Temporal and spatial variations in the sub-daily precipitation structure over the Qinghai–Tibet Plateau (QTP)

环境科学 气候变化 降水 大洪水 空间分布 气候学 高原(数学) 自然地理学 地理 生态学 地质学 气象学 生物 遥感 数学分析 考古 数学
作者
Hao Lu,Jun Qiu,Meng‐Jia Li,Hui-Min Zuo,J. Li,Bill X. Hu,Fangfang Li
出处
期刊:Science of The Total Environment [Elsevier BV]
卷期号:915: 170153-170153
标识
DOI:10.1016/j.scitotenv.2024.170153
摘要

Precipitation is a vital component of the global atmospheric and hydrological cycles and influencing the distribution of water resources. Even subtle changes in precipitation can significantly impact ecosystems, energy cycles, agricultural production, and food security. Therefore, understanding the changes in the precipitation structure under climate change is essential. The Qinghai–Tibet Plateau (QTP) is a region sensitive to global climate change and profoundly impacts the atmospheric water cycle in Asia and even globally, rendering it a hot topic in climate change research in recent years. Few studies have examined on the sub-daily scale precipitation structure over the QTP. In this paper, the characteristics of sub-daily precipitation on the QTP were systematically investigated from multiple perspectives, including the concentration index, skewness (the third standardized moment of a distribution), and kurtosis (the fourth standardized moment of a distribution). The results indicated that the frequency of moderate-intensity nighttime precipitation on the QTP generally increased, and the analysis of both the concentration index and kurtosis (skewness) suggested that extreme precipitation was more frequent in the southwestern foothills of the QTP. Furthermore, potential high-risk areas for natural disasters were identified on the QTP, and found that the southeastern part of the plateau constituted a potential hotspot area for flood disasters. Given the complexity of climate change, a comprehensive analysis of the spatiotemporal characteristics of diurnal and nighttime precipitation changes on the QTP could help reveal the regularity of precipitation changes. This has significant implications for forecasting, warning, disaster preparedness, and mitigation efforts on the QTP.

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