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 1 min. 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. Keywords. Magnetospheric physics (storms and substorms)
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