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On the Second-Year Warming in Late 2019 over the Tropical Pacific and Its Attribution to an Indian Ocean Dipole Event 期刊论文
ADVANCES IN ATMOSPHERIC SCIENCES, 2021, 卷号: 38, 期号: 12, 页码: 2153-2166
Authors:  Feng, Licheng;  Liu, Fei;  Zhang, Rong-Hua;  Han, Xue;  Yu, Bo;  Gao, Chuan
Adobe PDF(3442Kb)  |  Favorite  |  View/Download：21/0  |  Submit date：2022/01/05
second-year warming  IOD  wind stress anomalies  zonal advection feedback  thermocline feedback  
A review of progress in coupled ocean-atmosphere model developments for ENSO studies in China 期刊论文
JOURNAL OF OCEANOLOGY AND LIMNOLOGY, 2020, 卷号: 38, 期号: 4, 页码: 930-961
Authors:  Zhang Rong-Hua;  Yu Yongqiang;  Song Zhenya;  Ren Hong-Li;  Tang Youmin;  Qiao Fangli;  Wu Tongwen;  Gao Chuan;  Hu Junye;  Tian Feng;  Zhu Yuchao;  Chen Lin;  Liu Hailong;  Lin Pengfei;  Wu Fanghua;  Wang Lin
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El Nino-Southern Oscillation (ENSO)  coupled ocean-atmosphere models  simulations and predictions  model biases and uncertainties  
Separating freshwater flux effects on ENSO in a hybrid coupled model of the tropical Pacific 期刊论文
CLIMATE DYNAMICS, 2020, 页码: 22
Authors:  Gao, Chuan;  Zhang, Rong-Hua;  Karnauskas, Kristopher B.;  Zhang, Lei;  Tian, Feng
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Freshwater flux effects  Sea surface salinity  Buoyancy flux  Feedbacks on ENSO  Layer and level ocean models  
The Optimal Precursors for ENSO Events Depicted Using the Gradient-definition-based Method in an Intermediate Coupled Model 期刊论文
ADVANCES IN ATMOSPHERIC SCIENCES, 2019, 卷号: 36, 期号: 12, 页码: 1381-1392
Authors:  Mu, Bin;  Ren, Juhui;  Yuan, Shijin;  Zhang, Rong-Hua;  Chen, Lei;  Gao, Chuan
Adobe PDF(1429Kb)  |  Favorite  |  View/Download：35/0  |  Submit date：2020/09/21
optimal precursor  ENSO  gradient-definition-based method  conditional nonlinear optimal perturbation  intermediate coupled model  
A Hybrid Coupled Ocean-Atmosphere Model and Its Simulation of ENSO and Atmospheric Responses 期刊论文
ADVANCES IN ATMOSPHERIC SCIENCES, 2019, 卷号: 36, 期号: 6, 页码: 643-657
Authors:  Hu, Junya;  Zhang, Rong-Hua;  Gao, Chuan
Adobe PDF(7642Kb)  |  Favorite  |  View/Download：109/0  |  Submit date：2019/08/28
IOCAS ICM  hybrid coupled model  ENSO simulation  atmospheric response  
Model parameter-related optimal perturbations and their contributions to El Nino prediction errors 期刊论文
CLIMATE DYNAMICS, 2019, 卷号: 52, 期号: 3-4, 页码: 1425-1441
Authors:  Tao, Ling-Jiang;  Gao, Chuan;  Zhang, Rong-Hua
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Intermediate coupled model  CNOP approach  Model parameters  El Nino predictability  
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
Authors:  Tang, Youmin;  Zhang, Rong-Hua;  Liu, Ting;  Duan, Wansuo;  Yang, Dejian;  Zheng, Fei;  Ren, Hongli;  Lian, Tao;  Gao, Chuan;  Chen, Dake;  Mu, Mu
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ENSO prediction and predictability  coupled model  ensemble prediction  optimal error growth  probabilistic prediction  
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
Authors:  Zhang, Rong-Hua;  Tao, Ling-Jiang;  Gao, Chuan
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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
Authors:  Tao, Ling-Jiang;  Gao, Chuan;  Zhang, Rong-Hua
Adobe PDF(1354Kb)  |  Favorite  |  View/Download：123/0  |  Submit date：2019/08/21
El Nino prediction  initial condition errors  target observations  
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
Authors:  Gao, Chuan;  Zhang, Rong-Hua;  Wu, Xinrong;  Sun, Jichang
Adobe PDF(1370Kb)  |  Favorite  |  View/Download：99/0  |  Submit date：2019/08/21
intermediate coupled model  ENSO modeling  4D-Var data assimilation system  optimization of model parameter and initial condition