干旱区生态环境知识资源中心(Arid): Using Quantile Regression to Detect Relationships between Large-scale Predictors and Local Precipitation over Northern China

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	Using Quantile Regression to Detect Relationships between Large-scale Predictors and Local Precipitation over Northern China
	Fan Lijun; Xiong Zhe
来源期刊	Advances in Atmospheric Sciences
ISSN	0256-1530
出版年	2015
卷号	32 期号:4 页码:541-552
英文摘要	Quantile regression (QR) is proposed to examine the relationships between large-scale atmospheric variables and all parts of the distribution of daily precipitation amount at Beijing Station from 1960 to 2008. QR is also applied to evaluate the relationship between large-scale predictors and extreme precipitation (90th quantile) at 238 stations in northern China.Finally, QR is used to fit observed daily precipitation amounts for wet days at four sample stations. Results show that meridional wind and specific humidity at both 850 hPa and 500 hPa (V850, SH850, V500, and SH500) strongly affect all parts of the Beijing precipitation distribution during the wet season (April-September). Meridional wind, zonal wind, and specific humidity at only 850 hPa (V850, U850, SH850) are significantly related to the precipitation distribution in the dry season (October-March). Impacts of these large-scale predictors on the daily precipitation amount with higher quantile become stronger, whereas their impact on light precipitation is negligible. In addition, SH850 has a strong relationship with wet-season extreme precipitation across the entire region, whereas the impacts of V850, V500, and SH500 are mainly in semi-arid and semi-humid areas. For the dry season, both SH850 and V850 are the major predictors of extreme precipitation in the entire region. Moreover, QR can satisfactorily simulate the daily precipitation amount at each station and for each season, if an optimum distribution family is selected. Therefore, QR is valuable for detecting the relationship between the large-scale predictors and the daily precipitation amount.
英文关键词	quantile regression large-scale predictors precipitation distribution predictor-precipitation relationship northern China
类型	Article
语种	英语
收录类别	CSCD
WOS研究方向	Science & Technology - Other Topics
CSCD记录号	CSCD:5342387
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/335437
作者单位	Fan Lijun, Institute of Atmospheric Physics,Chinese Academy of Sciences,,Chinese Academy of Sciences, Key Laboratory of Regional Climate-Environment Research for Temperate East Asia, Beijing 100029, China.; Xiong Zhe, Institute of Atmospheric Physics,Chinese Academy of Sciences,,Chinese Academy of Sciences, Key Laboratory of Regional Climate-Environment Research for Temperate East Asia, Beijing 100029, China.
推荐引用方式 GB/T 7714	Fan Lijun,Xiong Zhe. Using Quantile Regression to Detect Relationships between Large-scale Predictors and Local Precipitation over Northern China[J],2015,32(4):541-552.
APA	Fan Lijun,&Xiong Zhe.(2015).Using Quantile Regression to Detect Relationships between Large-scale Predictors and Local Precipitation over Northern China.Advances in Atmospheric Sciences,32(4),541-552.
MLA	Fan Lijun,et al."Using Quantile Regression to Detect Relationships between Large-scale Predictors and Local Precipitation over Northern China".Advances in Atmospheric Sciences 32.4(2015):541-552.