2026-10-15T05:58:25Z https://www.scidb.cn/oai

10.57760/sciencedb.28716 2025-09-25T15:44:01Z

2025-09-25 Trends and Significance of Composite Extreme Events in the Huangshui River Basin, 1960–2022: A Dataset doi:10.57760/sciencedb.28716 en As the volatility and extremity of global climate change continue to intensify, the frequency, intensity, and disaster risks associated with compound extreme events are escalating, posing severe challenges to regional ecological environments and socio-economic development. To precisely investigate the patterns of change in compound extreme events and their potential impacts, this study focuses on the Huangshui River Basin in the northeastern Qinghai-Tibet Plateau. Utilising daily mean temperature and precipitation observations from eight meteorological stations within the basin spanning January 1960 to December 2022, the cumulative distribution function method was employed to systematically identify and analyse the spatiotemporal trends and intensity characteristics of four composite extreme event types: warm-wet, warm-dry, cold-wet, and cold-dry.The core content of this dataset comprises tif-format data on the trend and significance of composite extreme events in the Huangshui River Basin. With its extensive temporal coverage and strong spatial representativeness, this dataset directly supports in-depth research on composite extreme events in this region. Given the Huangshui River Basin's location at the northeastern edge of the Qinghai-Tibet Plateau, where it serves both as an ecological barrier and exhibits vulnerability, deepening the analysis of composite extreme events in this region not only provides a robust theoretical foundation and data support for establishing future meteorological disaster early warning and response systems. It also holds significant practical guidance for local management authorities in scientifically formulating meteorological disaster response strategies, optimising emergency management processes, and enhancing disaster risk prevention and control capabilities. 湟水流域; 显著性; 复合极端事件 Niu Zhihui Liu Fenggui Zhang Ziqian Shi Yanan PUBLIC https://creativecommons.org/licenses/by/4.0/ dataset Science Data Bank