2017
DOI: 10.5194/angeo-35-799-2017
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Automatic detection of Sfe: a proposal

Abstract: Abstract. Solar flare effects (Sfe's) are rapid magnetic variations related to the enhancement of the amount of radiation produced during solar flare events. For several minutes, the ionosphere is activated and electron densities, electrical conductivities and electric currents are enhanced. The magnetic signature of a flare is visible in the illuminated hemisphere, and sometimes it shows up as small crochet-like movements in the magnetograms. However, regarding their detection using an automatized procedure, … Show more

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Cited by 4 publications
(6 citation statements)
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“…The SECS method is postulated as a useful tool for Sfe analysis, and it could be used to obtain complementary data for Sfe detection (Curto et al, ).…”
Section: Discussionmentioning
confidence: 99%
“…The SECS method is postulated as a useful tool for Sfe analysis, and it could be used to obtain complementary data for Sfe detection (Curto et al, ).…”
Section: Discussionmentioning
confidence: 99%
“…Another approach to the Sfe detection problem involves taking advantage of some of the properties of Sfe ionospheric currents, especially their spherical symmetry around the vortex [16]. A first attempt was carried out by Curto et al [5]. Their prototype algorithm calculated the derivative of the data in order to avoid contamination of the daily variation Sq, and, by means of trigonometric formulas, they computed the magnetic radial component.…”
Section: Geometrical Modelmentioning
confidence: 99%
“…First of all, the magnetic data were filtered to avoid contamination of the daily variation Sq because Sfe are high frequency phenomena with respect to Sq. We used the derivative as a high-pass filter, as in Curto et al [5], but in this case it was conducted with intervals of 8 min and not minute by minute, the option that was used in that first prototype. We used 8 min intervals because it was the average time of the Sfe events and the high frequency magnetic noise was better filtered.…”
Section: Geometrical Modelmentioning
confidence: 99%
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