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DOI | 10.1007/s00382-018-4257-5 |
CWRF performance at downscaling China climate characteristics | |
Liang, Xin-Zhong1,2,3; Sun, Chao1,2; Zheng, Xiaohui2,4; Dai, Yongjiu5; Xu, Min6; Choi, Hyun I.7; Ling, Tiejun8; Qiao, Fengxue9; Kong, Xianghui10; Bi, Xunqiang10; Song, Lianchun11; Wang, Fang11 | |
2019-02-01 | |
发表期刊 | CLIMATE DYNAMICS |
ISSN | 0930-7575 |
EISSN | 1432-0894 |
出版年 | 2019 |
卷号 | 52页码:2159-2184 |
文章类型 | Article |
语种 | 英语 |
国家 | USA; Peoples R China; South Korea |
英文摘要 | The performance of the regional Climate-Weather Research and Forecasting model (CWRF) for downscaling China climate characteristics is evaluated using a 1980-2015 simulation at 30km grid spacing driven by the ECMWF Interim reanalysis (ERI). It is shown that CWRF outperforms the popular Regional Climate Modeling system (RegCM4.6) in key features including monsoon rain bands, diurnal temperature ranges, surface winds, interannual precipitation and temperature anomalies, humidity couplings, and 95th percentile daily precipitation. Even compared with ERI, which assimilates surface observations, CWRF better represents the geographic distributions of seasonal mean climate and extreme precipitation. These results indicate that CWRF may significantly enhance China climate modeling capabilities. |
英文关键词 | Regional climate model Downscaling performance Extreme precipitation Diurnal temperature range Surface wind CWRF |
领域 | 气候变化 |
收录类别 | SCI-E |
WOS记录号 | WOS:000460902200050 |
WOS关键词 | MODELING SYSTEM RIEMS ; EAST-ASIA ; MONSOON PRECIPITATION ; SUMMER PRECIPITATION ; PART I ; CUMULUS PARAMETERIZATION ; SURFACE-TEMPERATURE ; US PRECIPITATION ; EXTREME EVENTS ; BOUNDARY-LAYER |
WOS类目 | Meteorology & Atmospheric Sciences |
WOS研究方向 | Meteorology & Atmospheric Sciences |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/36426 |
专题 | 气候变化 |
作者单位 | 1.Univ Maryland, Dept Atmospher & Ocean Sci, College Pk, MD 20742 USA; 2.Univ Maryland, Earth Syst Sci Interdisciplinary Ctr, 5825 Univ Res Court,Suite 4001, College Pk, MD 20740 USA; 3.Nanjing Univ Informat Sci & Technol, Sch Atmospher Sci, Climate Environm & Sustainabil Ctr, Nanjing, Jiangsu, Peoples R China; 4.Beijing Normal Univ, Coll Global Change & Earth Syst Sci, Beijing, Peoples R China; 5.Sun Yat Sen Univ, Sch Atmospher Sci, Guangzhou, Guangdong, Peoples R China; 6.Oak Ridge Natl Lab, Climate Change Sci Inst, Oak Ridge, TN USA; 7.Yeungnam Univ, Dept Civil Engn, Gyongsan, South Korea; 8.Natl Marine Environm Forecasting Ctr, Key Lab Res Marine Hazards Forecasting, Beijing, Peoples R China; 9.East China Normal Univ, Minist Educ, Key Lab Geog Informat Sci, Shanghai, Peoples R China; 10.Chinese Acad Sci, Inst Atmospher Phys, Climate Change Res Ctr, Beijing, Peoples R China; 11.China Meteorol Adm, Natl Climate Ctr, Beijing, Peoples R China |
推荐引用方式 GB/T 7714 | Liang, Xin-Zhong,Sun, Chao,Zheng, Xiaohui,et al. CWRF performance at downscaling China climate characteristics[J]. CLIMATE DYNAMICS,2019,52:2159-2184. |
APA | Liang, Xin-Zhong.,Sun, Chao.,Zheng, Xiaohui.,Dai, Yongjiu.,Xu, Min.,...&Wang, Fang.(2019).CWRF performance at downscaling China climate characteristics.CLIMATE DYNAMICS,52,2159-2184. |
MLA | Liang, Xin-Zhong,et al."CWRF performance at downscaling China climate characteristics".CLIMATE DYNAMICS 52(2019):2159-2184. |
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