中文版 | English

在结果中检索

IOCAS-IR

浏览/检索结果: 共5条，第1-5条 帮助

限定条件    
已选(0)清除 条数/页：   排序方式：
Salinity effects on the 2014 warm "Blob" in the Northeast Pacific 期刊论文
ACTA OCEANOLOGICA SINICA, 2019, 卷号: 38, 期号: 9, 页码: 24-34
作者:  Zhi, Hai;  Lin, Pengfei;  Zhang, Rong-Hua;  Chai, Fei;  Liu, Hailong
Adobe PDF(2439Kb)  |  收藏  |  浏览/下载：344/0  |  提交时间：2020/01/03
warm "Blob"  mixed layer depth  surface and subsurface salinity anomalies  
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：206/0  |  提交时间：2019/05/15
Pacific Ocean  Atmosphere-ocean interaction  ENSO  Freshwater  Coupled models  Ecological models  
Model parameter-related optimal perturbations and their contributions to El Nino prediction errors 期刊论文
CLIMATE DYNAMICS, 2019, 卷号: 52, 期号: 3-4, 页码: 1425-1441
作者:  Tao, Ling-Jiang;  Gao, Chuan;  Zhang, Rong-Hua
Adobe PDF(6712Kb)  |  收藏  |  浏览/下载：197/0  |  提交时间：2019/05/15
Intermediate coupled model  CNOP approach  Model parameters  El Nino predictability  
A New Hybrid Coupled Model of Atmosphere, Ocean Physics, and Ocean Biogeochemistry to Represent Biogeophysical Feedback Effects in the Tropical Pacific 期刊论文
JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS, 2018, 卷号: 10, 期号: 8, 页码: 1901-1923
作者:  Zhang, Rong-Hua;  Tian, Feng;  Wang, Xiujun
Adobe PDF(4864Kb)  |  收藏  |  浏览/下载：303/0  |  提交时间：2019/08/27
an ocean biogeochemistry model  a hybrid coupled model for biogeochemistry-climate interactions  ocean biogeochemistry-induced feedback  ENSO modulations  
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：339/0  |  提交时间：2019/08/21
El Nino prediction  initial condition errors  target observations