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Recovering of local magnetic K-indices from global magnetic Kp-indices using neural networks: an application to Antarctica
Author(s) -
Antoni Segarra,
J. J. Curto
Publication year - 2015
Publication title -
annals of geophysics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.394
H-Index - 60
eISSN - 2037-416X
pISSN - 1593-5213
DOI - 10.4401/ag-6719
Subject(s) - earth's magnetic field , index (typography) , artificial neural network , space weather , computer science , meteorology , physics , magnetic field , artificial intelligence , quantum mechanics , world wide web

This paper describes a method to obtain local magnetic index, K, from the global index, Kp. Until now, however, for the cases of areas without magnetic observatories, to estimate the geomagnetic activity there, global indices were the only option. The methodology that we used to estimate local index was based on neural networks. This tool has a great potential for processing information from complex systems as in the case of the geomagnetic system. Local K index calculated with this method resulted to be a better option than directly using the global index Kp when we need an indicator of geomagnetic activity in a specific area. The best results of our method were for moderate and high geomagnetic activity, which are of major interest in Space Weather.

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