Automatic Detection and Classification of Coronal Holes and Filaments Based on EUV and Magnetogram Observations of the Solar Disk

Scholl, Isabelle; Habbal, Shadia Rifai

doi:10.1007/s11207-007-9075-6

Cited by 66 publications

(46 citation statements)

References 21 publications

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“…It is beyond the scope of this paper to perform a very sophisticated region extraction such as those realized by Fuller et al (2005), Ipson et al (2005), Bernasconi et al (2005), Aboudarham et al (2008) or Scholl & Habbal (2008), as their purpose was to identify complete filaments as a whole, with Virtual Observatory applications in mind (building of synoptic maps for example, in which the different pieces constituting a filament must be associated and tracked in time). Here we are mainly interested in the total area covered by these structures at a given time, therefore there is no need to associate them.…”

Section: Discussionmentioning

confidence: 99%

On the correlation between Ca and H$\mathsf{\alpha}$ solar emission and consequences for stellar activity observations

Meunier¹,

Delfosse²

2009

A&A

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Context. The correlation between Ca and Hα chromospheric emission, known to be positive in the solar case, has been found to vary between −1 and 1 for other stars. Aims. Our objective is to understand the factors influencing this correlation in the solar case, and then to extrapolate our interpretation to other stars. Methods. We characterize the correlation between both types of emission in the solar case for different time scales. Then we determine the filling factors due to plages and filaments, and reconstruct the Ca and Hα emission to test different physical conditions in terms of plage and filament contrasts. Results. We have been able to precisely determine the correlation in the solar case as a function of the cycle phase. We interpret the results as reflecting the balance between the emission in plages and the absorption in filaments. We found that correlations close to zero or slightly negative can be obtained when considering the same spatio-temporal distribution of plages and filaments than on the sun but with greater contrast. However, with that assumption, correlations close to −1 cannot be obtained for example. Stars with a very low Hα contrast in plages and filaments well correlated with plages could produce a correlation close to −1. Conclusions. This study opens new ways to study stellar activity, and provides a new diagnosis that will ultimately help to understand the magnetic configuration of stars other than the sun.

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Section: Discussionmentioning

confidence: 99%

On the correlation between Ca and H$\mathsf{\alpha}$ solar emission and consequences for stellar activity observations

Meunier¹,

Delfosse²

2009

A&A

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“…In the early phases of coronal holes identification, CHs were visually tracked by experienced observers (Harvey and Recely, 2002;McIntosh, 2003). Recently, several groups tried to automate the process for the identification and detection of coronal holes using different approaches such as perimeter tracing (Kirk et al, 2009), fuzzy clustering (Barra et al, 2009), multichannel segmentation (Delouille, Barra, and Hochedez, 2007), edge-based segmentation (Scholl and Habbal, 2008), intensity thresholding (Krista and Gallagher, 2009;de Toma, 2011;Rotter et al, 2012) and magnetic track-boundaries (Lowder et al, 2014). One way to model the physical parameters of the solar wind are MHD models of the corona and heliosphere, using synoptic solar magnetic field maps as input, such as ENLIL (Odstrcil and Pizzo, 2009).…”

Section: Introductionmentioning

confidence: 99%

Real-Time Solar Wind Prediction Based on SDO/AIA Coronal Hole Data

et al. 2015

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We present an empirical model based on the visible area covered by coronal holes close to the central meridian in order to predict the solar wind speed at 1 AU with a lead time up to four days in advance with a 1-h time resolution. Linear prediction functions are used to relate coronal hole areas to solar wind speed. The function parameters are automatically adapted by using the information from the previous 3 Carrington Rotations. Thus the algorithm automatically reacts on the changes of the solar wind speed during different phases of the solar cycle. The adaptive algorithm has been applied to and tested on SDO/AIA-193Å observations and ACE measurements during the years 2011 − 2013, covering 41 Carrington Rotations. The solar wind speed arrival time is delayed and needs on average 4.02 ± 0.5 days to reach Earth. The algorithm produces good predictions for the 156 solar wind high speed streams peak amplitudes with correlation coefficients of cc ≈ 0.60. For 80% of the peaks, the predicted arrival matches within a time window of 0.5 days of the ACE in situ measurements. The same algorithm, using linear predictions, was also applied to predict the magnetic field strength from coronal hole areas but did not give reliable predictions (cc ≈ 0.2).

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“…The regions of decreased intensity in the images of the Sun in the EUV wavelength range correspond not only to the regions of CHs, but also include the filament channels (FC). We excluded FCs by analysis of magnetic field distribution in the dimmed regions, which is different in CHs and FCs (Scholl & Habbal, 2008). To separate the CHs from FCs, we consider the data on the radial component of the photospheric magnetic field measured by the Helioseismic and Magnetic Imager on SDO (Hurlburt et al, 2012).…”

Section: Prediction Of Solar Wind Phenomena By the He Modelmentioning

confidence: 99%

Influence of coronal mass ejections on parameters of high-speed solar wind: a case study

Shugay

Slemzin

Rodkin

et al. 2018

J. Space Weather Space Clim.

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-We investigate the case of disagreement between predicted and observed in-situ parameters of the recurrent high-speed solar wind streams (HSSs) existing for Carrington rotation (CR) 2118 (December 2011) in comparison with CRs 2117 and 2119. The HSSs originated at the Sun from a recurrent polar coronal hole (CH) expanding to mid-latitudes, and its area in the central part of the solar disk increased with the rotation number. This part of the CH was responsible for the equatorial flank of the HSS directed to the Earth. The time and speed of arrival for this part of the HSS to the Earth were predicted by the hierarchical empirical model based on EUV-imaging and the Wang-Sheeley-Arge ENLIL semi-empirical model. The predicted parameters were compared with those measured in-situ. It was found, that for CR 2117 and CR 2119, the predicted HSS speed values agreed with the measured ones within the typical accuracy of ±100 km s À1 . During CR 2118, the measured speed was on 217 km s À1 less than the value predicted in accordance with the increased area of the CH. We suppose that at CR 2118, the HSS overtook and interacted with complex ejecta formed from three merged coronal mass ejections (CMEs) with a mean speed about 400 km s À1 . According to simulations of the Drag-based model, this complex ejecta might be created by several CMEs starting from the Sun in the period between 25 and 27 December 2011 and arriving to the Earth simultaneously with the HSS. Due to its higher density and magnetic field strength, the complex ejecta became an obstacle

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Automatic Detection and Classification of Coronal Holes and Filaments Based on EUV and Magnetogram Observations of the Solar Disk

Cited by 66 publications

References 21 publications

On the correlation between Ca and H$\mathsf{\alpha}$ solar emission and consequences for stellar activity observations

On the correlation between Ca and H$\mathsf{\alpha}$ solar emission and consequences for stellar activity observations

Real-Time Solar Wind Prediction Based on SDO/AIA Coronal Hole Data

Influence of coronal mass ejections on parameters of high-speed solar wind: a case study

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