Articles | Volume 36, issue 1
https://doi.org/10.5194/angeo-36-205-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/angeo-36-205-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Cross-correlation and cross-wavelet analyses of the solar wind IMF Bz and auroral electrojet index AE coupling during HILDCAAs
Adriane Marques de Souza
CORRESPONDING AUTHOR
National Institute for Space Research (INPE), São José dos Campos, Brazil
Ezequiel Echer
National Institute for Space Research (INPE), São José dos Campos, Brazil
Mauricio José Alves Bolzan
Federal University of Jataí, Jataí, Brazil
Rajkumar Hajra
Laboratoire de Physique et Chimie de l'Environnement et de l'Espace, CNRS, Orléans, France
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We used up-to-date substorms, HILDCAAs and geomagnetic storms of varying intensity along with all available geomagnetic indices during the space exploration era to explore the seasonal features of the geomagnetic activity and their drivers. As substorms, HILDCAAs and magnetic storms of varying intensity have varying solar/interplanetary drivers, such a study is important for acomplete understanding of the seasonal features of the geomagnetic response to the solar/interplanetary events.
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The wavelet transform was employed in nine HILDCAA events for intervals in which the Cluster crossed the magnetotail in order to identify the most energetic periods of these events in the magnetotail. It was seen that 76 % of the periods identified are ≤4 h. Using the cross wavelet analysis technique between Bz–IMF components and the Bx geomagnetic components, it was identified that the coupling of energy is stronger in periods between 2 and 4 h, which are typical substorm periods.
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On February 03, 2022, SpaceX launched a new group of satellites for its Starlink constellation. This launch simultaneously released 49 satellites in orbits between 200 km and 250 km height. The launches occurred during a geomagnetic storm, followed by a second one. There was an immediate loss of 32 satellites. The satellite losses may have been caused by an unusually high level of atmospheric drag (unexplained by current theory/modeling) or a high level of satellite collisions.
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Ann. Geophys., 39, 929–943, https://doi.org/10.5194/angeo-39-929-2021, https://doi.org/10.5194/angeo-39-929-2021, 2021
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We used up-to-date substorms, HILDCAAs and geomagnetic storms of varying intensity along with all available geomagnetic indices during the space exploration era to explore the seasonal features of the geomagnetic activity and their drivers. As substorms, HILDCAAs and magnetic storms of varying intensity have varying solar/interplanetary drivers, such a study is important for acomplete understanding of the seasonal features of the geomagnetic response to the solar/interplanetary events.
Adriane Marques de Souza Franco, Ezequiel Echer, and Mauricio José Alves Bolzan
Ann. Geophys., 37, 919–929, https://doi.org/10.5194/angeo-37-919-2019, https://doi.org/10.5194/angeo-37-919-2019, 2019
Short summary
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The wavelet transform was employed in nine HILDCAA events for intervals in which the Cluster crossed the magnetotail in order to identify the most energetic periods of these events in the magnetotail. It was seen that 76 % of the periods identified are ≤4 h. Using the cross wavelet analysis technique between Bz–IMF components and the Bx geomagnetic components, it was identified that the coupling of energy is stronger in periods between 2 and 4 h, which are typical substorm periods.
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Cross-wavelet and classical cross-correlation analyses were used in order to study solar-wind–magnetosphere coupling during HILDCAAs. Cross-correlation analyses results show that the coupling between the solar wind and the magnetosphere during HILDCAAs occurs mainly in the period ≤ 8 h. Classical correlation analysis indicates that the correlation between IMF Bz and AE may be classified as moderate (0.4–0.7) and that more than 80 % of the HILDCAAs exhibit a lag of 20–30 min.
Cross-wavelet and classical cross-correlation analyses were used in order to study...
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