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Volume 3 Issue 3

Jul.  1986

Article Contents

THE TRANSITION OF A MULTI-DIMENSIONAL LORENZ SYSTEM


doi: 10.1007/BF02678650

  • A multi-dimensional Lorenz system, which includes thirty-three amplitude equations describing time evolu-tion of convection, is derived from two-dimensional Boussinesq equations by using the Galerkin method. Its transition is studied by numerical solution. It is found that, with Rayleigh number increasing from zero to one hundred, five different types of motion appear one after another as follows: stationary motion, periodic motion, quasiperiodic motion with two-fundamental frequencies, quasi-periodic motion with three fundamental frequencies, and chaotic motion. By comparing with the Lorenz model and Curry's fourteen-dimensional model, it is shown that as retained modes increase, the critical values of transition become larger and the types of bi-furcation change. The results of dynamic behavior happen to be in agreement with the IIIa route of the Gollub and Benson experiments.
  • [1] Gong Jiuding, 1986: APPLICATION OF MULTI-DIMENSIONAL SEQUENCE SIMILARITY METHOD IN METEOROLOGY, ADVANCES IN ATMOSPHERIC SCIENCES, 3, 94-104.  doi: 10.1007/BF02680048
    [2] Ying ZHANG, Kayo IDE, Eugenia KALNAY, 2015: Bred Vectors of the Lorenz63 System, ADVANCES IN ATMOSPHERIC SCIENCES, 32, 1533-1538.  doi: 10.1007/s00376-015-4275-8
    [3] REN Hongli, CHOU Jifan, HUANG Jianping, ZHANG Peiqun, 2009: Theoretical Basis and Application of an Analogue- Dynamical Model in the Lorenz System, ADVANCES IN ATMOSPHERIC SCIENCES, 26, 67-77.  doi: 10.1007/s00376-009-0067-3
    [4] Zou Chengzhi, Yang Peicai, Zhou Xiuji, 1986: THE EFFECT OF ASPECT RATIO ON THE BIFURCATION PROPERTIES OF A DOUBLE PARALLEL-CONNECTION LORENZ SYSTEM, ADVANCES IN ATMOSPHERIC SCIENCES, 3, 406-423.  doi: 10.1007/BF02657931
    [5] Nathan SNOOK, Qinghong ZHANG, 2016: A Four-Dimensional Variational System for Skillful Operational Prediction of Convective Storms, ADVANCES IN ATMOSPHERIC SCIENCES, 33, 1102-1103.  doi: 10.1007/s00376-016-6170-3
    [6] QIN Danyu, LI Bo, and HUANG Yong, 2014: Transition from the Southern Mode of the Mei-yu Front Cloud System to Other Leading Modes, ADVANCES IN ATMOSPHERIC SCIENCES, 31, 948-961.  doi: 10.1007/s00376-013-3045-8
    [7] Hongqin ZHANG, Xiangjun TIAN, Wei CHENG, Lipeng JIANG, 2020: System of Multigrid Nonlinear Least-squares Four-dimensional Variational Data Assimilation for Numerical Weather Prediction (SNAP): System Formulation and Preliminary Evaluation, ADVANCES IN ATMOSPHERIC SCIENCES, 37, 1267-1284.  doi: 10.1007/s00376-020-9252-1
    [8] FANG Xiaoyi, JIANG Weimei, MIAO Shiguang, ZHANG Ning, XU Min, JI Chongping, CHEN Xianyan, WEI Jianmin, WANG Zhihua, WANG Xiaoyun, 2004: The Multi-Scale Numerical Modeling System for Research on the Relationship between Urban Planning and Meteorological Environment, ADVANCES IN ATMOSPHERIC SCIENCES, 21, 103-112.  doi: 10.1007/BF02915684
    [9] ZHANG Hanbin, CHEN Jing, ZHI Xiefei, WANG Yi, WANG Yanan, 2015: Study on Multi-Scale Blending Initial Condition Perturbations for a Regional Ensemble Prediction System, ADVANCES IN ATMOSPHERIC SCIENCES, 32, 1143-1155.  doi: 10.1007/s00376-015-4232-6
    [10] LI Lei, HU Fei, JIANG Jinhua, CHENG Xueling, 2007: An Application of the RAMS/FLUENT System on the Multi-Scale Numerical Simulation of the Urban Surface Layer---A Preliminary Study, ADVANCES IN ATMOSPHERIC SCIENCES, 24, 271-280.  doi: 10.1007/s00376-007-0271-y
    [11] LIU Ye, YAN Changxiang, 2010: Application of a Recursive Filter to a Three-Dimensional Variational Ocean Data Assimilation System, ADVANCES IN ATMOSPHERIC SCIENCES, 27, 293-302.  doi: 10.1007/s00376-009-8112-9
    [12] LIU Juanjuan, WANG Bin, WANG Shudong, 2010: The Structure of Background-error Covariance in a Four-dimensional Variational Data Assimilation System: Single-point Experiment, ADVANCES IN ATMOSPHERIC SCIENCES, 27, 1303-1310.  doi: 10.1007/s00376-010-9067-6
    [13] LIU Juan, WANG Bin, LIU Hailong, YU Yongqiang, 2008: A New Global Four-Dimensional Variational Ocean Data Assimilation System and Its Application, ADVANCES IN ATMOSPHERIC SCIENCES, 25, 680-691.  doi: 10.1007/s00376-008-0680-6
    [14] Peng Yongqing, Zhu Yufeng, Yan Shaojin, 1994: Preliminary Study of Reconstruction of a Dynamic System Using an One-Dimensional Time Series, ADVANCES IN ATMOSPHERIC SCIENCES, 11, 277-284.  doi: 10.1007/BF02658146
    [15] Zou Chengzhi, Zhou Xiuji, Yang Peicai, 1985: THE STATISTICAL STRUCTURE OF LORENZ STRANGE ATTRACTORS, ADVANCES IN ATMOSPHERIC SCIENCES, 2, 215-224.  doi: 10.1007/BF03179753
    [16] Peilong YU, Minghao YANG, Chao ZHANG, Yi LI, Lifeng ZHANG, Shiyao CHEN, 2023: Response of the North Pacific Storm Track Activity in the Cold Season to Multi-scale Oceanic Variations of Kuroshio Extension System: A Statistical Assessment, ADVANCES IN ATMOSPHERIC SCIENCES, 40, 514-530.  doi: 10.1007/s00376-022-2044-z
    [17] Xingchao CHEN, Kun ZHAO, Juanzhen SUN, Bowen ZHOU, Wen-Chau LEE, 2016: Assimilating Surface Observations in a Four-Dimensional Variational Doppler Radar Data Assimilation System to Improve the Analysis and Forecast of a Squall Line Case, ADVANCES IN ATMOSPHERIC SCIENCES, 33, 1106-1119.  doi: 10.1007/s00376-016-5290-0
    [18] DING Ruiqiang, LI Jianping, 2012: Relationships between the Limit of Predictability and Initial Error in the Uncoupled and Coupled Lorenz Models, ADVANCES IN ATMOSPHERIC SCIENCES, 29, 1078-1088.  doi: 10.1007/s00376-012-1207-8
    [19] Qian ZOU, Quanjia ZHONG, Jiangyu MAO, Ruiqiang DING, Deyu LU, Jianping LI, Xuan LI, 2023: Impact of Perturbation Schemes on the Ensemble Prediction in a Coupled Lorenz Model, ADVANCES IN ATMOSPHERIC SCIENCES, 40, 501-513.  doi: 10.1007/s00376-022-1376-z
    [20] Ruiqiang DING, Baojia LIU, Bin GU, Jianping LI, Xuan LI, 2019: Predictability of Ensemble Forecasting Estimated Using the Kullback-Leibler Divergence in the Lorenz Model, ADVANCES IN ATMOSPHERIC SCIENCES, , 837-846.  doi: 10.1007/s00376-019-9034-9

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Manuscript History

Manuscript received: 10 July 1986
Manuscript revised: 10 July 1986
通讯作者: 陈斌, bchen63@163.com
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    沈阳化工大学材料科学与工程学院 沈阳 110142

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THE TRANSITION OF A MULTI-DIMENSIONAL LORENZ SYSTEM

  • 1. Institute of Atmospheric Physics, Academia Sinica, Beijing,Institute of Atmospheric Physics, Academia Sinica, Beijing

Abstract: A multi-dimensional Lorenz system, which includes thirty-three amplitude equations describing time evolu-tion of convection, is derived from two-dimensional Boussinesq equations by using the Galerkin method. Its transition is studied by numerical solution. It is found that, with Rayleigh number increasing from zero to one hundred, five different types of motion appear one after another as follows: stationary motion, periodic motion, quasiperiodic motion with two-fundamental frequencies, quasi-periodic motion with three fundamental frequencies, and chaotic motion. By comparing with the Lorenz model and Curry's fourteen-dimensional model, it is shown that as retained modes increase, the critical values of transition become larger and the types of bi-furcation change. The results of dynamic behavior happen to be in agreement with the IIIa route of the Gollub and Benson experiments.

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