IGSNRR OpenIR
High-resolution precipitation data derived from dynamical downscaling using the WRF model for the Heihe River Basin, northwest China
Zhang, Xuezhen1,3; Xiong, Zhe2; Zheng, Jingyun1,3; Ge, Quansheng1
2018-02-01
Source PublicationTHEORETICAL AND APPLIED CLIMATOLOGY
ISSN0177-798X
Volume131Issue:3-4Pages:1249-1259
Corresponding AuthorZhang, Xuezhen(xzzhang@igsnrr.ac.cn)
AbstractThe community of climate change impact assessments and adaptations research needs regional high-resolution (spatial) meteorological data. This study produced two downscaled precipitation datasets with spatial resolutions of as high as 3 km by 3 km for the Heihe River Basin (HRB) from 2011 to 2014 using the Weather Research and Forecast (WRF) model nested with Final Analysis (FNL) from the National Center for Environmental Prediction (NCEP) and ERA-Interim from the European Centre for Medium-Range Weather Forecasts (ECMWF) (hereafter referred to as FNLexp and ERAexp, respectively). Both of the downscaling simulations generally reproduced the observed spatial patterns of precipitation. However, users should keep in mind that the two downscaled datasets are not exactly the same in terms of observations. In comparison to the remote sensing-based estimation, the FNLexp produced a bias of heavy precipitation centers. In comparison to the ground gauge-based measurements, for the warm season (May to September), the ERAexp produced more precipitation (root-mean-square error (RMSE) = 295.4 mm, across the 43 sites) and more heavy rainfall days, while the FNLexp produced less precipitation (RMSE = 115.6 mm) and less heavy rainfall days. Both the ERAexp and FNLexp produced considerably more precipitation for the cold season (October to April) with RMSE values of 119.5 and 32.2 mm, respectively, and more heavy precipitation days. Along with simulating a higher number of heavy precipitation days, both the FNLexp and ERAexp also simulated stronger extreme precipitation. Sensitivity experiments show that the bias of these simulations is much more sensitive to micro-physical parameterizations than to the spatial resolution of topography data. For the HRB, application of the WSM3 scheme may improve the performance of the WRF model.
DOI10.1007/s00704-017-2052-6
WOS KeywordBULK PARAMETERIZATION ; CLIMATE ; SIMULATIONS ; 1980S
Indexed BySCI
Language英语
Funding ProjectNational Natural Science Foundation of China[91425304] ; National Natural Science Foundation of China[41471171] ; Youth Innovation Promotion Association CAS[2015038] ; Kezhen Outstanding Young Scholars from IGSNRR[2015RC101]
Funding OrganizationNational Natural Science Foundation of China ; Youth Innovation Promotion Association CAS ; Kezhen Outstanding Young Scholars from IGSNRR
WOS Research AreaMeteorology & Atmospheric Sciences
WOS SubjectMeteorology & Atmospheric Sciences
WOS IDWOS:000423574800028
PublisherSPRINGER WIEN
Citation statistics
Cited Times:6[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/56953
Collection中国科学院地理科学与资源研究所
Corresponding AuthorZhang, Xuezhen
Affiliation1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Land Surface Pattern & Simulat, Beijing 100101, Peoples R China
2.Chinese Acad Sci, Inst Atmospher Phys, Key Lab Reg Climate Environm East Asia, Beijing 100029, Peoples R China
3.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
Recommended Citation
GB/T 7714
Zhang, Xuezhen,Xiong, Zhe,Zheng, Jingyun,et al. High-resolution precipitation data derived from dynamical downscaling using the WRF model for the Heihe River Basin, northwest China[J]. THEORETICAL AND APPLIED CLIMATOLOGY,2018,131(3-4):1249-1259.
APA Zhang, Xuezhen,Xiong, Zhe,Zheng, Jingyun,&Ge, Quansheng.(2018).High-resolution precipitation data derived from dynamical downscaling using the WRF model for the Heihe River Basin, northwest China.THEORETICAL AND APPLIED CLIMATOLOGY,131(3-4),1249-1259.
MLA Zhang, Xuezhen,et al."High-resolution precipitation data derived from dynamical downscaling using the WRF model for the Heihe River Basin, northwest China".THEORETICAL AND APPLIED CLIMATOLOGY 131.3-4(2018):1249-1259.
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