[1] |
YU Liang, MU Mu, Yanshan YU, ,
2014: Role of Parameter Errors in the Spring Predictability Barrier for ENSO Events in the Zebiak-Cane Model, ADVANCES IN ATMOSPHERIC SCIENCES, 31, 647-656.
doi: 10.1007/s00376-013-3058-3
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[2] |
BEI Naifang, Fuqing ZHANG,
2014: Mesoscale Predictability of Moist Baroclinic Waves: Variable and Scale-dependent Error Growth, ADVANCES IN ATMOSPHERIC SCIENCES, 31, 995-1008.
doi: 10.1007/s00376-014-3191-7
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[3] |
MU Mu, DUAN Wansuo, XU Hui, WANG Bo,
2006: Applications of Conditional Nonlinear Optimal Perturbation in Predictability Study and Sensitivity Analysis of Weather and Climate, ADVANCES IN ATMOSPHERIC SCIENCES, 23, 992-1002.
doi: 10.1007/s00376-006-0992-3
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[4] |
WANG Qiang, MU Mu, Henk A. DIJKSTRA,
2012: Application of the Conditional Nonlinear Optimal Perturbation Method to the Predictability Study of the Kuroshio Large Meander, ADVANCES IN ATMOSPHERIC SCIENCES, 29, 118-134.
doi: 10.1007/s00376-011-0199-0
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[5] |
Xiaoran ZHUANG, Jinzhong MIN, Liu ZHANG, Shizhang WANG, Naigeng WU, Haonan ZHU,
2020: Insights into Convective-scale Predictability in East China: Error Growth Dynamics and Associated Impact on Precipitation of Warm-Season Convective Events, ADVANCES IN ATMOSPHERIC SCIENCES, 37, 893-911.
doi: 10.1007/s00376-020-9269-5
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[6] |
ZHU Benlu, LIN Wantao, ZHANG Yun,
2010: Analysis Study on Perturbation Energy and Predictability of Heavy Precipitation in South China, ADVANCES IN ATMOSPHERIC SCIENCES, 27, 382-392.
doi: 10.1007/s00376-009-8164-x
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[7] |
XU Hui, DUAN Wansuo,
2008: What Kind of Initial Errors Cause the Severest Prediction Uncertainty of El Nino in Zebiak-Cane Model, ADVANCES IN ATMOSPHERIC SCIENCES, 25, 577-584.
doi: 10.1007/s00376-008-0577-4
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[8] |
LI Shan, RONG Xingyao, LIU Yun, LIU Zhengyu, Klaus FRAEDRICH,
2013: Dynamic Analogue Initialization for Ensemble Forecasting, ADVANCES IN ATMOSPHERIC SCIENCES, 30, 1406-1420.
doi: 10.1007/s00376-012-2244-z
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[9] |
LIU Jianyong, TAN Zhe-Min,
2009: Mesoscale Predictability of Mei-yu Heavy Rainfall, ADVANCES IN ATMOSPHERIC SCIENCES, 26, 438-450.
doi: 10.1007/s00376-009-0438-9
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[10] |
Jiawei YAO, Wansuo DUAN, Xiaohao QIN,
2021: Which Features of the SST Forcing Error Most Likely Disturb the Simulated Intensity of Tropical Cyclones?, ADVANCES IN ATMOSPHERIC SCIENCES, 38, 581-602.
doi: 10.1007/s00376-020-0073-z
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[11] |
Yujie WU, Wansuo DUAN,
2018: Impact of SST Anomaly Events over the Kuroshio-Oyashio Extension on the "Summer Prediction Barrier", ADVANCES IN ATMOSPHERIC SCIENCES, 35, 397-409.
doi: 10.1007/s00376-017-6322-0
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[12] |
Xia LIU, Qiang WANG, Mu MU,
2018: Optimal Initial Error Growth in the Prediction of the Kuroshio Large Meander Based on a High-resolution Regional Ocean Model, ADVANCES IN ATMOSPHERIC SCIENCES, 35, 1362-1371.
doi: 10.1007/s00376-018-8003-z
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[13] |
Ling-Jiang TAO, Rong-Hua ZHANG, Chuan GAO,
2017: Initial Error-induced Optimal Perturbations in ENSO Predictions, as Derived from an Intermediate Coupled Model, ADVANCES IN ATMOSPHERIC SCIENCES, 34, 791-803.
doi: 10.1007/s00376-017-6266-4
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[14] |
Ben TIAN, Hong-Li REN,
2022: Diagnosing SST Error Growth during ENSO Developing Phase in the BCC_CSM1.1(m) Prediction System, ADVANCES IN ATMOSPHERIC SCIENCES, 39, 427-442.
doi: 10.1007/s00376-021-1189-5
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[15] |
WANG Bo, and HUO Zhenhua,
2013: Extended application of the conditional nonlinear optimal parameter perturbation method in the Common Land Model, ADVANCES IN ATMOSPHERIC SCIENCES, 30, 1213-1223.
doi: 10.1007/s00376-012-2025-8
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[16] |
Chuan GAO, Rong-Hua ZHANG, Xinrong WU, Jichang SUN,
2018: Idealized Experiments for Optimizing Model Parameters Using a 4D-Variational Method in an Intermediate Coupled Model of ENSO, ADVANCES IN ATMOSPHERIC SCIENCES, 35, 410-422.
doi: 10.1007/s00376-017-7109-z
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[17] |
Bin MU, Juhui REN, Shijin YUAN, Rong-Hua ZHANG, Lei CHEN, Chuan GAO,
2019: The Optimal Precursors for ENSO Events Depicted Using the Gradient-definition-based Method in an Intermediate Coupled Model, ADVANCES IN ATMOSPHERIC SCIENCES, 36, 1381-1392.
doi: 10.1007/s00376-019-9040-y
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[18] |
JIANG Zhina,
2006: Applications of Conditional Nonlinear Optimal Perturbation to the Study of the Stability and Sensitivity of the Jovian Atmosphere, ADVANCES IN ATMOSPHERIC SCIENCES, 23, 775-783.
doi: 10.1007/s00376-006-0775-x
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[19] |
SUN Guodong, MU Mu, ZHANG Yale,
2010: Algorithm Studies on How to Obtain a Conditional Nonlinear Optimal Perturbation (CNOP), ADVANCES IN ATMOSPHERIC SCIENCES, 27, 1311-1321.
doi: 10.1007/s00376-010-9088-1
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[20] |
Xing ZHANG, Mu MU, Qiang WANG, Stefano PIERINI,
2017: Optimal Precursors Triggering the Kuroshio Extension State Transition Obtained by the Conditional Nonlinear Optimal Perturbation Approach, ADVANCES IN ATMOSPHERIC SCIENCES, 34, 685-699.
doi: 10.1007/s00376-017-6263-7
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