Spatial and temporal characterization of extreme precipitation in the Liaohe River Basin, China

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.

Authors

Institutions

Publication Details

Published
2024-11-27
DOI
https://doi.org/10.1117/12.3048786
Primary Topic
Cryospheric studies and observations
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Spatial and temporal characterization of extreme precipitation in the Liaohe River Basin, China

Jiale Xu, Xuan Wang, Yunzhi Fang
Cryospheric studies and observations
article

Spatial and temporal characterization of extreme precipitation in the Liaohe River Basin, China

Jiale Xu, Xuan Wang, Yunzhi Fang
article en

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.

University of Jinan (CN)
Openalex Percentile: Top 75%
Cryospheric studies and observations
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Spatial and temporal characterization of extreme precipitation in the Liaohe River Basin, China — Jiale Xu, Xuan Wang, et al. · (2024) | TGRS Research Map | TGRS