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Counteracting effects on ENSO induced by ocean chlorophyll interannual variability and tropical instability wave-scale perturbations in the tropical Pacific 期刊论文
SCIENCE CHINA-EARTH SCIENCES, 2023, 页码: 18
作者:  Zhang, Rong-Hua;  Tian, Feng;  Shi, Qidong;  Wang, Xiujun;  Wu, Tongwen
Adobe PDF(5337Kb)  |  收藏  |  浏览/下载：4/0  |  提交时间：2024/04/07
Ocean chlorophyll  Bio-climate feedbacks  Interannual variability  Tropical instability waves  Counteracting effects  A hybrid coupled model  
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：102/0  |  提交时间：2023/01/04
Prolonged La Nina evolution in 2020-2021  Subsurface effect on SST  Remote and local processes  Modeling experiments  
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：131/0  |  提交时间：2022/04/12
ENSO prediction  the principal oscillation pattern (POP) analyses  neural network  a hybrid approach  
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：152/0  |  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)  
Rectified Effects of Interannual Chlorophyll Variability on the Tropical Pacific Climate Revealed by a Hybrid Coupled Physics-Biology Model 期刊论文
JOURNAL OF GEOPHYSICAL RESEARCH-OCEANS, 2021, 卷号: 126, 期号: 6, 页码: 22
作者:  Tian, Feng;  Zhang, Rong-Hua;  Wang, Xiujun;  Zhi, Hai
Adobe PDF(4332Kb)  |  收藏  |  浏览/下载：157/0  |  提交时间：2021/12/07
The Thermocline Biases in the Tropical North Pacific and Their Attributions 期刊论文
JOURNAL OF CLIMATE, 2021, 卷号: 34, 期号: 5, 页码: 1635-1648
作者:  Zhu, Yuchao;  Zhang, Rong-Hua;  Li, Delei;  Chen, Dake
Adobe PDF(3211Kb)  |  收藏  |  浏览/下载：246/0  |  提交时间：2021/04/14
Climate models  Model errors  Model evaluation/performance  
Interannual-to-Decadal Variations of Particulate Organic Carbon and the Contribution of Phytoplankton in the Tropical Pacific During 1981-2016: A Model Study 期刊论文
JOURNAL OF GEOPHYSICAL RESEARCH-OCEANS, 2021, 卷号: 126, 期号: 1, 页码: 24
作者:  Yu, Jun;  Wang, Xiujun;  Murtugudde, Raghu;  Tian, Feng;  Zhang, Rong-Hua
Adobe PDF(8750Kb)  |  收藏  |  浏览/下载：193/0  |  提交时间：2021/04/21
climate impact  decadal variability  interannal variability  tropical Pacific  particulate organic carbon  phytoplankton contribution  
Interannual Salinity Variability Associated With the Central Pacific and Eastern Pacific El Ninos in the Tropical Pacific 期刊论文
JOURNAL OF GEOPHYSICAL RESEARCH-OCEANS, 2020, 卷号: 125, 期号: 10, 页码: 19
作者:  Zhi, Hai;  Zhang, Rong-Hua;  Lin, Pengfei;  Yu, Peng;  Zhou, Guanghui;  Shi, Shiwei
Adobe PDF(13185Kb)  |  收藏  |  浏览/下载：283/0  |  提交时间：2021/04/21
the eastern and central Pacific El Ninos  mixed layer salinity variability  salinity budget  the relationship between SST and MLS  
Purely satellite data-driven deep learning forecast of complicated tropical instability waves 期刊论文
SCIENCE ADVANCES, 2020, 卷号: 6, 期号: 29, 页码: 9
作者:  Zheng, Gang;  Li, Xiaofeng;  Zhang, Rong-Hua;  Liu, Bin
Adobe PDF(7758Kb)  |  收藏  |  浏览/下载：88/0  |  提交时间：2020/09/25
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：184/0  |  提交时间：2020/09/25
El Nino-Southern Oscillation (ENSO)  coupled ocean-atmosphere models  simulations and predictions  model biases and uncertainties