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.
Similar content being viewed by others
References
Bloxham, J., and A. Jackson. 1992. Time-dependent mapping of the magnetic field at the core-mantle boundary, J. Geophys. Res., 97(19), 537–19,563.
Brown, W. J., Mound, J.E., Livermore, P.W. 2013. Jerks abound: An analysis of geomagnetic observatory data from 1957 to 2008. Phys. Earth Planet. Inter. 223, 62–76.
Chulliat, A. and Telali, K. 2007. World monthly means database project. Publ. Inst. Geophys. Pol. Acad. Sci. C-99 (398).
Courtillot, V., Ducruix, J., Le Mouël, J. L. 1978. Sur une accélération récente de la variation séculaire du champ magnétique terrestre. C.R. Acad. Sci. Paris. Ser. D. 287, 1095–1098.
Feng, Y., Holme, R., Cox, A. G., et al. 2018. The geomagnetic jerk of 2003.5-characterisation with regional observatory secular variation data. Phys. Earth Planet. Inter. 278, 47–58.
Finlay, C., Olsen, N., Kotsiaros, S., et al. 2016. Recent geomagnetic secular variation from Swarm and ground observatories as estimated in the CHAOS-6 geomagnetic field model. Earth, Planets Space. 68, 1–18.
Holme, R and De Viron, O. 2013. Characterization and implications of intradecadal variations in length of day. Nature. 499(7457):202–204. doi:10.1038/nature12282.
Mandea, M, Holme R, Pais A et al. 2010. Geomagnetic jerks: Rapid core field variations and core dynamics. Space Sci. Rev. 155(1–4):147–175. doi:10.1007/s11214-010-9663-x.
Mursula, K., Holappa, L., Karinen, A. 2008. Correct normalization of the Dst index. Astrophysics Space Sci. Trans. 4, 41–45.
Olsen, N. and Mandea, M. 2007. Investigation of a secular variation impulse using satellite data: The 2003 geomagnetic jerk. Earth Planet Sci. Lett. 255(1–2):94–105. doi:10.1016/j.epsl.2006.12.008.
Pinheiro, K.J., Jackson, A., Finlay, C.C. 2011. Measurements and uncertainties of the occurrence time of the 1969, 1978, 1991, and 1999 geomagnetic jerks. Geochem. Geophys, Geosyst, 12.
Sabaka, T. J., Finlay, C. C., Beggan C. D., et al. 2015. CM5, ia pre-Swarm comprehensive geomagnetic field model derived from over 12 yr of CHAMP, Ørsted, SAC-C and observatory data. Geophys. J. Int. 200, 1596–1626.
Torta, J.M., Pavòn-Carrasco, F.J., Marsal, S. et al. 2015. Evidence for a new geomagnetic jerk in 2014. Geophys. Res. Lett. 42, 7933–7940.
Wardinski, I. and Holme, R. 2006. A time-dependent model of the Earth’s magnetic field and its secular variation for the period 1980–2000. J. Geophys. Res.: Solid. Earth. 111, 1–14.
Wardinski, I. and Holme, R. 2011. Signal from noise in geomagnetic field modelling: Denoising data for secular variation studies. Geophys. J. Int. 185, 653–662.
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.
Author information
Authors and Affiliations
Corresponding author
Additional information
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)
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.
Rights and permissions
About this article
Cite this article
Feng, Y., Jiang, YS., Gu, JL. et al. Geomagnetic jerk extraction based on the covariance matrix. Appl. Geophys. 16, 153–159 (2019). https://doi.org/10.1007/s11770-019-0761-6
Received:
Revised:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11770-019-0761-6