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@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 = "30 nov. 2020"
}


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