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Annales Geophysicae An interactive open-access journal of the European Geosciences Union
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Volume 36, issue 5
Ann. Geophys., 36, 1207-1225, 2018
https://doi.org/10.5194/angeo-36-1207-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Ann. Geophys., 36, 1207-1225, 2018
https://doi.org/10.5194/angeo-36-1207-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Regular paper 19 Sep 2018

Regular paper | 19 Sep 2018

Multiscale variation model and activity level estimation algorithm of the Earth's magnetic field based on wavelet packets

Oksana V. Mandrikova1,2, Igor S. Solovyev1,2, Sergey Y. Khomutov3, Vladimir V. Geppener4, Dmitry M. Klionskiy4, and Mikhail I. Bogachev5 Oksana V. Mandrikova et al.
  • 1Laboratory of System Analysis (LSA), Institute of Cosmophysical Research and Radio Wave Propagation, Far Eastern Branch of the Russian Academy of Sciences, Paratunka, Kamchatka region, Russian Federation
  • 2Kamchatka State Technical University, Petropavlovsk-Kamchatsky, Russian Federation
  • 3Geophysical Observatory, Institute of Cosmophysical Research and Radio Wave Propagation, Far Eastern Branch of the Russian Academy of Sciences, Paratunka, Kamchatka region, Russian Federation
  • 4Computer Science Department, Saint Petersburg Electrotechnical University “LETI”, Saint Petersburg, Russian Federation
  • 5Department of Radio Engineering, Saint Petersburg Electrotechnical University “LETI”, Saint Petersburg, Russian Federation

Abstract. We suggest a wavelet-based multiscale mathematical model of geomagnetic field variations. The model is particularly capable of reflecting the characteristic variation and local perturbations in the geomagnetic field during the periods of increased geomagnetic activity. Based on the model, we have designed numerical algorithms to identify the characteristic variation component as well as other components that represent different geomagnetic field activity. The substantial advantage of the designed algorithms is their fully automatic performance without any manual control. The algorithms are also suited for estimating and monitoring the activity level of the geomagnetic field at different magnetic observatories without any specific adjustment to their particular locations. The suggested approach has high temporal resolution reaching 1min. This allows us to study the dynamics and spatiotemporal distribution of geomagnetic perturbations using data from ground-based observatories. Moreover, the suggested approach is particularly capable of discovering weak perturbations in the geomagnetic field, likely linked to the nonstationary impact of the solar wind plasma on the magnetosphere. The algorithms have been validated using the experimental data collected at the IKIR FEB RAS observatory network.

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Data analysis of the geomagnetic field is needed for space weather prediction. Conventional techniques do not always provide sufficient efficiency. We suggest new techniques for processing and analyzing geomagnetic data based on the wavelet transform for studying the dynamics and spatiotemporal distribution of geomagnetic perturbations. The paper discusses prestorm short-term increases of geomagnetic activity and the features of different magnetospheric processes for increased solar activity.
Data analysis of the geomagnetic field is needed for space weather prediction. Conventional...
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