中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
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CAS IR Grid
机构
海洋研究所 [17]
中国科学院大学 [3]
采集方式
OAI收割 [17]
iSwitch采集 [3]
内容类型
期刊论文 [11]
CNKI期刊论文 [9]
发表日期
2020 [1]
2019 [1]
2017 [2]
2016 [3]
2015 [2]
2014 [1]
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学科主题
Meteorolog... [3]
Environmen... [1]
Marine & F... [1]
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浏览/检索结果:
共20条,第1-10条
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Impacts of parameter uncertainties on deep chlorophyll maximum simulation revealed by the CNOP-P approach
CNKI期刊论文
OAI收割
2020
作者:
GAO Yongli
;
MU Mu
;
ZHANG Kun
  |  
收藏
  |  
浏览/下载:6/0
  |  
提交时间:2024/12/18
deep chlorophyll maximum(DCM) simulation
parameter uncertainty
conditional nonlinear optimal perturbation related to parameters(CNOP-P)
sensitivity
Optimal precursors of double-gyre regime transitions with an adjoint-free method
CNKI期刊论文
OAI收割
2019
作者:
YUAN Shijin
;
LI Mi
;
WANG Qiang
;
ZHANG Kun
;
ZHANG Huazhen
  |  
收藏
  |  
浏览/下载:1/0
  |  
提交时间:2024/12/18
optimal precursors
double-gyre regime transitions
conditional nonlinear optimal perturbation(CNOP)
Principal Component Analysis-based Simulated Annealing(PCASA)
multiple-equilibria regimes
Identifying the sensitive area in adaptive observation for predicting the upstream Kuroshio transport variation in a 3-D ocean model
期刊论文
OAI收割
SCIENCE CHINA-EARTH SCIENCES, 2017, 卷号: 60, 期号: 5, 页码: 866-875
作者:
Zhang Kun
;
Mu Mu
;
Wang Qiang
  |  
收藏
  |  
浏览/下载:22/0
  |  
提交时间:2017/09/29
Sensitive Area
Adaptive Observation
The Upstream Kuroshio Transport
Conditional Nonlinear Optimal Perturbation (Cnop)
Identifying the sensitive area in adaptive observation for predicting the upstream Kuroshio transport variation in a 3-D ocean model
CNKI期刊论文
OAI收割
2017
作者:
ZHANG Kun
;
MU Mu
;
WANG Qiang
  |  
收藏
  |  
浏览/下载:4/0
  |  
提交时间:2024/12/18
Sensitive area
Adaptive observation
The upstream Kuroshio transport
Conditional nonlinear optimal perturbation(CNOP)
Identifying sensitive areas of adaptive observations for prediction of the Kuroshio large meander using a shallowwater model
CNKI期刊论文
OAI收割
2016
作者:
Zou GA(邹广安)
;
Wang Q(王强)
;
Mu M(穆穆)
  |  
收藏
  |  
浏览/下载:3/0
  |  
提交时间:2024/12/18
Kuroshio large meander
conditional nonlinear optimal perturbation(CNOP)
first singular vector(FSV)
sensitive areas
Identifying sensitive areas of adaptive observations for prediction of the Kuroshio large meander using a shallow-water model
期刊论文
OAI收割
CHINESE JOURNAL OF OCEANOLOGY AND LIMNOLOGY, 2016, 卷号: 34, 期号: 5, 页码: 1122-1133
作者:
Zou Guang'an
;
Wang Qiang
;
Mu Mu
收藏
  |  
浏览/下载:22/0
  |  
提交时间:2016/09/19
Kuroshio large meander
conditional nonlinear optimal perturbation (CNOP)
first singular vector (FSV)
sensitive areas
Identifying sensitive areas of adaptive observations for prediction of the kuroshio large meander using a shallow-water model
期刊论文
iSwitch采集
Chinese journal of oceanology and limnology, 2016, 卷号: 34, 期号: 5, 页码: 1122-1133
作者:
Zou Guang'an
;
Wang Qiang
;
Mu Mu
收藏
  |  
浏览/下载:41/0
  |  
提交时间:2019/05/09
Kuroshio large meander
Conditional nonlinear optimal perturbation (cnop)
First singular vector (fsv)
Sensitive areas
Impact of nonlinear processes on formation of the Kuroshio large meander path in a barotropic inflow-outflow model
CNKI期刊论文
OAI收割
2015
作者:
Zhang PJ(张培军)
;
Wang Q(王强)
;
Ma LB(马利斌)
  |  
收藏
  |  
浏览/下载:1/0
  |  
提交时间:2024/12/18
Kuroshio large meander
nonlinear perturbation advection
conditional nonlinear optimal perturbation(CNOP)
Impact of nonlinear processes on formation of the Kuroshio large meander path in a barotropic inflow-outflow model
期刊论文
OAI收割
CHINESE JOURNAL OF OCEANOLOGY AND LIMNOLOGY, 2015, 卷号: 33, 期号: 1, 页码: 252-261
作者:
Zhang Peijun
;
Wang Qiang
;
Ma Libin
收藏
  |  
浏览/下载:20/0
  |  
提交时间:2015/06/15
Kuroshio large meander
nonlinear perturbation advection
conditional nonlinear optimal perturbation (CNOP)
The analyses of the net primary production due to regional and seasonal temperature differences in eastern China using the LPJ model
期刊论文
OAI收割
ECOLOGICAL MODELLING, 2014, 卷号: 289, 页码: 66-76
作者:
Sun, Guodong
;
Mu, Mu
收藏
  |  
浏览/下载:29/0
  |  
提交时间:2015/06/11
Conditional nonlinear optimal perturbation
CNOP-P
Terrestrial ecosystem
Climate change
Regional and seasonal differences