Future Increase in Extreme Precipitation: Historical Data Analysis and Influential Factors

Hengfei Zhang, Xinglong Mu, Fanxiang Meng (), Ennan Zheng, Fangli Dong, Tianxiao Li and Fuwang Xu
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Hengfei Zhang: School of Hydraulic and Electric Power, Heilongjiang University, Harbin 150080, China
Xinglong Mu: School of Hydraulic and Electric Power, Heilongjiang University, Harbin 150080, China
Fanxiang Meng: School of Hydraulic and Electric Power, Heilongjiang University, Harbin 150080, China
Ennan Zheng: School of Hydraulic and Electric Power, Heilongjiang University, Harbin 150080, China
Fangli Dong: School of Hydraulic and Electric Power, Heilongjiang University, Harbin 150080, China
Tianxiao Li: School of Water Conservancy and Civil Engineering, Northeast Agricultural University, Harbin 150030, China
Fuwang Xu: School of Hydraulic and Electric Power, Heilongjiang University, Harbin 150080, China

Sustainability, 2024, vol. 16, issue 22, 1-22

Abstract: With global warming driving an increase in extreme precipitation, the ensuing disasters present an unsustainable scenario for humanity. Consequently, understanding the characteristics of extreme precipitation has become paramount. Analyzing observational data from 1961 to 2020 across 29 meteorological stations in Heilongjiang Province, China, we employed kriging interpolation, the trend-free pre-whitening Mann–Kendall (TFPW–MK) method, and linear trend analysis. These methods allowed us to effectively assess the spatiotemporal features of extreme precipitation. Furthermore, Pearson’s correlation analysis explored the relationship between extreme precipitation indices (EPIs) and geographic factors, while the geodetector quantified the impacts of climate teleconnections. The results revealed the following: (1) There has been a clear trend in increasing extreme precipitation over the last few decades, particularly in the indices of wet day precipitation (PRCPTOT), very wet day precipitation (R95P), and extremely wet day precipitation (R99P), with regional mean trends of 10.4 mm/decade, 5.7 mm/decade, and 3.4 mm/decade, respectively. This spatial trend showed a decrease from south to north. (2) Significant upward trends were observed in both spring and winter for the maximum 1-day precipitation (RX1day) and the maximum 5-day precipitation (RX5day). (3) The latitude and longitude were significantly correlated with the most extreme precipitation indices, while elevation showed a weaker correlation. (4) Extreme precipitation exhibited a nonlinear response to large-scale climate teleconnections, with the combined influence of factors having a greater impact than individual factors. This research provides critical insights into the spatiotemporal dynamics of extreme precipitation, guiding the development of targeted strategies to mitigate risks and enhance resilience. It offers essential support for addressing regional climate challenges and promoting agricultural development in Heilongjiang Province.

Keywords: global warming; extreme precipitation; spatiotemporal dynamics; large-scale climate teleconnections; Heilongjiang Province (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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