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Improving terrestrial evapotranspiration estimation across China during 2000-2018 with machine learning methods 期刊论文
JOURNAL OF HYDROLOGY, 2021, 卷号: 600, 页码: 18
Authors:  Yin, Lichang;  Tao, Fulu;  Chen, Yi;  Liu, Fengshan;  Hu, Jian
Favorite  |  View/Download:8/0  |  Submit date:2021/11/05
Evapotranspiration  Machine learning  process-based ET  ET integration  China  Gaussian process regression  
Response of Growing Season Gross Primary Production to El Nino in Different Phases of the Pacific Decadal Oscillation over Eastern China Based on Bayesian Model Averaging 期刊论文
ADVANCES IN ATMOSPHERIC SCIENCES, 2021, 卷号: 38, 期号: 9, 页码: 1580-1595
Authors:  Li, Yueyue;  Dan, Li;  Peng, Jing;  Wang, Junbang;  Yang, Fuqiang;  Gao, Dongdong;  Yang, Xiujing;  Yu, Qiang
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East China  Bayesian model averaging  Gross primary production  El Nino  Pacific Decadal Oscillation  Monsoon rainfall  
A Comparison of SSEBop-Model-Based Evapotranspiration with Eight Evapotranspiration Products in the Yellow River Basin, China 期刊论文
REMOTE SENSING, 2020, 卷号: 12, 期号: 16, 页码: 30
Authors:  Yin, Lichang;  Wang, Xiaofeng;  Feng, Xiaoming;  Fu, Bojie;  Chen, Yongzhe
Favorite  |  View/Download:14/0  |  Submit date:2021/03/18
evapotranspiration  operational simplified surface energy balance model  Yellow River Basin  
Using multi-model ensembles of CMIP5 global climate models to reproduce observed monthly rainfall and temperature with machine learning methods in Australia 期刊论文
INTERNATIONAL JOURNAL OF CLIMATOLOGY, 2018, 卷号: 38, 期号: 13, 页码: 4891-4902
Authors:  Wang, Bin;  Zheng, Lihong;  Liu, De Li;  Ji, Fei;  Clark, Anthony;  Yu, Qiang
Favorite  |  View/Download:35/0  |  Submit date:2019/05/23
GCMs  machine learning  multi-model ensemble  random forest  support vector machine  
Improving global terrestrial evapotranspiration estimation using support vector machine by integrating three process-based algorithms 期刊论文
AGRICULTURAL AND FOREST METEOROLOGY, 2017, 卷号: 242, 页码: 55-74
Authors:  Yao, Yunjun;  Liang, Shunlin;  Li, Xianglan;  Chen, Jiquan;  Liu, Shaomin;  Jia, Kun;  Zhang, Xiaotong;  Xiao, Zhiqiang;  Fisher, Joshua B.;  Mu, Qiaozhen;  Pan, Ming;  Liu, Meng;  Cheng, Jie;  Jiang, Bo;  Xie, Xianhong;  Gruenwald, Thomas;  Bernhofer, Christian;  Roupsard, Olivier
Favorite  |  View/Download:26/0  |  Submit date:2019/09/25
Terrestrial evapotranspiration  Machine learning methods  Bayesian model averaging method  Plant functional type  
Simulation of the climatic effects of land use/land cover changes in eastern China using multi-model ensembles 期刊论文
GLOBAL AND PLANETARY CHANGE, 2017, 卷号: 154, 页码: 1-9
Authors:  Zhang, Xianliang;  Xiong, Zhe;  Zhang, Xuezhen;  Shi, Ying;  Liu, Jiyuan;  Shao, Quanqin;  Yan, Xiaodong
Favorite  |  View/Download:26/0  |  Submit date:2019/09/25
Land use change  Eastern China  Multi-model ensemble  WRF  RegCM3  RIEMS  
气候变化对我国甘蔗适宜种植区分布和产量的影响 学位论文
硕士, 北京: 中国科学院研究生院, 2017
Authors:  宓春荣
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Using multi-model ensembles to improve the simulated effects of land use/cover change on temperature: a case study over northeast China 期刊论文
CLIMATE DYNAMICS, 2016, 卷号: 46, 期号: 3-4, 页码: 765-778
Authors:  Zhang, Xianliang;  Xiong, Zhe;  Zhang, Xuezhen;  Shi, Ying;  Liu, Jiyuan;  Shao, Quanqin;  Yan, Xiaodong
Favorite  |  View/Download:22/0  |  Submit date:2019/09/26
Land use/cover change  Regional climate model  Multi-model ensemble  Bayesian model averaging  
Evaluating the skill of NMME seasonal precipitation ensemble predictions for 17 hydroclimatic regions in continental China SCI/SSCI论文
2016
Authors:  Ma F.;  Ye, A. Z.;  Deng, X. X.;  Zhou, Z.;  Liu, X. J.;  Duan, Q. Y.;  Xu, J.;  Miao, C. Y.;  Di, Z. H.;  Gong, W.
View  |  Adobe PDF(2151Kb)  |  Favorite  |  View/Download:179/70  |  Submit date:2017/11/09
seasonal precipitation predictions  NMME  BMA  RRMSE-R diagram  China  american multimodel ensemble  to-interannual prediction  climate  forecast system  potential predictability  data assimilation  united-states  rainfall  model  simulations  variability  
Causality between abundance and diversity is weak for wintering migratory waterbirds SCI/SSCI论文
2016
Authors:  Guan L.;  Jia, Y. F.;  Saintilan, N.;  Wang, Y. Y.;  Liu, G. H.;  Lei, G. C.;  Wen, L.
View  |  Adobe PDF(765Kb)  |  Favorite  |  View/Download:111/48  |  Submit date:2017/11/09
habitat quality  migratory waterbird  more individuals hypothesis  Poyang Lake  species-area relationship  species-energy theory  poyang lake  individuals hypothesis  productivity  relationships  community structure  bird communities  scale variation  santa-rosalia  woody plant  richness