机构

• 海洋研究所 [36]
• 中国科学院大学 [4]

采集方式

• OAI收割 [36]
• iSwitch采集 [4]

内容类型

• 期刊论文 [22]
• CNKI期刊论文 [18]

发表日期

• 2022 [3]
• 2020 [1]
• 2019 [3]
• 2017 [2]
• 2016 [3]
• 2015 [3]
• 更多

学科主题

• Meteorolog... [8]
• Marine & F... [2]
• Oceanograp... [2]
• Environmen... [1]

筛选

浏览/检索结果: 共40条，第1-10条 帮助 条数/页： 5101520253035404550556065707580859095100 排序方式： 请选择题名升序题名降序提交时间升序提交时间降序作者升序作者降序发表日期升序发表日期降序 Recent Progress in Applications of the Conditional Nonlinear Optimal Perturbation Approach to Atmosphere-Ocean Sciences CNKI期刊论文  OAI收割 2022 作者:  Mu MU;  Kun ZHANG;  Qiang WANG   |  收藏  |  浏览/下载：1/0  |  提交时间：2024/12/18 Conditional nonlinear optimal perturbation  Atmosphere  Ocean  Targeted observation  Predictability   Recent Progress in Applications of the Conditional Nonlinear Optimal Perturbation Approach to Atmosphere-Ocean Sciences 期刊论文  OAI收割 CHINESE ANNALS OF MATHEMATICS SERIES B, 2022, 卷号: 43, 期号: 6, 页码: 1033-1048 作者:  Mu, Mu;  Zhang, Kun;  Wang, Qiang   |  收藏  |  浏览/下载：5/0  |  提交时间：2023/11/16 Conditional nonlinear optimal perturbation  Atmosphere  Ocean  Targeted observation  Predictability   Optimal Precursor Triggering Kuroshio Large Meander Decay Obtained in a Regional Ocean Model 期刊论文  OAI收割 JOURNAL OF GEOPHYSICAL RESEARCH-OCEANS, 2022, 卷号: 127, 期号: 6, 页码: 18 作者:  Liu, Xia;  Wang, Qiang;  Zhang, Hui   |  收藏  |  浏览/下载：48/0  |  提交时间：2022/07/18 predictability  large meander decay  optimal precursor  conditional nonlinear optimal perturbation   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   The Optimal Precursors for ENSO Events Depicted Using the Gradientdefinition-based Method in an Intermediate Coupled Model CNKI期刊论文  OAI收割 2019 作者:  Bin MU;  Juhui REN;  Shijin YUAN;  Rong-Hua ZHANG;  Lei CHEN   |  收藏  |  浏览/下载：2/0  |  提交时间：2024/12/18 optimal precursor  ENSO  gradient-definition-based method  conditional nonlinear optimal perturbation  intermediate coupled model   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   Conditional Nonlinear Optimal Perturbations of Moisture Triggering Primary MJO Initiation 期刊论文  OAI收割 GEOPHYSICAL RESEARCH LETTERS, 2019, 卷号: 46, 期号: 6, 页码: 3492-3501 作者:  Wei, Yuntao;  Mu, Mu;  Ren, Hong-Li;  Fu, Joshua-Xiouhua   |  收藏  |  浏览/下载：49/0  |  提交时间：2019/08/28 Madden-Julian Oscillation  conditional nonlinear optimal perturbation  primary MJO initiation  optimal precursor  nonlinearity   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：5/0  |  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