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IOCAS-IR

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A Hybrid Neural Network Model for ENSO Prediction in Combination with Principal Oscillation Pattern Analyses 期刊论文
ADVANCES IN ATMOSPHERIC SCIENCES, 2022, 页码: 14
作者:  Zhou, Lu;  Zhang, Rong-Hua
Adobe PDF(2978Kb)  |  收藏  |  浏览/下载：132/0  |  提交时间：2022/04/12
ENSO prediction  the principal oscillation pattern (POP) analyses  neural network  a hybrid approach  
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
作者:  Mu, Bin;  Ren, Juhui;  Yuan, Shijin;  Zhang, Rong-Hua;  Chen, Lei;  Gao, Chuan
Adobe PDF(1429Kb)  |  收藏  |  浏览/下载：177/0  |  提交时间：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
作者:  Hu, Junya;  Zhang, Rong-Hua;  Gao, Chuan
Adobe PDF(7642Kb)  |  收藏  |  浏览/下载：310/0  |  提交时间：2019/08/28
IOCAS ICM  hybrid coupled model  ENSO simulation  atmospheric response  
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：356/0  |  提交时间：2019/08/21
El Nino prediction  initial condition errors  target observations  
Initial error-induced optimal perturbations in ENSO predictions, as derived from an intermediate coupled model 期刊论文
ADVANCES IN ATMOSPHERIC SCIENCES, 2017, 卷号: 34, 期号: 6, 页码: 791-803
作者:  Tao, Ling-Jiang;  Zhang, Rong-Hua;  Gao, Chuan
Adobe PDF(1934Kb)  |  收藏  |  浏览/下载：267/0  |  提交时间：2017/09/29
El Nino Predictability  Initial Errors  Intermediate Coupled Model  Spring Predictability Barrier  
Optimal precursors triggering the Kuroshio Extension state transition obtained by the Conditional Nonlinear Optimal Perturbation approach 期刊论文
ADVANCES IN ATMOSPHERIC SCIENCES, 2017, 卷号: 34, 期号: 6, 页码: 685-699
作者:  Zhang, Xing;  Mu, Mu;  Wang, Qiang;  Pierini, Stefano
Adobe PDF(9596Kb)  |  收藏  |  浏览/下载：257/0  |  提交时间：2017/09/29
Kuroshio Extension  States Transition  Cnop Approach  Optimal Precursor  Ocean Modeling  
Testing a four-dimensional variational data assimilation method using an improved intermediate coupled model for ENSO analysis and prediction 期刊论文
ADVANCES IN ATMOSPHERIC SCIENCES, 2016, 卷号: 33, 期号: 7, 页码: 875-888
作者:  Gao, Chuan;  Wu, Xinrong;  Zhang, Rong-Hua
Adobe PDF(1168Kb)  |  收藏  |  浏览/下载：319/0  |  提交时间：2016/09/21
Four-dimensional Variational Data Assimilation  Intermediate Coupled Model  Twin Experiment  Enso Prediction  
Assessment of Interannual Sea Surface Salinity Variability and Its Effects on the Barrier Layer in the Equatorial Pacific Using BNU-ESM 期刊论文
ADVANCES IN ATMOSPHERIC SCIENCES, 2016, 卷号: 33, 期号: 3, 页码: 339-351
作者:  Zhi, Hai;  Zhang, Rong-Hua;  Zheng, Fei;  Lin, Pengfei;  Wang, Lanning;  Yu, Peng
Adobe PDF(6781Kb)  |  收藏  |  浏览/下载：327/0  |  提交时间：2016/05/03
Feedback  Interannual Variability  Sea Surface Salinity  Barrier Layer Thickness  
Effects of interannual salinity variability on the barrier layer in the western-central equatorial Pacific: A diagnostic analysis from Argo 期刊论文
ADVANCES IN ATMOSPHERIC SCIENCES, 2014, 卷号: 31, 期号: 3, 页码: 532-542
作者:  Zheng Fei;  Zhang Rong-Hua;  Zhu Jiang
Adobe PDF(1350Kb)  |  收藏  |  浏览/下载：293/2  |  提交时间：2014/08/28
Barrier Layer  Salinity Effect  Enso  Argo  
Can Adaptive Observations Improve Tropical Cyclone Intensity Forecasts? 期刊论文
ADVANCES IN ATMOSPHERIC SCIENCES, 2014, 卷号: 31, 期号: 2, 页码: 252-262
作者:  Qin Xiaohao;  Mu Mu;  Qin, XH (reprint author), Chinese Acad Sci, Inst Atmospher Phys, State Key Lab Numer Modeling Atmospher Sci & Geop, Beijing 100029, Peoples R China.
Adobe PDF(2793Kb)  |  收藏  |  浏览/下载：184/0  |  提交时间：2015/06/11
Adaptive Observation  Tropical Cyclone  Intensity Forecast  Conditional Nonlinear Optimal Perturbation