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Annales Geophysicae An interactive open-access journal of the European Geosciences Union
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Volume 34, issue 4
Ann. Geophys., 34, 451–462, 2016
https://doi.org/10.5194/angeo-34-451-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
Ann. Geophys., 34, 451–462, 2016
https://doi.org/10.5194/angeo-34-451-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

Regular paper 19 Apr 2016

Regular paper | 19 Apr 2016

An alternative way to identify local geomagnetically quiet days: a case study using wavelet analysis

Virginia Klausner1,2,3, Andrés Reinaldo Rodriguez Papa3,4, Cláudia Maria Nicole Cândido2, Margarete Oliveira Domingues2, and Odim Mendes2 Virginia Klausner et al.
  • 1Vale do Paraiba University – UNIVAP 12244-000, São José dos Campos, SP, Brazil
  • 2National Institute for Space Research – INPE 12227-010, São José dos Campos, SP, Brazil
  • 3National Observatory – ON 20921-400, Rio de Janeiro, RJ, Brazil
  • 4Rio de Janeiro State University – UERJ 20550-900, Rio de Janeiro, RJ, Brazil

Abstract. This paper proposes a new method to evaluate geomagnetic activity based on wavelet analysis during the solar minimum activity (2007). In order to accomplish this task, a newly developed algorithm called effectiveness wavelet coefficient (EWC) was applied. Furthermore, a comparison between the 5 geomagnetically quiet days determined by the Kp-based method and by wavelet-based method was performed. This paper provides a new insight since the geomagnetic activity indexes are mostly designed to quantify the extent of disturbance rather than the quietness. The results suggest that the EWC can be used as an alternative tool to accurately detect quiet days, and consequently, it can also be used as an alternative to determine the Sq baseline to the current Kp-based 5 quietest days method. Another important aspect of this paper is that most of the quietest local wavelet candidate days occurred in an interval 2 days prior to the high-speed-stream-driven storm events. In other words, the EWC algorithm may potentially be used to detect the quietest magnetic activity that tends to occur just before the arrival of high-speed-stream-driven storms.

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