Statistical downscaling of extremes of precipitation and temperature and construction of their future scenarios in an elevated and cold zone

被引:0
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作者
Xiaoyan Wang
Tao Yang
Quanxi Shao
Kumud Acharya
Weiguang Wang
Zhongbo Yu
机构
[1] Hohai University,State Key Laboratory of Hydrology
[2] CSIRO Mathematics,Water Resources and Hydraulics Engineering
[3] Informatics and Statistics,Division of Hydrologic Sciences
[4] Desert Research Institute,undefined
关键词
Climate change; Coupled general circulation model (CGCM); Statistical downscaling; Statistical downscaling model (SDSM); Projection; Scenarios;
D O I
暂无
中图分类号
学科分类号
摘要
Reliable projections of extremes at finer spatial scales are important in assessing the potential impacts of climate change on societal and natural systems, particularly for elevated and cold regions in the Tibetan Plateau. This paper presents future projections of extremes of daily precipitation and temperature, under different future scenarios in the headwater catchment of Yellow River basin over the 21st century, using the statistical downscaling model (SDSM). The results indicate that: (1) although the mean temperature was simulated perfectly, followed by monthly pan evaporation, the skill scores in simulating extreme indices of precipitation are inadequate; (2) The inter-annual variabilities for most extreme indices were underestimated, although the model could reproduce the extreme temperatures well. In fact, the simulation of extreme indices for precipitation and evaporation were not satisfactory in many cases. (3) In future period from 2011 to 2100, increases in the temperature and evaporation indices are projected under a range of climate scenarios, although decreasing mean and maximum precipitation are found in summer during 2020s. The findings of this work will contribute toward a better understanding of future climate changes for this unique region.
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页码:405 / 418
页数:13
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