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PROBLEMS OF GEOCOSMOS

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Proceedings of the 7th International Conference "Problems of Geocosmos" (St. Petersburg, Russia, 26-30 May 2008)<br />

Introduction<br />

FRACTAL CHARACTERISTICS <strong>OF</strong> ULF EMISSIONS<br />

REGISTERED IN THE HIGH LATITUDE<br />

SEISMIC-QUIET REGION <strong>OF</strong> SPITSBERGEN ISLAND<br />

N.A. Smirnova, A.A. Isavnin<br />

Institute of Physics, St.Petersburg University, St.Petersburg, 198504, Russia, e-mail:<br />

nsmir@geo.phys.spbu.ru<br />

Abstract. ULF frequency range (f = 0.001-5Hz) is now considered as a promising one for manifestation<br />

of electromagnetic earthquake precursors. To support the registration of ULF emissions in seismicactive<br />

areas, and to exclude magnetospheric effects from the lithospheric ones, the reference stations in<br />

seismic quiet but magnetic active regions are required. Here we are starting to analyze the magnetic<br />

field data obtained with high resolution (10 Hz sampling rate) in the high latitude seismic-quiet region<br />

of Spitsbergen Island (Barentsburg station, Φm=76° N; Λm=115°). Fractal analysis of the ULF data has<br />

been fulfilled using Higuchi method and Burlaga-Klein approach. The first preliminary results of the<br />

fractal analysis are presented. Variations of the fractal dimensions of the ULF emissions time series are<br />

considered along the local time. The possible physical interpretation of the results obtained is suggested.<br />

A possibility of using the Barentsburg observatory as a reference station in seismo-electromagnetic<br />

research is discussed.<br />

One the most important tasks in geophysics is the study of precursors of earthquakes. Nowadays it is known that<br />

earthquakes are related to weak seismogenic ULF emissions (see Hayakawa and Fujinawa (eds), 1994). But the<br />

problem of analyzing these signals is that they are strongly screened by ULF emissions of the magnetospheric<br />

origin (Smirnova, 1999). So the analysis may be strict only during the calm “space weather” time. In this work<br />

we are starting to analyze the magnetic field data in the high latitude seismic-quiet region of Spitsbergen Island.<br />

This region is situated at the cusp latitude – the most sensitive area to magnetic field disturbances. Because of its<br />

extremely high sensitivity to the solar wind conditions it can be used as a reference station for the research of<br />

seismogenic electromagnetic emissions.<br />

There is also an important task to monitor the position and size of the cusp area.<br />

Experimental data<br />

In Fig.1 you can see a principle scheme of the magnetosphere of the Earth. There are two cusp areas in the<br />

magnetosphere corresponding to two poles of the dipole field of the Earth. Each of the cusps is situated between<br />

closed and opened magnetic field lines. It is clear that dependent on the solar wind conditions the geographical<br />

position of the station can fall into the zone of opened or closed magnetic field lines. So it is important to learn<br />

out if the station is situated in the cusp during the<br />

analyzed period of time (the magnitude gap of<br />

cusp area is very narrow). For this aim we will<br />

use the Tsyganenko model of magnetosphere to<br />

project the cusp area on the Earth's surface<br />

according to parameters of the solar wind.<br />

Comparing the magnetic field behavior during the<br />

periods when the station falls into the projection<br />

of the cusp area on the Earth's surface with<br />

parameters of solar wind we will exclude the<br />

fluctuations of the magnetic field caused by<br />

inhomogenities in the solar wind. After such<br />

filtering we will obtain the magnetic field data<br />

with most of fluctuations in ULF frequency range<br />

Fig.1. The scheme of the Earth's magnetosphere. One can<br />

see the polar cusps between opened and closed magnetic<br />

field lines (the so-called points of bifurcation).<br />

caused by lithospheric effects, not magnetospheric. Analyzing such “clean” data and confronting it in time with<br />

registered lithospheric events and finding correlation parameters between them could give us some sort of<br />

483

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