The Inner Coronagraph on Board ADITYA-L1 and Automatic Detection of CMEs

Banerjee, D.; Patel, Ritesh; Pant,; Team, Aditya

doi:10.1017/s1743921317008584

Cited by 9 publications

(9 citation statements)

References 14 publications

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“…Thus the legs can be identified in the K-Cor FOV, while its still not seen in the COR-1 FOV at the same time as shown in Figure 1, but it should also be noted that despite the promising FOV of K-Cor, yet the poor image quality due to challenges faced from being a ground based coronagraph makes it difficult to fit (refer the discussion in Section 2.2. In this regard, the upcoming ADITYA-L1 (Seetha & Megala 2017) mission with the Visible Emission Line Coronagraph (VELC; Prasad et al 2017;Banerjee et al 2017) (FOV : 1.05 -3 R ) on-board and PROBA-3 (Renotte et al 2014) (FOV : 1.02 -3 R ) with the giant Association de Satellites pour l'Imagerie et l'Interferométrie de la Couronne Solaire (ASPIICS; Lamy et al 2017) will provide much better data and hence will help in arriving at much stronger conclusion on the evolution of CME legs. Having said that, it must also be noted that a true estimation of the volume of CME legs require the CME to be seen face-on, as a face-on view will help in identifying the inner edges of the CMEs and hence the volume of their legs.…”

Section: Discussionmentioning

confidence: 99%

On the Variation of Volumetric Evolution of CMEs from Inner to Outer Corona

Majumdar,

Patel,

Pant

2022

Preprint

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Some of the major challenges faced in understanding the early evolution of Coronal Mass Ejections (CMEs) are due to limited observations in the inner corona (< 3 R ) and the plane of sky measurements. In this work, we have thus extended the application of the Graduated Cylindrical Shell (GCS) model to the inner coronal observations from the ground-based coronagraph K-Cor of the Mauna Loa Solar Observatory (MLSO) along with the pair of observations from COR-1 onboard the Solar Terrestrial Relations Observatory (STEREO). We study the rapid initial acceleration and width expansion phase of 5 CMEs in white-light in the lower heights. We also study the evolution of the modelled volume of these CMEs in inner corona and report for the first time, a power law dependence of the CME volume with distance from the Sun. We further find the volume of ellipsoidal leading front and the conical legs follow different power laws, thus indicating differential volume expansion through a CME. The study also reveals two distinct power laws for the total volume evolution of CMEs in the inner and outer corona, thus suggesting different expansion mechanisms at these different heights. These results besides aiding our current understanding on CME evolution, will also provide better constraints to CME initiation and propagation models. Also, since the loss of STEREO-B (and hence COR-1B data) from 2016, this modified GCS model presented here will still enable stereoscopy in the inner corona for the 3D study of CMEs in white-light.

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Section: Discussionmentioning

confidence: 99%

On the Variation of Volumetric Evolution of CMEs from Inner to Outer Corona

Majumdar,

Patel,

Pant

2022

Preprint

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“…The application of the algorithm is not only limited to CMEs, but also to analyse the dynamics of streamers, blobs, current sheets/rays, etc... in this FOV, and long-term coronal studies (Lamy et al, 2020a,b). The recently launched Multi Element Telescope for Imaging and Spectroscopy (METIS) onboard Solar Orbiter (Müller et al, 2020), and future space-based missions including the Visible Emission Line Coronagraph (VELC: Raghavendra Prasad et al, 2017;Banerjee, Patel, and Pant, 2017) onboard Aditya-L1 (Seetha and Megala, 2017), and the Association of Spacecraft for Polarimetric and the Imaging Investigation of the Corona of the Sun (ASPIICS: Renotte et al, 2014) of the Project for Onboard Autonomy-3 (PROBA-3) will also observe the inner corona. The application of SiRGraF on their data will be helpful to bring out processes occurring in the inner corona thereby improving our understanding of the same.…”

Section: Discussionmentioning

confidence: 99%

A Simple Radial Gradient Filter for Batch-Processing of Coronagraph Images

Patel,

Majumdar,

Pant

et al. 2022

Preprint

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Images of the extended solar corona, as observed by white-light coronagraphs as observed by different white-light coronagraphs include the K-and F-corona and suffer from a radial variation in intensity. These images require separation of the two coronal components with some additional image-processing to reduce the intensity gradient and analyse the structures and processes occurring at different heights in the solar corona within the full field of view. Over the past few decades, coronagraphs have been producing enormous amounts of data, which will be continued with the launch of new telescopes. To process these bulk coronagraph images with steep radial-intensity gradients, we have developed an algorithm: Simple Radial Gradient Filter (SiRGraF). This algorithm is based on subtracting a minimum background (F-corona) created using long duration images and then dividing the resultant by a uniform intensity gradient image to enhance the K-corona. We demonstrate the utility of this algorithm to bring out the short time-scale transient structures of the corona. SiRGraF could be used to reveal and analyse such structures. It is not suitable for quantitative estimations based on intensity. We have successfully tested the algorithm on images of the Large Angle Spectroscopic COronagraph (LASCO)-C2 onboard the Solar and Heliospheric Observatory (SOHO), and COR-2A onboard the Solar TErrestrial D. Banerjee

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“…On-board algorithms based on an intensity threshold, using running difference polarized brightness coronagraph images, have been developed for Multi Element Telescope for Imaging and Spectroscopy (METIS) on-board the Solar Orbiter (Bemporad et al, 2014). Visible Emission Line Coronagraph (VELC) on-board ADITYA-L1 (Raghavendra Prasad et al, 2017;Seetha and Megala, 2017) has a simple on-board algorithm for CME detection based on intensity and area threshold (Patel et al, 2018b,a;Banerjee, Patel, and Pant, 2017).…”

Section: Introductionmentioning

confidence: 99%