IOCAS-IR

浏览/检索结果: 共20条,第1-10条 帮助

限定条件    
已选(0)清除 条数/页:   排序方式:
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:1/0  |  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:124/0  |  提交时间:2022/04/12
ENSO prediction  the principal oscillation pattern (POP) analyses  neural network  a hybrid approach  
Structure and Evolution of Decadal Spiciness Variability in the North Pacific during 2004-20, Revealed from Argo Observations 期刊论文
ADVANCES IN ATMOSPHERIC SCIENCES, 2022, 页码: 14
作者:  Zhou, Guanghui;  Zhang, Rong-Hua
Adobe PDF(4536Kb)  |  收藏  |  浏览/下载:130/0  |  提交时间:2022/04/12
isopycnal analysis  spiciness anomalies  subduction pathway  advection role  decadal variability  North Pacific  
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:154/0  |  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:283/0  |  提交时间:2019/08/28
IOCAS ICM  hybrid coupled model  ENSO simulation  atmospheric response  
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:255/0  |  提交时间:2019/08/21
intermediate coupled model  ENSO modeling  4D-Var data assimilation system  optimization of model parameter and initial condition  
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:253/0  |  提交时间:2017/09/29
El Nino Predictability  Initial Errors  Intermediate Coupled Model  Spring Predictability Barrier  
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:268/0  |  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:314/0  |  提交时间:2016/09/21
Four-dimensional Variational Data Assimilation  Intermediate Coupled Model  Twin Experiment  Enso Prediction  
Influence of positive and negative Indian Ocean Dipoles on ENSO via the Indonesian Throughflow: Results from sensitivity experiments 期刊论文
ADVANCES IN ATMOSPHERIC SCIENCES, 2015, 卷号: 32, 期号: 6, 页码: 783-793
作者:  Zhou Qian;  Duan Wansuo;  Mu Mu;  Feng Rong
Adobe PDF(2994Kb)  |  收藏  |  浏览/下载:211/0  |  提交时间:2015/06/15
Iod  Pacific Ocean  Enso  Indonesian Throughflow