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	Change trend of monthly precipitation in China with an improved surface modeling method
	Wang C. L.; Zhao, N.; Yue, T. X.; Zhao, M. W.; Chen, C.
	2015
关键词	Box-Cox transformation Geographically weighted regression HASM Precipitation Time series China geographically weighted regression seasonal precipitation water-resources climate-change interpolation variables temperature generation patterns terrain
英文摘要	In this paper, a combination of a novel interpolation method and a local regression method was employed to improve the estimation accuracy of monthly precipitation over China. After the normalized processing and Box-Cox transformation of the data, we used the geographically weighted regression (GWR) method to describe the spatial precipitation trend, and then interpolated the residual by using a modified high accuracy surface modeling method (HASM-PRE). A high quality database of monthly precipitation with a resolution of 1 km(2) was constructed based on the meteorological stations. Results showed that wet years and dry years appear alternatively, and trend analysis of precipitation data series from 1981 to 2010 showed that the probability of years with extreme precipitation has increased in recent years. Precipitation in winter is rather uncertain and more dynamic from year to year compared to precipitation in summer.
出处	Environmental Earth Sciences
卷	74
期	8
页	6459-6469
收录类别	SCI
语种	英语
ISSN号	1866-6280
内容类型	SCI/SSCI论文
源URL	[http://ir.igsnrr.ac.cn/handle/311030/38894]
专题	地理科学与资源研究所_历年回溯文献
推荐引用方式 GB/T 7714	Wang C. L.,Zhao, N.,Yue, T. X.,et al. Change trend of monthly precipitation in China with an improved surface modeling method. 2015.

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