1. The College of Mathematics and Statistics, Nanjing University of Information Science & Technology, Nanjing 210044,China.
2. State Key Laboratory of Space Weather, Chinese Academy of Sciences, Beijing 100190, China.
3. NUIST Reading Academy, Nanjing 210044, China
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.
This work was supported by the National Natural Science Foundation of China (Grant No. 41404053) and Special Project for Meteo-Scientific Research in the Public Interest (No. GYHY201306073)
Corresponding Authors: Feng Yan (Email: frank_feng8848@163.com)
E-mail: frank_feng8848@163.com
About author: Feng Yan received his B.S. in Computer Science and Technology from Nanjing University in 2006 and his Ph.D. in Soil Science from Nanjing Agricultural University in 2011. He was a visiting scientist at the University of Liverpool in 2016–2017. He is currently an associate professor at the School of Mathematics and Statistics, Nanjing University of Information Science & Technology. His research interests are geomagnetic field modeling and applications.
Cite this article:
. Geomagnetic jerk extraction based on the covariance matrix[J]. APPLIED GEOPHYSICS, 2019, 16(2): 154-160.
2019, Vol. 16 
