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Above the Noise: The Search for Periodicities in the Inner Heliosphere

Remote sensing of coronal and heliospheric periodicities can provide vital insight into the local conditions and dynamics of the solar atmosphere. We seek to trace long (one hour or longer) periodic oscillatory signatures (previously identified above the limb in the corona by, e.g., Telloni et al. i...

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Autores principales: Threlfall, James, De Moortel, Ineke, Conlon, Thomas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Netherlands 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6953979/
https://www.ncbi.nlm.nih.gov/pubmed/31983777
http://dx.doi.org/10.1007/s11207-017-1191-3
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author Threlfall, James
De Moortel, Ineke
Conlon, Thomas
author_facet Threlfall, James
De Moortel, Ineke
Conlon, Thomas
author_sort Threlfall, James
collection PubMed
description Remote sensing of coronal and heliospheric periodicities can provide vital insight into the local conditions and dynamics of the solar atmosphere. We seek to trace long (one hour or longer) periodic oscillatory signatures (previously identified above the limb in the corona by, e.g., Telloni et al. in Astrophys. J. 767, 138, 2013) from their origin at the solar surface out into the heliosphere. To do this, we combined on-disk measurements taken by the Atmospheric Imaging Assembly (AIA) onboard the Solar Dynamics Observatory (SDO) and concurrent extreme ultra-violet (EUV) and coronagraph data from one of the Solar Terrestrial Relations Observatory (STEREO) spacecraft to study the evolution of two active regions in the vicinity of an equatorial coronal hole over several days in early 2011. Fourier and wavelet analysis of signals were performed. Applying white-noise-based confidence levels to the power spectra associated with detrended intensity time series yields detections of oscillatory signatures with periods from 6 – 13 hours in both AIA and STEREO data. As was found by Telloni et al. (2013), these signatures are aligned with local magnetic structures. However, typical spectral power densities all vary substantially as a function of period, indicating spectra dominated by red (rather than white) noise. Contrary to the white-noise-based results, applying global confidence levels based on a generic background-noise model (allowing a combination of white noise, red noise, and transients following Auchère et al. in Astrophys. J. 825, 110, 2016) without detrending the time series uncovers only sporadic, spatially uncorrelated evidence of periodic signatures in either instrument. Automating this method to individual pixels in the STEREO/COR coronagraph field of view is non-trivial. Efforts to identify and implement a more robust automatic background noise model fitting procedure are needed.
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spelling pubmed-69539792020-01-23 Above the Noise: The Search for Periodicities in the Inner Heliosphere Threlfall, James De Moortel, Ineke Conlon, Thomas Sol Phys Article Remote sensing of coronal and heliospheric periodicities can provide vital insight into the local conditions and dynamics of the solar atmosphere. We seek to trace long (one hour or longer) periodic oscillatory signatures (previously identified above the limb in the corona by, e.g., Telloni et al. in Astrophys. J. 767, 138, 2013) from their origin at the solar surface out into the heliosphere. To do this, we combined on-disk measurements taken by the Atmospheric Imaging Assembly (AIA) onboard the Solar Dynamics Observatory (SDO) and concurrent extreme ultra-violet (EUV) and coronagraph data from one of the Solar Terrestrial Relations Observatory (STEREO) spacecraft to study the evolution of two active regions in the vicinity of an equatorial coronal hole over several days in early 2011. Fourier and wavelet analysis of signals were performed. Applying white-noise-based confidence levels to the power spectra associated with detrended intensity time series yields detections of oscillatory signatures with periods from 6 – 13 hours in both AIA and STEREO data. As was found by Telloni et al. (2013), these signatures are aligned with local magnetic structures. However, typical spectral power densities all vary substantially as a function of period, indicating spectra dominated by red (rather than white) noise. Contrary to the white-noise-based results, applying global confidence levels based on a generic background-noise model (allowing a combination of white noise, red noise, and transients following Auchère et al. in Astrophys. J. 825, 110, 2016) without detrending the time series uncovers only sporadic, spatially uncorrelated evidence of periodic signatures in either instrument. Automating this method to individual pixels in the STEREO/COR coronagraph field of view is non-trivial. Efforts to identify and implement a more robust automatic background noise model fitting procedure are needed. Springer Netherlands 2017-10-31 2017 /pmc/articles/PMC6953979/ /pubmed/31983777 http://dx.doi.org/10.1007/s11207-017-1191-3 Text en © The Author(s) 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Article
Threlfall, James
De Moortel, Ineke
Conlon, Thomas
Above the Noise: The Search for Periodicities in the Inner Heliosphere
title Above the Noise: The Search for Periodicities in the Inner Heliosphere
title_full Above the Noise: The Search for Periodicities in the Inner Heliosphere
title_fullStr Above the Noise: The Search for Periodicities in the Inner Heliosphere
title_full_unstemmed Above the Noise: The Search for Periodicities in the Inner Heliosphere
title_short Above the Noise: The Search for Periodicities in the Inner Heliosphere
title_sort above the noise: the search for periodicities in the inner heliosphere
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6953979/
https://www.ncbi.nlm.nih.gov/pubmed/31983777
http://dx.doi.org/10.1007/s11207-017-1191-3
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