@Article{BarbosaCAHBVNPP:2017:TsStDi,
author = "Barbosa, C. S. and Caraballo, R. and Alves, Livia Ribeiro and
Hartmann, G. A. and Beggan, C. D. and Viljanen, A. and Ngwira, C.
M. and Papa, A. R. R. and Pirjola, R. J.",
affiliation = "{Observat{\'o}rio Nacional (ON/MCTI)} and {Facultad de
Ingenier{\'{\i}}a (Udelar)} and {Instituto Nacional de Pesquisas
Espaciais (INPE)} and {Universidade Estadual de Campinas
(UNICAMP)} and {British Geological Survey} and {Finnish
Meteorological Institute} and {Catholic University of America} and
{Observat{\'o}rio Nacional (ON/MCTI)} and {Finnish Meteorological
Institute}",
title = "The Tsallis statistical distribution applied to geomagnetically
induced currents",
journal = "Space Weather",
year = "2017",
volume = "15",
number = "9",
pages = "1094--1101",
month = "Sept.",
abstract = "Geomagnetically induced currents (GICs) have been long recognized
as a ground effect arising from a chain of space weather events.
GICs have been measured and modeled in many countries, resulting
in a considerable amount of data. Previous statistical analyses
have proposed various types of distribution functions to fit
long-term GICs data sets. However, these extensive statistical
approaches have been only partially successful in fitting the data
sets. Here we use modeled GICs data sets calculated in four
countries (Brazil, South Africa, United Kingdom, and Finland)
using data from solar cycle 23 to show a plausible function based
on a nonextensive statistical model of the q-exponential Tsallis
function. The fitted q-exponential parameter is approximately the
same for all locations, and the Lilliefors test shows good
agreement with the q-exponential fits. From this fit, we compute
that the likely numbers of extreme GICs events over the next ten
solar cycles are 12 for both Finland and United Kingdom, at least
one for Brazil and less than one event for South Africa. Our
results indicate that the nonextensive statistics are a general
characteristic of GICs, suggesting that the ground current
intensity has a strong temporal correlation and long-range
interaction.",
doi = "10.1002/2017SW001631",
url = "http://dx.doi.org/10.1002/2017SW001631",
issn = "1542-7390",
language = "en",
targetfile = "Barbosa_et_al-2017-Space_Weather.pdf",
urlaccessdate = "19 mar. 2024"
}