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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)
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浏览/下载:114/0
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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)
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浏览/下载:128/0
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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)
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浏览/下载:262/0
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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)
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浏览/下载:283/0
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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)
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浏览/下载:240/0
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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)
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浏览/下载:253/0
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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)
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浏览/下载:305/0
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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)
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浏览/下载:184/0
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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)
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浏览/下载:179/0
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提交时间:2015/06/11
Adaptive Observation
Tropical Cyclone
Intensity Forecast
Conditional Nonlinear Optimal Perturbation
Remote effects of tropical cyclone wind forcing over the western Pacific on the eastern equatorial ocean
期刊论文
ADVANCES IN ATMOSPHERIC SCIENCES, 2013, 卷号: 30, 期号: 6, 页码: 1507-1525
作者:
Zhang Ronghua
;
Pei Yuhua
;
Chen Dake
Adobe PDF(2757Kb)
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浏览/下载:317/0
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提交时间:2014/08/28
Tropical Cyclone Wind Forcing
Ocean Modeling
Remote Effects
Ocean Pathway
Satellite Data
Nino-southern Oscillation
Mixed-layer Model
Fresh-water Flux
El-nino
North Pacific
Hurricane
Enso
Variability
Simulation
Intensity