Advanced Search
Article Contents

Multi-scale Fractal Characteristics of Atmospheric Boundary-Layer Turbulence

  • The turbulence data are decomposed to multi-scales and its respective fractal dimensions are computed. The conclusions are drawn from investigating the variation of fractal dimensions. With the level of decomposition increasing, the low-frequency part extracted from the turbulence signals tends to be sim ple and smooth, the dimensions decrease; the high-frequency part shows complex, the dimensions are fixed, about 1.70 on the average, which indicates clear serf-similarity characteristics.
  • [1] Zhang Fuqing, Lin Zhenshan, Jiang Quanrong, 1994: The Fractal Dimension Distribution of the Short-Term Climate System in China and It’s Connection with the Monsoon Climate, ADVANCES IN ATMOSPHERIC SCIENCES, 11, 459-462.  doi: 10.1007/BF02658166
    [2] MIAO Yucong, LIU Shuhua, ZHENG Hui, ZHENG Yijia, CHEN Bicheng, WANG Shu, 2014: A Multi-Scale Urban Atmospheric Dispersion Model for Emergency Management, ADVANCES IN ATMOSPHERIC SCIENCES, 31, 1353-1365.  doi: 10.1007/s00376-014-3254-9
    [3] Wen CHEN, Renhe ZHANG, Renguang WU, Zhiping WEN, Liantong ZHOU, Lin WANG, Peng HU, Tianjiao MA, Jinling PIAO, Lei SONG, Zhibiao WANG, Juncong LI, Hainan GONG, Jingliang HUANGFU, Yong LIU, 2023: Recent Advances in Understanding Multi-scale Climate Variability of the Asian Monsoon, ADVANCES IN ATMOSPHERIC SCIENCES, 40, 1429-1456.  doi: 10.1007/s00376-023-2266-8
    [4] YANG Hongping, Jian ZHANG, Carrie LANGSTON, 2009: Synchronization of Radar Observations with Multi-Scale Storm Tracking, ADVANCES IN ATMOSPHERIC SCIENCES, 26, 78-86.  doi: 10.1007/s00376-009-0078-0
    [5] Lin Zhenshan, Zhu Yanyu, Deng Ziwang, 1995: Experiments of Reconstructing Discrete Atmospheric Dynamic Models from Data (I), ADVANCES IN ATMOSPHERIC SCIENCES, 12, 121-125.  doi: 10.1007/BF02661295
    [6] 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
    [7] WANG Gaili, WONG Waikin, LIU Liping, WANG Hongyan, 2013: Application of Multi-Scale Tracking Radar Echoes Scheme in Quantitative Precipitation Nowcasting, ADVANCES IN ATMOSPHERIC SCIENCES, 30, 448-460.  doi: 10.1007/s00376-012-2026-7
    [8] Hengyi WENG, 2012: Impacts of Multi-Scale Solar Activity on Climate. Part I: Atmospheric Circulation Patterns and Climate Extremes, ADVANCES IN ATMOSPHERIC SCIENCES, 29, 867-886.  doi: 10.1007/s00376-012-1238-1
    [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] Yan GAO, Jiali FENG, Xin XIA, Jian SUN, Yulong MA, Dongmei CHEN, Qilin WAN, 2023: Multi-scale Incremental Analysis Update Scheme and Its Application to Typhoon Mangkhut (2018) Prediction, ADVANCES IN ATMOSPHERIC SCIENCES, 40, 95-109.  doi: 10.1007/s00376-022-1425-7
    [11] Yuanwen ZHANG, Guiwan CHEN, Jian LING, Shenming FU, Chongyin LI, 2021: A Case Study on MJO Energy Transport Path in a Local Multi-scale Interaction Framework, ADVANCES IN ATMOSPHERIC SCIENCES, 38, 1929-1944.  doi: 10.1007/s00376-021-1098-7
    [12] ZHANG Zuqiang, ZHANG Renhe, Song YANG, 2007: Roles of Multi-Scale Disturbances over the Tropical North Pacific in the Turnabout of 1997--98 El Nino, ADVANCES IN ATMOSPHERIC SCIENCES, 24, 581-590.  doi: 10.1007/s00376-007-0581-0
    [13] 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
    [14] Zhang Minghua, Zeng Qingcun, 1999: Discrete Spectra and Continuous Spectrum of the Barotropic Quasi-Geostrophic Model-A Calculation of Meteorological Data, ADVANCES IN ATMOSPHERIC SCIENCES, 16, 487-506.  doi: 10.1007/s00376-999-0026-z
    [15] Hengyi WENG, 2012: Impacts of Multi-Scale Solar Activity on Climate. Part II: Dominant Timescales in Decadal-Centennial Climate Variability, ADVANCES IN ATMOSPHERIC SCIENCES, 29, 887-908.  doi: 10.1007/s00376-012-1239-0
    [16] Yujing QIN, Chuhan LU, Liping LI, 2017: Multi-scale Cyclone Activity in the Changjiang River-Huaihe River Valleys during Spring and Its Relationship with Rainfall Anomalies, ADVANCES IN ATMOSPHERIC SCIENCES, 34, 246-257.  doi: 10.1007/s00376-016-6042-x
    [17] 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
    [18] HU Zhiqun, and LIU Liping, 2014: Applications of Wavelet Analysis in Differential Propagation Phase Shift Data De-noising, ADVANCES IN ATMOSPHERIC SCIENCES, 31, 825-835.  doi: 10.1007/s00376-013-3095-y
    [19] Zibo ZHUANG, Kunyun LIN, Hongying ZHANG, Pak-Wai CHAN, 2024: Detection of Turbulence Anomalies Using a Symbolic Classifier Algorithm in Airborne Quick Access Record (QAR) Data Analysis, ADVANCES IN ATMOSPHERIC SCIENCES.  doi: 10.1007/s00376-024-3195-x
    [20] Marco Y. T. LEUNG, Wen ZHOU, Chi-Ming SHUN, Pak-Wai CHAN, 2018: Large-scale Circulation Control of the Occurrence of Low-level Turbulence at Hong Kong International Airport, ADVANCES IN ATMOSPHERIC SCIENCES, 35, 435-444.  doi: 10.1007/s00376-017-7118-y

Get Citation+

Export:  

Share Article

Manuscript History

Manuscript received: 10 September 2001
Manuscript revised: 10 September 2001
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索

Multi-scale Fractal Characteristics of Atmospheric Boundary-Layer Turbulence

  • 1. LAPC, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029,LAPC, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029,LAPC, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029,LAPC, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029

Abstract: The turbulence data are decomposed to multi-scales and its respective fractal dimensions are computed. The conclusions are drawn from investigating the variation of fractal dimensions. With the level of decomposition increasing, the low-frequency part extracted from the turbulence signals tends to be sim ple and smooth, the dimensions decrease; the high-frequency part shows complex, the dimensions are fixed, about 1.70 on the average, which indicates clear serf-similarity characteristics.

Catalog

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return