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Influence of solar activity and large-scale climate phenomena on extreme precipitation events in the Yangtze River Economic Belt.

Authors :
Wu, Yi
Zhang, Lin
Zhang, Zhixin
Ling, Jingyun
Yang, Shiqi
Si, Jingjing
Zhan, Hongbin
Chen, Wenling
Source :
Stochastic Environmental Research & Risk Assessment. Jan2024, Vol. 38 Issue 1, p211-231. 21p.
Publication Year :
2024

Abstract

The Yangtze River Economic Belt (YREB) is an important strategic area in China. However, frequent extreme precipitation events have caused great economic losses and human casualties in this region. In this article, we explore the spatial and temporal links between extreme precipitation events and Sunspot Number (SSN), El Niño Southern Oscillation (ENSO), Arctic Oscillation (AO) and Pacific Decadal Oscillation (PDO) in this important economic belt. According to the research findings, all of the extreme precipitation indices (EPIs) except for consecutive dry days (CDD) and consecutive wet days (CWD) showed an upward trend in the YREB over the 59 years. The spatial distributions of very wet days (R95p), extremely wet days (R99p), max 1-day precipitation amount (Rx1day) and max 5-day precipitation amount (Rx5day) had similar distribution patterns, showing decreasing trends from east to west. The EPIs generally had a 2–4-year band, suggesting stronger and more elusive changes. The wavelet coherence (WTC) spectra suggested that SSN, ENSO, AO, and PDO have different effects on extreme precipitation events during different time periods. Before 1985, the SSN, ENSO, AO, PDO and extreme precipitation events shared similar oscillation periods, but after 1985, their oscillation periods were no longer consistent with each other. In addition, solar activity and the AO mainly had negative correlations with extreme precipitation events, while the ENSO and PDO had predominantly positive correlations with the EPIs. This paper provides a reference for national economic strategic planning and natural resource management in the YREB. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
14363240
Volume :
38
Issue :
1
Database :
Academic Search Index
Journal :
Stochastic Environmental Research & Risk Assessment
Publication Type :
Academic Journal
Accession number :
174819521
Full Text :
https://doi.org/10.1007/s00477-023-02573-3