中文版 | English

在结果中检索

IOCAS-IR

浏览/检索结果: 共17条，第1-10条 帮助

限定条件    
已选(0)清除 条数/页：   排序方式：
U-Net Models for Representing Wind Stress Anomalies over the Tropical Pacific and Their Integrations with an Intermediate Coupled Model for ENSO Studies 期刊论文
ADVANCES IN ATMOSPHERIC SCIENCES, 2024, 页码: 14
作者:  Du, Shuangying;  Zhang, Rong-Hua
收藏  |  浏览/下载：4/0  |  提交时间：2024/06/04
U-Net models  wind stress anomalies  ICM  integration of AI and physical components  
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：153/0  |  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：202/0  |  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：372/0  |  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：388/0  |  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：288/0  |  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：301/0  |  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：334/0  |  提交时间：2016/09/21
Four-dimensional Variational Data Assimilation  Intermediate Coupled Model  Twin Experiment  Enso Prediction  
Role of parameter errors in the spring predictability barrier for ENSO events in the Zebiak-Cane model 期刊论文
ADVANCES IN ATMOSPHERIC SCIENCES, 2014, 卷号: 31, 期号: 3, 页码: 647-656
作者:  Yu Liang;  Mu Mu;  Yu, Yanshan;  Mu, M (reprint author), Chinese Acad Sci, Inst Oceanol, Key Lab Ocean Circulat & Waves, Qingdao 266071, Peoples R China.
Adobe PDF(500Kb)  |  收藏  |  浏览/下载：251/0  |  提交时间：2015/06/11
Enso Predictability  Spring Predictability Barrier  Initial Errors  Parameter Errors  Error Growth  
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：193/0  |  提交时间：2015/06/11
Adaptive Observation  Tropical Cyclone  Intensity Forecast  Conditional Nonlinear Optimal Perturbation