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Properties and Type of Latitudinal Dependence of Statistical Distribution of Geomagnetic Field Variations

  • Andrei Vorobev
  • Gulnara VorobevaEmail author
Conference paper
Part of the Springer Proceedings in Earth and Environmental Sciences book series (SPEES)

Abstract

Understanding the nature of latitudinal dependence of geomagnetic field (GMF) variations is of quite definite interest in tasks, which are related to assessment of geomagnetic activity. Partly it is related to the fact that according to the type of function, approximating the probability density distribution of geomagnetic variation (GMV) values, it is possible to define the physical mechanism which is determined by geomagnetic variations. Therefore, for example, as a result of observing the sum effect of many random and weakly interdependent values, each of which provides a small contribution to the total sum, a normal distribution is formed; in a closed system, the energy of the system components is distributed according to the exponential law or the Laplace law (i.e., double exponential distribution); a random multiplicative set of several parameters leads to log-normal distribution and etc. In such case, analysis of heavy-tailed distributions is a separate task since the variance of the studied values is predominantly determined by rare intense deviations rather than frequent minor deviations in distributions of such type. Although a number of leading research works provide some data regarding the dependence of GMV parameter values on geographic latitude, but nevertheless it remains unclear when neither an analytical (graphical) form has the dependence, nor the manner in which the probability density function values of GMV change at movement, e.g., from the Poles to Equator. Moreover, it is a common practice for the majority of leading research works to deal with only the mean values of amplitude of GMV, which are specific for the latitudinal range. Relying on these values without understanding the general nature of the distribution can lead to improper conclusions and unauthentic results. Thus, the latitudinal dependence of statistical parameters is studied, the nature of the change of probability density function and distribution law for the northern and eastern components of geomagnetic field vector variations is analysed on the basis of the data obtained from magnetic observatories of the INTREMAGNET network. The observed functional dependencies are approximated, analysed and are illustrated in graphical and analytical form.

Keywords

Geomagnetic field Geomagnetic variations Statistical analysis Latitudinal dependence Geospatial analysis 

References

  1. 1.
    Vorobev, A.V., Pilipenko, V.A., Sakharov, Ya.A., Selivanov, V.N.: Statistical relationships between variations of the geomagnetic field, auroral electrojet, and geomagnetically induced currents. Solar-Terr. Phys. 5(1), 35–42 (2019). (in Russian)Google Scholar
  2. 2.
    Zabolotnaya, N.A.: Geomagnetic Activity Indices. LKI Publishing House, Moscow (2007). (in Russian)Google Scholar
  3. 3.
    Yanovsky, B.M.: Terrestrial Magnetism. Publishing House of the Leningrad State University, Leningrad (1978). (in Russian)Google Scholar
  4. 4.
    Intermagnet technical reference manual. http://intermagnet.org/publications/intermag_4-6.pdf. Accessed 05 Feb 2019
  5. 5.
    Love, J.: An international network of magnetic observatories. EOS Trans. Am. Geophys. Union 94(42), 373–384 (2013)ADSCrossRefGoogle Scholar
  6. 6.
    Nusinov, A.A., Rudneva, N.M., Ginzburg, E.A., et al.: Seasonal variations in statistical distributions of geomagnetic activity indices. Geomag. Aeron. 55(4), 493–498 (2015)CrossRefGoogle Scholar
  7. 7.
    Russel, C.T., McPherron, R.L.: Semiannual variation of geomagnetic activity. J. Geophys. Res. 78(1), 92 (1973)ADSCrossRefGoogle Scholar
  8. 8.
    Vorobev, A.V., Vorobeva, G.R.: Approach to assessment of the relative informational efficiency of intermagnet magnetic observatories. Geomag. Aeron. 58(5), 625–628 (2018)CrossRefGoogle Scholar
  9. 9.
    Magnetic Observatories (IMOs). http://intermagnet.org/imos/magobs-eng.php. Accessed 05 Feb 2019
  10. 10.
    Newell, P.T., Gjerloev, J.W.: Evaluation of SuperMAG auroral electrojet indices as indicators of substorms and auroral power. Magnetos. Phys. 116, A12 (2011)Google Scholar
  11. 11.
    Hinkle, D.E., Wiersma, W., Jurs, S.G.: Applied Statistics for the Behavioral Sciences. Houghton Mifflin, Boston (2003)Google Scholar
  12. 12.
    Sturges, H.: The choice of a class-interval. J. Am. Statist. Assoc. 21, 65–66 (1926)CrossRefGoogle Scholar
  13. 13.
    Bolshev, L.N., Smirnov, N.V.: Tables of Mathematical Statistics. Nauka, Moscow (1983). (in Russian)Google Scholar
  14. 14.
    Gill, P.E., Murray, W., Wright, M.H.: Practical Optimization, Academic Press Inc. (London) Limited (1981)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Geophysical Center of the Russian Academy of SciencesMoscowRussia
  2. 2.Ufa State Aviation Technical UniversityUfaRussia

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