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Different El Ni?o Flavors and Associated Atmospheric Teleconnections as Simulated in a Hybrid Coupled Model 期刊论文
ADVANCES IN ATMOSPHERIC SCIENCES, 2024, 页码: 17
作者:  Hu, Junya;  Wang, Hongna;  Gao, Chuan;  Zhang, Rong-Hua
收藏  |  浏览/下载：3/0  |  提交时间：2024/04/07
hybrid coupled model  tropical Pacific Ocean  global atmosphere  Eastern/Central-Pacific El Nino  atmospheric teleconnections  
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：128/0  |  提交时间：2022/04/12
ENSO prediction  the principal oscillation pattern (POP) analyses  neural network  a hybrid approach  
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
作者:  Feng, Licheng;  Liu, Fei;  Zhang, Rong-Hua;  Han, Xue;  Yu, Bo;  Gao, Chuan
Adobe PDF(3442Kb)  |  收藏  |  浏览/下载：150/0  |  提交时间：2022/01/05
second-year warming  IOD  wind stress anomalies  zonal advection feedback  thermocline feedback  
Roles of Wind Stress and Subsurface Cold Water in the Second-Year Cooling of the 2017/18 La Nina Event 期刊论文
ADVANCES IN ATMOSPHERIC SCIENCES, 2020, 卷号: 37, 期号: 8, 页码: 847-860
作者:  Feng, Licheng;  Zhang, Rong-Hua;  Yu, Bo;  Han, Xue
Adobe PDF(6509Kb)  |  收藏  |  浏览/下载：165/0  |  提交时间：2020/09/25
2017  18 La Nina  second-year cooling in 2017  wind stress anomalies  subsurface cold anomalies  
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：163/0  |  提交时间：2020/09/21
optimal precursor  ENSO  gradient-definition-based method  conditional nonlinear optimal perturbation  intermediate coupled model  
Interannual Salinity Variability in the Tropical Pacific in CMIP5 Simulations 期刊论文
ADVANCES IN ATMOSPHERIC SCIENCES, 2019, 卷号: 36, 期号: 4, 页码: 378-396
作者:  Zhi, Hai;  Zhang, Rong-Hua;  Lin, Pengfei;  Yu, Peng
Adobe PDF(5481Kb)  |  收藏  |  浏览/下载：315/0  |  提交时间：2019/08/28
mixed-layer salinity  salt budget  interannual variability  tropical Pacific  model simulation  
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：330/0  |  提交时间：2019/08/21
El Nino prediction  initial condition errors  target observations  
Role of the oceanic channel in the relationships between the basin/dipole mode of SST anomalies in the tropical Indian Ocean and ENSO transition 期刊论文
ADVANCES IN ATMOSPHERIC SCIENCES, 2016, 卷号: 33, 期号: 12, 页码: 1386-1400
作者:  Zhao, Xia;  Yuan, Dongliang;  Yang, Guang;  Zhou, Hui;  Wang, Jing
Adobe PDF(7013Kb)  |  收藏  |  浏览/下载：274/0  |  提交时间：2017/03/21
Indian Ocean Sstas  Dipole Mode  Basin Mode  Enso Transition  Oceanic Channel  
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：315/0  |  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：325/0  |  提交时间：2016/05/03
Feedback  Interannual Variability  Sea Surface Salinity  Barrier Layer Thickness