Principal component analysis of polar cap convection

被引:11
|
作者
Kim, H. -J. [1 ]
Lyons, L. R. [1 ]
Ruohoniemi, J. M. [2 ]
Frissell, N. A. [2 ]
Baker, J. B. [2 ]
机构
[1] Univ Calif Los Angeles, Dept Atmospher & Ocean Sci, Los Angeles, CA 90095 USA
[2] Virginia Polytech & State Univ, Bradley Dept Elect & Comp Engn, Blacksburg, VA USA
基金
美国国家科学基金会;
关键词
FIELD;
D O I
10.1029/2012GL052083
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
We apply a statistical technique called Principal Component Analysis (PCA) for examining underlying patterns of polar cap convection and illustrate potential applications of the PCA-based dimension reduction. Two principal components are identified: the first mode (PC1) is related to "uniform variation" of the flow speed at all MLTs, and is primarily governed by IMF Bz. The second mode (PC2) is related to "dawn-dusk asymmetry", and is predominantly driven by IMF By. PCA gives the relative variance contribution of the two modes: PC1 giving similar to 42% of the total variance and PC2 similar to 17% of the total variance, which is about 40% of that from PC1. Due to the orthogonality of the principal components, the degree of dawn-dusk asymmetry can be represented by P-2, where P-2 is a component value when the observed data are projected along PC2. We identified P2 as proportional to IMF By, which leads to stronger dawn flows for By > 0 and stronger dusk flows for By < 0. The same primary modes are found regardless of the IMF orientation, implying that they are intrinsic properties of the average polar cap convection. Citation: Kim, H.-J., L. R. Lyons, J. M. Ruohoniemi, N. A. Frissell, and J. B. Baker (2012), Principal component analysis of polar cap convection, Geophys. Res. Lett., 39, L11105, doi: 10.1029/2012GL052083.
引用
收藏
页数:5
相关论文
共 50 条
  • [41] New face expression recognition using polar angular radial transform and principal component analysis
    Taleb, Imene
    Mammar, Madani Ould
    Ouamri, Abdelaziz
    INTERNATIONAL JOURNAL OF BIOMETRICS, 2018, 10 (02) : 176 - 194
  • [42] SEPARATION OF POLAR AND ENTHALPIC EFFECTS ON RADICAL-ADDITION REACTIONS USING PRINCIPAL COMPONENT ANALYSIS
    HEBERGER, K
    LOPATA, A
    JOURNAL OF THE CHEMICAL SOCIETY-PERKIN TRANSACTIONS 2, 1995, (01): : 91 - 96
  • [43] Euler Principal Component Analysis
    Liwicki, Stephan
    Tzimiropoulos, Georgios
    Zafeiriou, Stefanos
    Pantic, Maja
    INTERNATIONAL JOURNAL OF COMPUTER VISION, 2013, 101 (03) : 498 - 518
  • [44] Abstract principal component analysis
    Li TianJiang
    Du Qiang
    SCIENCE CHINA-MATHEMATICS, 2013, 56 (12) : 2783 - 2798
  • [45] On Bayesian principal component analysis
    Smidl, Vaclav
    Quinn, Anthony
    COMPUTATIONAL STATISTICS & DATA ANALYSIS, 2007, 51 (09) : 4101 - 4123
  • [46] Directed Principal Component Analysis
    Kao, Yi-Hao
    Van Roy, Benjamin
    OPERATIONS RESEARCH, 2014, 62 (04) : 957 - 972
  • [47] Regularized Principal Component Analysis
    Aflalo, Yonathan
    Kimmel, Ron
    CHINESE ANNALS OF MATHEMATICS SERIES B, 2017, 38 (01) : 1 - 12
  • [48] Principal Volatility Component Analysis
    Hu, Yu-Pin
    Tsay, Ruey S.
    JOURNAL OF BUSINESS & ECONOMIC STATISTICS, 2014, 32 (02) : 153 - 164
  • [49] Multiscale principal component analysis
    Akinduko, A. A.
    Gorban, A. N.
    2ND INTERNATIONAL CONFERENCE ON MATHEMATICAL MODELING IN PHYSICAL SCIENCES 2013 (IC-MSQUARE 2013), 2014, 490
  • [50] Predictive principal component analysis
    Isomura, Takuya
    JOURNAL OF COMPUTATIONAL NEUROSCIENCE, 2021, 49 (SUPPL 1) : S91 - S91