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Statistical downscaling of precipitation using local regression and high accuracy surface modeling method

文献类型：期刊论文

作者Zhao, Na1,2; Yue, Tianxiang1,2; Zhou, Xun2; Zhao, Mingwei3; Liu, Yu2; Du, Zhengping2; Zhang, Lili2
刊名THEORETICAL AND APPLIED CLIMATOLOGY
出版日期2017-07-01
卷号129期号:1-2页码:281-292
ISSN号0177-798X
DOI10.1007/s00704-016-1776-z
通讯作者Zhao, Na(zhaon@lreis.ac.cn)
英文摘要Downscaling precipitation is required in local scale climate impact studies. In this paper, a statistical downscaling scheme was presented with a combination of geographically weighted regression (GWR) model and a recently developed method, high accuracy surface modeling method (HASM). This proposed method was compared with another downscaling method using the Coupled Model Intercomparison Project Phase 5 (CMIP5) database and ground-based data from 732 stations across China for the period 1976-2005. The residual which was produced by GWR was modified by comparing different interpolators including HASM, Kriging, inverse distance weighted method (IDW), and Spline. The spatial downscaling from 1A degrees to 1-km grids for period 1976-2005 and future scenarios was achieved by using the proposed downscaling method. The prediction accuracy was assessed at two separate validation sites throughout China and Jiangxi Province on both annual and seasonal scales, with the root mean square error (RMSE), mean relative error (MRE), and mean absolute error (MAE). The results indicate that the developed model in this study outperforms the method that builds transfer function using the gauge values. There is a large improvement in the results when using a residual correction with meteorological station observations. In comparison with other three classical interpolators, HASM shows better performance in modifying the residual produced by local regression method. The success of the developed technique lies in the effective use of the datasets and the modification process of the residual by using HASM. The results from the future climate scenarios show that precipitation exhibits overall increasing trend from T1 (2011-2040) to T2 (2041-2070) and T2 to T3 (2071-2100) in RCP2.6, RCP4.5, and RCP8.5 emission scenarios. The most significant increase occurs in RCP8.5 from T2 to T3, while the lowest increase is found in RCP2.6 from T2 to T3, increased by 47.11 and 2.12 mm, respectively.
WOS关键词GEOGRAPHICALLY WEIGHTED REGRESSION ; CLIMATE-CHANGE ; IMPACTS ; RAINFALL ; SDSM
资助项目National Natural Science Foundation of China[41541010] ; National Natural Science Foundation of China[91425304] ; National Natural Science Foundation of China[91325204] ; National Natural Science Foundation of China[41421001] ; Cultivate Project of Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Science[TSYJS03] ; Youth Science Funds of LREIS, CAS
WOS研究方向Meteorology & Atmospheric Sciences
语种英语
WOS记录号WOS:000403666400022
出版者SPRINGER WIEN
资助机构National Natural Science Foundation of China ; Cultivate Project of Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Science ; Youth Science Funds of LREIS, CAS
源URL[http://ir.igsnrr.ac.cn/handle/311030/63125]  
专题中国科学院地理科学与资源研究所
通讯作者Zhao, Na
作者单位1.Jiangsu Ctr Collaborat Innovat Geog Informat Reso, Nanjing 210023, Jiangsu, Peoples R China
2.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China
3.Chuzhou Univ, Anhui Ctr Collaborat Innovat Geog Informat Integr, Chuzhou 239012, Anhui, Peoples R China
推荐引用方式
GB/T 7714		 Zhao, Na,Yue, Tianxiang,Zhou, Xun,et al. Statistical downscaling of precipitation using local regression and high accuracy surface modeling method[J]. THEORETICAL AND APPLIED CLIMATOLOGY,2017,129(1-2):281-292.
APA Zhao, Na.,Yue, Tianxiang.,Zhou, Xun.,Zhao, Mingwei.,Liu, Yu.,...&Zhang, Lili.(2017).Statistical downscaling of precipitation using local regression and high accuracy surface modeling method.THEORETICAL AND APPLIED CLIMATOLOGY,129(1-2),281-292.
MLA Zhao, Na,et al."Statistical downscaling of precipitation using local regression and high accuracy surface modeling method".THEORETICAL AND APPLIED CLIMATOLOGY 129.1-2(2017):281-292.

入库方式： OAI收割

来源：地理科学与资源研究所

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