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IOCAS-IR
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Synergistic Interdecadal Evolution of Precipitation over Eastern China and the Pacific Decadal Oscillation during 1951-2015 期刊论文
ADVANCES IN ATMOSPHERIC SCIENCES, 2024, 卷号: 41, 期号: 1, 页码: 53-72
作者:  Wu, Minmin;  Zhang, Rong-Hua;  Hu, Junya;  Zhi, Hai
收藏  |  浏览/下载：19/0  |  提交时间：2024/04/07
MTM-SVD  PDO  SST anomalies  interdecadal variability  precipitation over China  
The 2020-2021 prolonged La Nina evolution in the tropical Pacific 期刊论文
SCIENCE CHINA-EARTH SCIENCES, 2022, 页码: 19
作者:  Gao, Chuan;  Chen, Maonan;  Zhou, Lu;  Feng, Licheng;  Zhang, Rong-Hua
Adobe PDF(11034Kb)  |  收藏  |  浏览/下载：128/0  |  提交时间：2023/01/04
Prolonged La Nina evolution in 2020-2021  Subsurface effect on SST  Remote and local processes  Modeling experiments  
Effects of Temperature and Salinity on Surface Currents in the Equatorial Pacific 期刊论文
JOURNAL OF GEOPHYSICAL RESEARCH-OCEANS, 2022, 卷号: 127, 期号: 4, 页码: 22
作者:  Chen, Lu;  Zhang, Rong-Hua;  Gao, Chuan
Adobe PDF(3933Kb)  |  收藏  |  浏览/下载：190/0  |  提交时间：2022/07/18
the equatorial Pacific  surface currents  OSCAR product  temperature and salinity effects  
Mesoscale Surface Wind-SST Coupling in a High-Resolution CESM Over the KE and ARC Regions 期刊论文
JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS, 2021, 卷号: 13, 期号: 12, 页码: 16
作者:  Tang, Zhijia;  Zhang, Rong-Hua;  Wang, Hongna;  Zhang, Shaoqing;  Wang, Hong
Adobe PDF(5518Kb)  |  收藏  |  浏览/下载：180/0  |  提交时间：2022/02/18
mesoscale coupling  atmospheric response mechanisms  high-resolution climate model  the Kuroshio Extensions (KE)  the Agulhas Return Current (ARC)  
North Pacific Upper-Ocean Cold Temperature Biases in CMIP6 Simulations and the Role of Regional Vertical Mixing 期刊论文
JOURNAL OF CLIMATE, 2020, 卷号: 33, 期号: 17, 页码: 7523-7538
作者:  Zhu, Yuchao;  Zhang, Rong-Hua;  Sun, Jichang
Adobe PDF(3067Kb)  |  收藏  |  浏览/下载：248/0  |  提交时间：2021/04/14
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：212/0  |  提交时间：2020/09/25
El Nino-Southern Oscillation (ENSO)  coupled ocean-atmosphere models  simulations and predictions  model biases and uncertainties  
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：338/0  |  提交时间：2019/08/28
IOCAS ICM  hybrid coupled model  ENSO simulation  atmospheric response  
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：445/0  |  提交时间：2019/08/27
ENSO prediction and predictability  coupled model  ensemble prediction  optimal error growth  probabilistic prediction  
Estimating Convection Parameters in the GFDL CM2.1 Model Using Ensemble Data Assimilation 期刊论文
JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS, 2018, 卷号: 10, 期号: 4, 页码: 989-1010
作者:  Li, Shan;  Zhang, Shaoqing;  Liu, Zhengyu;  Lu, Lv;  Zhu, Jiang;  Zhang, Xuefeng;  Wu, Xinrong;  Zhao, Ming;  Vecchi, Gabriel A.;  Zhang, Rong-Hua;  Lin, Xiaopei
Adobe PDF(3658Kb)  |  收藏  |  浏览/下载：414/0  |  提交时间：2018/10/29
parameter estimation  data assimilation  coupled climate model  convection  
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