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Progress in ENSO prediction and predictability study 期刊论文
NATIONAL SCIENCE REVIEW, 2018, 卷号: 5, 期号: 6, 页码: 826-839
作者:  Tang, Youmin;  Zhang, Rong-Hua;  Liu, Ting;  Duan, Wansuo;  Yang, Dejian;  Zheng, Fei;  Ren, Hongli;  Lian, Tao;  Gao, Chuan;  Chen, Dake;  Mu, Mu
Adobe PDF(1925Kb)  |  收藏  |  浏览/下载：395/0  |  提交时间：2019/08/27
ENSO prediction and predictability  coupled model  ensemble prediction  optimal error growth  probabilistic prediction  
Scaling wind stirring effects in an oceanic bulk mixed layer model with application to an OGCM of the tropical Pacific 期刊论文
CLIMATE DYNAMICS, 2018, 卷号: 51, 期号: 5-6, 页码: 1927-1946
作者:  Zhu, Yuchao;  Zhang, Rong-Hua
Adobe PDF(8367Kb)  |  收藏  |  浏览/下载：343/0  |  提交时间：2019/08/23
Bulk mixed layer  Optimizing wind stirring effect  Ocean circulation models  
The ribosome biogenesis protein Esf1 is essential for pharyngeal cartilage formation in zebrafish 期刊论文
FEBS JOURNAL, 2018, 卷号: 285, 期号: 18, 页码: 3464-3484
作者:  Chen, Jian-Yang;  Tan, Xungang;  Wang, Zheng-Hua;  Liu, Yun-Zhang;  Zhou, Jian-Feng;  Rong, Xiao-Zhi;  Lu, Ling;  Li, Yun
Adobe PDF(11012Kb)  |  收藏  |  浏览/下载：340/0  |  提交时间：2019/08/27
apoptosis  neural crest cells  p53  pharyngeal cartilage  
A Coupled Ocean Physics-Biology Modeling Study on Tropical Instability Wave-Induced Chlorophyll Impacts in the Pacific 期刊论文
JOURNAL OF GEOPHYSICAL RESEARCH-OCEANS, 2018, 卷号: 123, 期号: 8, 页码: 5160-5179
作者:  Tian, Feng;  Zhang, Rong-Hua;  Wang, Xiujun
Adobe PDF(9753Kb)  |  收藏  |  浏览/下载：347/0  |  提交时间：2019/08/27
tropical instability waves  chlorophyll  bio-feedback  
A New Hybrid Coupled Model of Atmosphere, Ocean Physics, and Ocean Biogeochemistry to Represent Biogeophysical Feedback Effects in the Tropical Pacific 期刊论文
JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS, 2018, 卷号: 10, 期号: 8, 页码: 1901-1923
作者:  Zhang, Rong-Hua;  Tian, Feng;  Wang, Xiujun
Adobe PDF(4864Kb)  |  收藏  |  浏览/下载：301/0  |  提交时间：2019/08/27
an ocean biogeochemistry model  a hybrid coupled model for biogeochemistry-climate interactions  ocean biogeochemistry-induced feedback  ENSO modulations  
An improved simulation of the 2015 El Nio event by optimally correcting the initial conditions and model parameters in an intermediate coupled model 期刊论文
CLIMATE DYNAMICS, 2018, 卷号: 51, 期号: 1-2, 页码: 269-282
作者:  Zhang, Rong-Hua;  Tao, Ling-Jiang;  Gao, Chuan
Adobe PDF(3230Kb)  |  收藏  |  浏览/下载：282/0  |  提交时间：2019/08/21
The 2015 El Nino event  ICM  The CNOP-based approach  Optimal bias corrections to ICs and MPs  
ENSO Predictions in an Intermediate Coupled Model Influenced by Removing Initial Condition Errors in Sensitive Areas: A Target Observation Perspective 期刊论文
ADVANCES IN ATMOSPHERIC SCIENCES, 2018, 卷号: 35, 期号: 7, 页码: 853-867
作者:  Tao, Ling-Jiang;  Gao, Chuan;  Zhang, Rong-Hua
Adobe PDF(1354Kb)  |  收藏  |  浏览/下载：337/0  |  提交时间：2019/08/21
El Nino prediction  initial condition errors  target observations  
Effect of mesoscale wind stress-SST coupling on the Kuroshio extension jet 期刊论文
JOURNAL OF OCEANOLOGY AND LIMNOLOGY, 2018, 卷号: 36, 期号: 3, 页码: 612-619
作者:  Wei Yanzhou;  Zhang Ronghua;  Wang Hongna;  Kang Xianbiao
收藏  |  浏览/下载：269/0  |  提交时间：2020/01/03
mesoscale wind stress-SST coupling  Kuroshio extension  surface kinetic energy  ocean modeling  
Idealized Experiments for Optimizing Model Parameters Using a 4D-Variational Method in an Intermediate Coupled Model of ENSO 期刊论文
ADVANCES IN ATMOSPHERIC SCIENCES, 2018, 卷号: 35, 期号: 4, 页码: 410-422
作者:  Gao, Chuan;  Zhang, Rong-Hua;  Wu, Xinrong;  Sun, Jichang
Adobe PDF(1370Kb)  |  收藏  |  浏览/下载：265/0  |  提交时间：2019/08/21
intermediate coupled model  ENSO modeling  4D-Var data assimilation system  optimization of model parameter and initial condition  
Estimating Convection Parameters in the GFDL CM2.1 Model Using Ensemble Data Assimilation 期刊论文
JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS, 2018, 卷号: 10, 期号: 4, 页码: 989-1010
作者:  Li, Shan;  Zhang, Shaoqing;  Liu, Zhengyu;  Lu, Lv;  Zhu, Jiang;  Zhang, Xuefeng;  Wu, Xinrong;  Zhao, Ming;  Vecchi, Gabriel A.;  Zhang, Rong-Hua;  Lin, Xiaopei
Adobe PDF(3658Kb)  |  收藏  |  浏览/下载：378/0  |  提交时间：2018/10/29
parameter estimation  data assimilation  coupled climate model  convection