@InProceedings{CaraballoAlveHartBarb:2018:PRCO,
               author = "Caraballo, Ramon and Alves, Livia Ribeiro and Hartmann, G. and 
                         Barbosa, Cleiton",
          affiliation = "{Universidad de la Rep{\'u}blica del Uruguay} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Universidade Estadual 
                         de Campinhas (UNICAMP)} and {Observat{\'o}rio Nacional 
                         (ON/MCTI)}",
                title = "Benchmarking GIC estimates at low latitudes using data by second: 
                         PROS and CONS",
                 year = "2018",
         organization = "Latin American Conference on Space Geophysics, 11. (COLAGE)",
             abstract = "Geomagnetic Induced currents (GIC) are becoming a common subject 
                         of study at low-to-mid latitude around the world. Also, a crescent 
                         observational evidence supporting the existence of significative 
                         GIC estimates or measures on several infrastructures. Several 
                         works have been published in the last four years addressing GIC 
                         modeling or measurements. Mostly of the GIC studies rely on three 
                         key inputs: geomagnetic data, geophysical data and electrical 
                         parameters of the system under study. From this point of view, 
                         geomagnetic data quality is rarely mentioned, maybe by the fact 
                         that the most used geomagnetic data comes in form of oneminute 
                         means. Usually, one-minute means can be obtained by a standard 
                         procedures mainly based on those provided by IAGA for all magnetic 
                         observatories around the world which are part of the INTERMAGNET 
                         network. Despite it is a great advantage to get data from more 
                         than 250 magnetic observatories around the world in a common 
                         format, one-second data it is still scarce and only available from 
                         a reduced number of observatories on South America under request. 
                         Geomagnetic variations at a one-minute sampling period is too slow 
                         to catch the high frequency parts of the geomagnetic spectrum. 
                         When dealing with the geomagnetic variations close to the storm 
                         onset, where sudden impulses are more prone to occur, one-minute 
                         data might not be sufficient faster to take account of the rapid 
                         change in the field components. As a result, the estimated GIC 
                         often underestimates the real one. As the geomagnetic variations 
                         are the first input in any GIC calculations, they exerts a great 
                         leverage on the final results. No matter the averaging method used 
                         to produce one-minute data, they produce a strong smoothing by 
                         filtering much of the rapid time variations on the original 
                         signal. Mostly of the fine grained structures on the magnetograms 
                         are lost in this process leading to a rather flattened version of 
                         the original signal. As the sampling frequency increases the more 
                         detailed structures in the geomagnetic variations leads to more 
                         weird peaks in the calculated GIC. Here, we address this problem 
                         intending to assess the fraction of signal power lost by the use 
                         of one-minute data. The methodology used consisted in assess the 
                         estimated GIC for two specific power grids in Uruguay and Brazil, 
                         respectively, during three major geomagnetic storms of the solar 
                         cycle 24. The GIC calculated using both one-minute and one-second 
                         data respectively, for those power grids was compared to study the 
                         effect in the final estimates. In this case, the round mean square 
                         (rms) of differences and the power spectral density of both 
                         results can provide and outlook of the fraction of energy lost by 
                         the averaging process in the one-minute case. In order to provide 
                         the best estimation possible which result in a valuable tool for 
                         the forecasting GIC events.",
  conference-location = "Buenos Aires, Argentina",
      conference-year = "16-20 abr.",
             language = "en",
        urlaccessdate = "04 jun. 2024"
}