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IOCAS-IR
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A multi-model prediction system for ENSO 期刊论文
SCIENCE CHINA-EARTH SCIENCES, 2023, 页码: 10
作者:  Liu, Ting;  Gao, Yanqiu;  Song, Xunshu;  Gao, Chuan;  Tao, Lingjiang;  Tang, Youmin;  Duan, Wansuo;  Zhang, Rong-Hua;  Chen, Dake
收藏  |  浏览/下载：49/0  |  提交时间：2023/12/13
MME  ENSO  Prediction  
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  
Zonal Structure of Tropical Pacific Surface Salinity Anomalies Affects ENSO Intensity and Asymmetry 期刊论文
GEOPHYSICAL RESEARCH LETTERS, 2022, 卷号: 49, 期号: 1, 页码: 10
作者:  Guan, Cong;  Tian, Feng;  McPhaden, Michael J.;  Wang, Fan;  Hu, Shijian;  Zhang, Rong-Hua
Adobe PDF(5259Kb)  |  收藏  |  浏览/下载：176/0  |  提交时间：2022/04/12
ENSO  ENSO asymmetry  ENSO intensity  freshwater flux  salinity  vertical entrainment  
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
作者:  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
Adobe PDF(3839Kb)  |  收藏  |  浏览/下载：169/0  |  提交时间：2020/09/25
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
作者:  Gao, Chuan;  Zhang, Rong-Hua;  Karnauskas, Kristopher B.;  Zhang, Lei;  Tian, Feng
Adobe PDF(17407Kb)  |  收藏  |  浏览/下载：150/0  |  提交时间：2020/09/23
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
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  
Observed structural relationships between ocean chlorophyll variability and its heating effects on the ENSO 期刊论文
CLIMATE DYNAMICS, 2019, 卷号: 53, 期号: 9-10, 页码: 5165-5186
作者:  Zhang, Rong-Hua;  Tian, Feng;  Zhi, Hai;  Kang, Xianbiao
Adobe PDF(9387Kb)  |  收藏  |  浏览/下载：142/0  |  提交时间：2020/09/21
Chlorophyll variability  Ocean biology-induced heating  ENSO modulations  The penetration depth and mixed layer depth  Satellite and Argo data  
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  
Freshwater Flux and Ocean Chlorophyll Produce Nonlinear Feedbacks in the Tropical Pacific 期刊论文
JOURNAL OF CLIMATE, 2019, 卷号: 32, 期号: 7, 页码: 2037-2055
作者:  Zhang, Rong-Hua;  Tian, Feng;  Busalacchi, Antonio J.;  Wang, Xiujun
Adobe PDF(2641Kb)  |  收藏  |  浏览/下载：201/0  |  提交时间：2019/05/15
Pacific Ocean  Atmosphere-ocean interaction  ENSO  Freshwater  Coupled models  Ecological models  
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
作者:  Tang, Youmin;  Zhang, Rong-Hua;  Liu, Ting;  Duan, Wansuo;  Yang, Dejian;  Zheng, Fei;  Ren, Hongli;  Lian, Tao;  Gao, Chuan;  Chen, Dake;  Mu, Mu
Adobe PDF(1925Kb)  |  收藏  |  浏览/下载：377/0  |  提交时间：2019/08/27
ENSO prediction and predictability  coupled model  ensemble prediction  optimal error growth  probabilistic prediction