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Applied Geophysics

, Volume 16, Issue 2, pp 153–159 | Cite as

Geomagnetic jerk extraction based on the covariance matrix

  • Yan FengEmail author
  • Yun-Shan Jiang
  • Jia-Lin Gu
  • Fan Xu
  • Yi Jiang
  • Shuang Liu
Gravity and Magnetic Exploration Methods

Abstract

We normalize data from 43 Chinese observatories and select data from ten Chinese observatories with most continuous records to assess the secular variations (SVs) and geomagnetic jerks by calculating the deviations between annual observed and CHAOS-6 model monthly means. The variations in the north, east, and vertical eigendirections are studied by using the covariance matrix of the residuals, and we find that the vertical direction is strongly affected by magnetospheric ring currents. To obtain noise-free data, we rely on the covariance matrix of the residuals to remove the noise contributions from the largest eigenvalue or vectors owing to ring currents. Finally, we compare the data from the ten Chinese observatories to seven European observatories. Clearly, the covariance matrix method can simulate the SVs of Dst, the jerk of the northward component in 2014 and that of the eastward component in 2003.5 in China are highly agree with that of Vertically downward component in Europe, compare to CHAOS-6, covariance matrix method can show more details of SVs.

Keywords

Geomagnetic field secular variation covariance matrix jerk CHAOS-6 

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Notes

Acknowledgments

We acknowledge the supports of Institute of Geophysics, Chinese Earthquake Administration, and the State Key Laboratory of Space Weather, Chinese Academy of Sciences. We also thank the reviewers for their valuable advice.

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Copyright information

© The Editorial Department of APPLIED GEOPHYSICS 2018

Authors and Affiliations

  • Yan Feng
    • 1
    • 2
    Email author
  • Yun-Shan Jiang
    • 3
  • Jia-Lin Gu
    • 3
  • Fan Xu
    • 3
  • Yi Jiang
    • 1
  • Shuang Liu
    • 1
  1. 1.The College of Mathematics and StatisticsNanjing University of Information Science & TechnologyNanjingChina
  2. 2.State Key Laboratory of Space WeatherChinese Academy of SciencesBeijingChina
  3. 3.NUIST Reading AcademyNanjingChina

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