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More realistic land-use and vegetation parameters in a regional climate model reduce model biases over China

文献类型：期刊论文

作者Gou, Jiaojiao1,3,4; Wang, Fei1,3; Jin, Kai3; Mu, Xingmin1,3; Chen, Deliang2
刊名INTERNATIONAL JOURNAL OF CLIMATOLOGY
出版日期2019-10-01
卷号39期号:12页码:4825-4837
关键词China CLM improved climate simulations plant functional type RegCM
ISSN号0899-8418
DOI10.1002/joc.6110
通讯作者Wang, Fei(wafe@ms.iswc.ac.cn)
英文摘要Accurate vegetation cover data are important for realistic simulation of regional climate. The default vegetation parameters from Global Land Cover 2000, currently incorporated into global climate models and used in regional climate model RegCM, are not realistic for China, which may have contributed to serious bias in surface climate simulation. In this study, a new set of vegetation parameters considering the Plant Functional Type (PFT) fractions and the corresponding monthly leaf area index (PFT_LAI), were developed based on the land cover and MODIS LAI data sets. The regional climate model RegCM4.5 coupled with the land surface model CLM4.5 were utilized to test the performance of the new vegetation parameters by comparing simulations with observations using different surface parameters. The surface energy balance was analysed to examine the effects of changed vegetation parameters on regional climate. The results showed that the new parameters were more accurate than the GLC2000 parameters when describing the distribution of crops, grassland, and forests over China. The improved vegetation parameters reduced model biases for winter air temperature and precipitation over southern China by 0.9 degrees C and 8%, respectively, and reduced the winter temperature and summer precipitation biases over northeastern China by approximately 0.7 degrees C and 8%, respectively. More accurate surface albedo are the main reasons for reductions in model bias. However, certain biases, such as the cold and dry bias over the Tibetan Plateau, still remained in the simulation results using our new vegetation data.
WOS关键词COVER CHANGES ; REGCM4 ; TEMPERATURE ; RAINFALL ; IMPACTS ; DATASET
资助项目European Union's Horizon 2020 Programme[635750] ; External Cooperation Program of BIC, Chinese Academy of Sciences[16146KYSB20150001] ; National Key Research and Development Program of China[2016YFC0501707] ; National Natural Science Foundation of China (NSFC)[41771558]
WOS研究方向Meteorology & Atmospheric Sciences
语种英语
WOS记录号WOS:000489003100017
出版者WILEY
资助机构European Union's Horizon 2020 Programme ; External Cooperation Program of BIC, Chinese Academy of Sciences ; National Key Research and Development Program of China ; National Natural Science Foundation of China (NSFC)
源URL[http://ir.igsnrr.ac.cn/handle/311030/129925]  
专题中国科学院地理科学与资源研究所
通讯作者Wang, Fei
作者单位1.Chinese Acad Sci & Minist Water Resources, Inst Soil & Water Conservat, Yangling, Shaanxi, Peoples R China
2.Univ Gothenburg, Dept Earth Sci, Reg Climate Grp, Gothenburg, Sweden
3.Northwest A&F Univ, State Key Lab Soil Eros & Dryland Farming Loess P, Inst Soil & Water Conservat, Yangling, Shaanxi, Peoples R China
4.Beijing Normal Univ, Fac Geog Sci, State Key Lab Earth Surface Proc & Resource Ecol, Beijing, Peoples R China
推荐引用方式
GB/T 7714		 Gou, Jiaojiao,Wang, Fei,Jin, Kai,et al. More realistic land-use and vegetation parameters in a regional climate model reduce model biases over China[J]. INTERNATIONAL JOURNAL OF CLIMATOLOGY,2019,39(12):4825-4837.
APA Gou, Jiaojiao,Wang, Fei,Jin, Kai,Mu, Xingmin,&Chen, Deliang.(2019).More realistic land-use and vegetation parameters in a regional climate model reduce model biases over China.INTERNATIONAL JOURNAL OF CLIMATOLOGY,39(12),4825-4837.
MLA Gou, Jiaojiao,et al."More realistic land-use and vegetation parameters in a regional climate model reduce model biases over China".INTERNATIONAL JOURNAL OF CLIMATOLOGY 39.12(2019):4825-4837.

入库方式： OAI收割

来源：地理科学与资源研究所

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