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中国黄淮海-长江流域极端降水的时空变化。

Spatial-temporal variation of extreme precipitation in the Yellow-Huai-Hai-Yangtze Basin of China.

机构信息

State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing, 210098, China.

State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing, 100038, China.

出版信息

Sci Rep. 2023 Jun 8;13(1):9312. doi: 10.1038/s41598-023-36470-0.

Abstract

Climate warming leads to frequent extreme precipitation events, which is a prominent manifestation of the variation of the global water cycle. In this study, data from 1842 meteorological stations in the Huang-Huai-Hai-Yangtze River Basin and 7 climate models of CMIP6 were used to obtain the historical and future precipitation data using the Anusplin interpolation, BMA method, and a non-stationary deviation correction technique. The temporal and spatial variations of extreme precipitation in the four basins were analysed from 1960 to 2100. The correlation between extreme precipitation indices and their relationship with geographical factors was also analysed. The result of the study indicates that: (1) in the historical period, CDD and R99pTOT showed an upward trend, with growth rates of 14.14% and 4.78%, respectively. PRCPTOT showed a downward trend, with a decreasing rate of 9.72%. Other indices showed minimal change. (2) Based on SSP1-2.6, the intensity, frequency, and duration of extreme precipitation changed by approximately 5% at SSP3-7.0 and 10% at SSP5-8.5. The sensitivity to climate change was found to be highest in spring and autumn. The drought risk decreased, while the flood risk increased in spring. The drought risk increased in autumn and winter, and the flood risk increased in the alpine climate area of the plateau in summer. (3) Extreme precipitation index is significantly correlated with PRCPTOT in the future period. Different atmospheric circulation factors significantly affected different extreme precipitation indices of FMB. (4) CDD, CWD, R95pD, R99pD, and PRCPTOT are affected by latitude. On the other hand, RX1day and RX5day are affected by longitude. The extreme precipitation index is significantly correlated with geographical factors, and areas above 3000 m above sea level are more sensitive to climate change.

摘要

气候变暖导致极端降水事件频繁发生,这是全球水循环变化的突出表现。本研究利用 Anusplin 插值、BMA 方法和非平稳偏差修正技术,利用来自 CMIP6 的 7 个气候模型,从 1960 年到 2100 年获取了黄河-淮河流域和长江流域 1842 个气象站的历史和未来降水数据,分析了四个流域极端降水的时空变化,并分析了极端降水指数与地理因素的相关性。研究结果表明:(1)在历史时期,CDD 和 R99pTOT 呈上升趋势,增长率分别为 14.14%和 4.78%。PRCPTOT 呈下降趋势,下降率为 9.72%。其他指数变化不大。(2)基于 SSP1-2.6,在 SSP3-7.0 和 SSP5-8.5 下,极端降水的强度、频率和持续时间分别变化了约 5%和 10%。在春、秋两季对气候变化的敏感性最高。春季干旱风险降低,洪水风险增加。秋季和冬季干旱风险增加,高原高山气候区夏季洪水风险增加。(3)在未来时期,极端降水指数与 PRCPTOT 显著相关。不同的大气环流因素显著影响了 FMB 的不同极端降水指数。(4)CDD、CWD、R95pD、R99pD 和 PRCPTOT 受纬度影响。另一方面,RX1day 和 RX5day 受经度影响。极端降水指数与地理因素显著相关,海拔 3000 米以上地区对气候变化更为敏感。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9216/10250351/c8cc078b9e91/41598_2023_36470_Fig1_HTML.jpg

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