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Segmentation of coronal features to understand the solar EUV and UV irradiance variability

Context. The study of solar irradiance variability is of great importance in heliophysics, the Earth’s climate, and space weather applications. These studies require careful identifying, tracking and monitoring of active regions (ARs), coronal holes (CHs), and the quiet Sun (QS). Aims. We studied th...

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Published in:Astronomy and astrophysics (Berlin) 2014-01, Vol.561, p.np-np
Main Authors: Kumara, S. T., Kariyappa, R., Zender, J. J., Giono, G., Delouille, V., Chitta, L. P., Damé, L., Hochedez, J.-F., Verbeeck, C., Mampaey, B., Doddamani, V. H.
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container_title Astronomy and astrophysics (Berlin)
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creator Kumara, S. T.
Kariyappa, R.
Zender, J. J.
Giono, G.
Delouille, V.
Chitta, L. P.
Damé, L.
Hochedez, J.-F.
Verbeeck, C.
Mampaey, B.
Doddamani, V. H.
description Context. The study of solar irradiance variability is of great importance in heliophysics, the Earth’s climate, and space weather applications. These studies require careful identifying, tracking and monitoring of active regions (ARs), coronal holes (CHs), and the quiet Sun (QS). Aims. We studied the variability of solar irradiance for a period of two years (January 2011–December 2012) using the Large Yield Radiometer (LYRA), the Sun Watcher using APS and image Processing (SWAP) on board PROBA2, and the Atmospheric Imaging Assembly (AIA) on board the Solar Dynamics Observatory (SDO). Methods. We used the spatial possibilistic clustering algorithm (SPoCA) to identify and segment coronal features from the EUV observations of AIA. The AIA segmentation maps were then applied on SWAP images, and parameters such as the intensity, fractional area, and contribution of ARs/CHs/QS features were computed and compared with the full-disk integrated intensity and LYRA irradiance measurements. Results. We report the results obtained from SDO/AIA and PROBA2/SWAP images taken from January 2011 to December 2012 and compare the resulting integrated full-disk intensity with PROBA2/LYRA irradiance. We determine the contributions of the segmented features to EUV and UV irradiance variations. The variations of the parameters resulting from the segmentation, namely the area, integrated intensity, and relative contribution to the solar irradiance, are compared with LYRA irradiance. We find that the active regions have a great impact on the irradiance fluctuations. In the EUV passbands considered in this study, the QS is the greatest contributor to the solar irradiance, with up to 63% of total intensity values. Active regions, on the other hand, contribute to about 10%, and off-limb structures to about 24%. We also find that the area of the features is highly variable suggesting that their area has to be taken into account in irradiance models, in addition to their intensity variations. Conclusions. We successfully show that the feature extraction allows us to use EUV telescopes to measure irradiance fluctuations and to quantify the contribution of each part to the EUV spectral solar irradiance observed with a calibrated radiometer. This study also shows that SPoCA is viable, and that the segmentation of images can be a useful tool. We also provide the measurement correlation between SWAP and AIA during this analysis.
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T. ; Kariyappa, R. ; Zender, J. J. ; Giono, G. ; Delouille, V. ; Chitta, L. P. ; Damé, L. ; Hochedez, J.-F. ; Verbeeck, C. ; Mampaey, B. ; Doddamani, V. H.</creator><creatorcontrib>Kumara, S. T. ; Kariyappa, R. ; Zender, J. J. ; Giono, G. ; Delouille, V. ; Chitta, L. P. ; Damé, L. ; Hochedez, J.-F. ; Verbeeck, C. ; Mampaey, B. ; Doddamani, V. H.</creatorcontrib><description>Context. The study of solar irradiance variability is of great importance in heliophysics, the Earth’s climate, and space weather applications. These studies require careful identifying, tracking and monitoring of active regions (ARs), coronal holes (CHs), and the quiet Sun (QS). Aims. We studied the variability of solar irradiance for a period of two years (January 2011–December 2012) using the Large Yield Radiometer (LYRA), the Sun Watcher using APS and image Processing (SWAP) on board PROBA2, and the Atmospheric Imaging Assembly (AIA) on board the Solar Dynamics Observatory (SDO). Methods. We used the spatial possibilistic clustering algorithm (SPoCA) to identify and segment coronal features from the EUV observations of AIA. The AIA segmentation maps were then applied on SWAP images, and parameters such as the intensity, fractional area, and contribution of ARs/CHs/QS features were computed and compared with the full-disk integrated intensity and LYRA irradiance measurements. Results. We report the results obtained from SDO/AIA and PROBA2/SWAP images taken from January 2011 to December 2012 and compare the resulting integrated full-disk intensity with PROBA2/LYRA irradiance. We determine the contributions of the segmented features to EUV and UV irradiance variations. The variations of the parameters resulting from the segmentation, namely the area, integrated intensity, and relative contribution to the solar irradiance, are compared with LYRA irradiance. We find that the active regions have a great impact on the irradiance fluctuations. In the EUV passbands considered in this study, the QS is the greatest contributor to the solar irradiance, with up to 63% of total intensity values. Active regions, on the other hand, contribute to about 10%, and off-limb structures to about 24%. We also find that the area of the features is highly variable suggesting that their area has to be taken into account in irradiance models, in addition to their intensity variations. Conclusions. We successfully show that the feature extraction allows us to use EUV telescopes to measure irradiance fluctuations and to quantify the contribution of each part to the EUV spectral solar irradiance observed with a calibrated radiometer. This study also shows that SPoCA is viable, and that the segmentation of images can be a useful tool. 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T.</creatorcontrib><creatorcontrib>Kariyappa, R.</creatorcontrib><creatorcontrib>Zender, J. J.</creatorcontrib><creatorcontrib>Giono, G.</creatorcontrib><creatorcontrib>Delouille, V.</creatorcontrib><creatorcontrib>Chitta, L. P.</creatorcontrib><creatorcontrib>Damé, L.</creatorcontrib><creatorcontrib>Hochedez, J.-F.</creatorcontrib><creatorcontrib>Verbeeck, C.</creatorcontrib><creatorcontrib>Mampaey, B.</creatorcontrib><creatorcontrib>Doddamani, V. H.</creatorcontrib><title>Segmentation of coronal features to understand the solar EUV and UV irradiance variability</title><title>Astronomy and astrophysics (Berlin)</title><description>Context. The study of solar irradiance variability is of great importance in heliophysics, the Earth’s climate, and space weather applications. These studies require careful identifying, tracking and monitoring of active regions (ARs), coronal holes (CHs), and the quiet Sun (QS). Aims. 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H.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Segmentation of coronal features to understand the solar EUV and UV irradiance variability</atitle><jtitle>Astronomy and astrophysics (Berlin)</jtitle><date>2014-01-01</date><risdate>2014</risdate><volume>561</volume><spage>np</spage><epage>np</epage><pages>np-np</pages><issn>0004-6361</issn><eissn>1432-0746</eissn><eissn>1432-0756</eissn><abstract>Context. The study of solar irradiance variability is of great importance in heliophysics, the Earth’s climate, and space weather applications. These studies require careful identifying, tracking and monitoring of active regions (ARs), coronal holes (CHs), and the quiet Sun (QS). Aims. We studied the variability of solar irradiance for a period of two years (January 2011–December 2012) using the Large Yield Radiometer (LYRA), the Sun Watcher using APS and image Processing (SWAP) on board PROBA2, and the Atmospheric Imaging Assembly (AIA) on board the Solar Dynamics Observatory (SDO). Methods. We used the spatial possibilistic clustering algorithm (SPoCA) to identify and segment coronal features from the EUV observations of AIA. The AIA segmentation maps were then applied on SWAP images, and parameters such as the intensity, fractional area, and contribution of ARs/CHs/QS features were computed and compared with the full-disk integrated intensity and LYRA irradiance measurements. Results. We report the results obtained from SDO/AIA and PROBA2/SWAP images taken from January 2011 to December 2012 and compare the resulting integrated full-disk intensity with PROBA2/LYRA irradiance. We determine the contributions of the segmented features to EUV and UV irradiance variations. The variations of the parameters resulting from the segmentation, namely the area, integrated intensity, and relative contribution to the solar irradiance, are compared with LYRA irradiance. We find that the active regions have a great impact on the irradiance fluctuations. In the EUV passbands considered in this study, the QS is the greatest contributor to the solar irradiance, with up to 63% of total intensity values. Active regions, on the other hand, contribute to about 10%, and off-limb structures to about 24%. We also find that the area of the features is highly variable suggesting that their area has to be taken into account in irradiance models, in addition to their intensity variations. Conclusions. We successfully show that the feature extraction allows us to use EUV telescopes to measure irradiance fluctuations and to quantify the contribution of each part to the EUV spectral solar irradiance observed with a calibrated radiometer. This study also shows that SPoCA is viable, and that the segmentation of images can be a useful tool. We also provide the measurement correlation between SWAP and AIA during this analysis.</abstract><pub>EDP Sciences</pub><doi>10.1051/0004-6361/201322137</doi><oa>free_for_read</oa></addata></record>
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subjects Astrophysics
Atmospherics
Boards
Irradiance
Radiometers
Sciences of the Universe
Segmentation
Solar and Stellar Astrophysics
Solar observatories
solar-terrestrial relations
Space weather
Sun: activity
Sun: atmosphere
Sun: corona
Sun: evolution
Sun: UV radiation
title Segmentation of coronal features to understand the solar EUV and UV irradiance variability
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