMG 2024); 134023M (2024) https://doi.org/10.1117/12.3048786
Event: International Conference on Remote Sensing, Mapping, and Geographic Information Systems (RSMG 2024), 2024, Zhengzhou, China
Abstract
Extreme precipitation events are expected to happen more frequently due to global climate change, affecting societal development and human life. Therefore, six extreme precipitation indices were computed using the daily precipitation data of 139 meteorological grid points in the Liaohe River Basin (LRB) from 1961 to 2020. The spatial and temporal characteristics of the extreme precipitation indices in the basin were then examined using trend analysis and mutation testing., and their correlation with latitude, longitude, altitude, and atmospheric circulation indices were also analyzed. The results show that: The extreme precipitation indices, with the exception of RX1day, all showed an increasing trend; however, R95p, R99p, R20, R25, and CWD all showed decreasing trends; none of them displayed obvious mutation years; decreases within the basin dominated the changes in the extreme precipitation indices, with the northeastern part of the basin experiencing the greatest decreases; the majority of the extreme precipitation indices demonstrated a significant positive correlation with longitude and a significant negative correlation with latitude and elevation. The majority of the extreme precipitation indices have a considerable negative correlation with the Sunspot Number (SN) in the atmospheric circulation.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Yunzhi Fang, Jiale Xu, and Xuan Wang "Spatial and temporal characterization of extreme precipitation in the Liaohe River Basin, China", Proc. SPIE 13402, International Conference on Remote Sensing, Mapping, and Geographic Information Systems (RSMG 2024), 134023M (27 November 2024); https://doi.org/10.1117/12.3048786
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KEYWORDS
Analytical research

Data acquisition

Statistical analysis

Meteorology

Climatology

Climate change

Rain

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