Volume 37 Issue 6
Nov.  2017
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Article Navigation >  Chinese Journal of Space Science  > 2017  >  37(6): 690-701
CHEN Kaiwen, LAI Peng, ZHAO Kai, JIANG Yong. Statistical Modeling Research on the Magnetosheath Plasma Density[J]. Chinese Journal of Space Science, 2017, 37(6): 690-701. doi: 10.11728/cjss2017.06.690
Citation: CHEN Kaiwen, LAI Peng, ZHAO Kai, JIANG Yong. Statistical Modeling Research on the Magnetosheath Plasma Density[J]. Chinese Journal of Space Science, 2017, 37(6): 690-701. doi: 10.11728/cjss2017.06.690
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Statistical Modeling Research on the Magnetosheath Plasma Density

doi: 10.11728/cjss2017.06.690

  • 1. School of Mathematics and Statistics, Nanjing University of Information Science and Technology, Nanjing 210044;

  • 2. Institute of Space Weather, Nanjing University of Information Science and Technology, Nanjing 210044

  • Received Date: 2016-11-30
  • Rev Recd Date: 2017-06-20
  • Publish Date: 2017-11-15
    Abstract
  • By using the simulation data of the ideal MHD LFM model, the model of the mean plasma density of the magnetosheath from 03:00UT to 07:00UT on November 14, 2004 is established based on the Sliced Inverse Regression (SIR) and Local Polynomial Regression (LPR) method. The statistical relationship between the mean plasma density and the upstream solar wind parameters, the interplanetary magnetic field, and the geomagnetic disturbance indices are analyzed. The results show that the ionospheric disturbance intensity factor, the solar wind-magnetosphere coupling intensity factor, and the Sun-Earth coupling intensity factor are the three main factors which influence the plasma density of the magnetosheath. The up-flowing ions are the important source for magnetosphere circular current and magnetotail plasma during the recovery phase. The analyses show that, as modeling the process of space physics by the empirical regression method, the multi-collinearity problem usually leads to the poor accuracy of the model. However, the statistical models built by the non-parametric statistical method of SIP and LPR can efficiently solve the problems above.

     

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