Michael S. Kirk, K. S. Balasubramaniam, Jason Jackiewicz, R. T. James McAteer
Nov 14, 2014·astro-ph.SR·PDF Chromospheric flare ribbons observed in H-alpha appear well-organized when first examined: ribbons impulsively brighten, morphologically evolve, and exponentially decay back to pre-flare levels. Upon closer inspection of H-alpha flares, there is often a significant number of compact areas brightening in concert with the flare eruption but are spatially separated from the evolving flare ribbon. One class of these brightenings is known as sequential chromospheric brightenings (SCBs). SCBs are often observed in the intimidate vicinity of erupting flares and are associated with coronal mass ejections. In the past decade there have been several previous investigations of SCBs. These studies have exclusively relied upon H-alphaimages to discover and analyze these ephemeral brightenings. This work employs the automated detection algorithm of Kirk et al. (2011) to extract the physical qualities of SCBs in observations of ground-based H-alpha images and complementary AIA images in HeII, Civ, and 1700 Å. The meta-data produced in this tracking process are then culled using complementary Doppler velocities to isolate three distinguishable types of SCBs. From a statistical analysis, we find that the SCBs at the chromospheric H-alpha layer appear earlier, and last longer than their corresponding signatures measured in AIA. From this multi-layer analysis, we infer that SCBs are spatially constrained to the mid-chromosphere. We also derive an energy budget to explain SCBs in which SCBs have a postulated energy of not more than 0.01% of the total flare energy.
Michael S. Kirk, K. S. Balasubramaniam, Jason Jackiewicz, Holly R. Gilbert
Apr 12, 2017·astro-ph.SR·PDF The chromosphere is a complex region that acts as an intermediary between the magnetic flux emergence in the photosphere and the magnetic features seen in the corona. Large eruptions in the chromosphere of flares and filaments are often accompanied by ejections of coronal mass off the sun. Several studies have observed fast-moving progressive trains of compact bright points (called Sequential Chromospheric Brightenings or SCBs) streaming away from chromospheric flares that also produce a coronal mass ejection (CME). In this work, we review studies of SCBs and search for commonalties between them. We place these findings into a larger context with contemporary chromospheric and coronal observations. SCBs are fleeting indicators of the solar atmospheric environment as it existed before their associated eruption. Since they appear at the very outset of a flare eruption, SCBs are good early indication of a CME measured in the chromosphere.
Michael S. Kirk, K. S. Balasubramaniam, Jason Jackiewicz, R. T. James McAteer, Ryan O. Milligan
We report on the physical properties of solar sequential chromospheric brightenings (SCBs) observed in conjunction with moderate-sized chromospheric flares with associated CMEs. To characterize these ephemeral events, we developed automated procedures to identify and track subsections (kernels) of solar flares and associated SCBs using high resolution H-alpha images. Following the algorithmic identification and a statistical analysis, we compare and find the following: SCBs are distinctly different from flare kernels in their temporal characteristics of intensity, Doppler structure, duration, and location properties. We demonstrate that flare ribbons are themselves made up of subsections exhibiting differing characteristics. Flare kernels are measured to have a mean propagation speed of 0.2 km/s and a maximum speed of 2.3 km/s over a mean distance of 5 x 10^3 km. Within the studied population of SCBs, different classes of characteristics are observed with coincident negative, positive, or both negative and positive Doppler shifts of a few km/s. The appearance of SCBs precede peak flare intensity by ~12 minutes and decay ~1 hour later. They are also found to propagate laterally away from flare center in clusters at 41 km/s or 89 km/s. Given SCBs distinctive nature compared to flares, we suggest a different physical mechanism relating to their origin than the associated flare. We present a heuristic model of the origin of SCBs.
Michael S. Kirk, K. S. Balasubramaniam, Jason Jackiewicz, Holly R. Gilbert
Apr 12, 2017·astro-ph.SR·PDF Sequential chromospheric brightenings (SCBs) are often observed in the immediate vicinity of erupting flares and are associated with coronal mass ejections. Since their initial discovery in 2005, there have been several subsequent investigations of SCBs. These studies have used differing detection and analysis techniques, making it difficult to compare results between studies. This work employs the automated detection algorithm of Kirk et al. (Solar Phys. 283, 97, 2013) to extract the physical characteristics of SCBs in 11 flares of varying size and intensity. We demonstrate that the magnetic substructure within the SCB appears to have a significantly smaller area than the corresponding H-alpha emission. We conclude that SCBs originate in the lower corona around 0.1 R_sun above the photosphere, propagate away from the flare center at speeds of 35 - 85 km/s, and have peak photosphere magnetic intensities of 148 +/- 2.9 G. In light of these measurements, we infer SCBs to be distinctive chromospheric signatures of erupting coronal mass ejections.
Jaime A. Landeros, Michael S. Kirk, C. Nick Arge, Laura E. Boucheron, Jie Zhang, Vadim M. Uritsky, Jeremy A. Grajeda, Matthew Dupertuis
Coronal Holes (CHs) are large-scale, low-density regions in the solar atmosphere which may expel high-speed solar wind streams that incite hazardous, geomagnetic storms. Coronal and solar wind models can predict these high-speed streams and the performance of the coronal model can be validated against segmented CH boundaries. We present a novel method named Sub-Transition Region Identification of Ensemble Coronal Holes (STRIDE-CH) to address prominent challenges in segmenting CHs with Extreme Ultraviolet (EUV) imagery. Ground-based, chromospheric He I 10830 Å line imagery and underlying Fe I photospheric magnetograms are revisited to disambiguate CHs from filaments and quiet Sun, overcome obscuration by coronal loops, and complement established methods in the community which use space-borne, coronal EUV observations. Classical computer vision techniques are applied to constrain the radiative and magnetic properties of detected CHs, produce an ensemble of boundaries, and compile these boundaries in a confidence map that quantifies the likelihood of CH presence throughout the solar disk. This method is science-enabling towards future studies of CH formation and variability from a mid-atmospheric perspective.
Michael S. Kirk, K. S. Balasubramaniam, Jason Jackiewicz, R. T. James McAteer, Bernie J. McNamara
We make a comparison between small scale chromospheric brightenings and energy release processes through examining the temporal evolution of sequential chromospheric brightenings (SCBs), derive propagation velocities, and propose a connection of the small-scale features to solar flares. Our automated routine detects and distinguishes three separate types of brightening regularly observed in the chromosphere: plage, flare ribbon, and point brightenings. By studying their distinct dynamics, we separate out the flare-associated bright points commonly known as SCBs and identify a propagating Moreton wave. Superimposing our detections on complementary off-band images, we extract a Doppler velocity measurement beneath the point brightening locations. Using these dynamic measurements, we put forward a connection between point brightenings, the erupting flare, and overarching magnetic loops. A destabilization of the pre-flare loop topology by the erupting flare directly leads to the SCBs observed.
Daniel E. da Silva, Michael Kirk, Nat Mathews, Andrés Muñoz-Jaramillo
In this work, we introduce a novel generative denoising diffusion model for synthesizing the Sun's three-dimensional coronal magnetic field, a complex and dynamic region characterized by evolving magnetic structures. Despite daily variability, these structures exhibit recurring patterns and long-term cyclic trends, presenting unique modeling challenges and opportunities at the intersection of physics and machine learning. Our generative approach employs an innovative architecture influenced by Spherical Fourier Neural Operators (SFNO), operating within the spherical harmonic domain, where the scalar field corresponds directly to the magnetic potential under physical constraints. We trained this model using an extensive dataset comprising 11.7 years of daily coupled simulations from the Air Force Data Assimilative Photospheric Flux Transport-Wang Sheeley Arge (ADAPT-WSA) model, further enhanced by data augmentation. Initial results demonstrate the model's capability to conditionally generate physically realistic magnetic fields reflective of distinct phases within the 11-year solar cycle: from solar minimum ($S = 0$) to solar maximum ($S = 1$). This approach represents a significant step toward advanced generative three-dimensional modeling in Heliophysics, with potential applications in solar forecasting, data assimilation, inverse problem-solving, and broader impacts in areas such as procedural generation of physically-informed graphical assets.
John C. Dorelli, Chris Bard, Thomas Y. Chen, Daniel Da Silva, Luiz Fernando Guides dos Santos, Jack Ireland, Michael Kirk, Ryan McGranaghan, Ayris Narock, Teresa Nieves-Chinchilla, Marilia Samara, Menelaos Sarantos, Pete Schuck, Barbara Thompson
Dec 27, 2022·astro-ph.IM·PDF Traditionally, data analysis and theory have been viewed as separate disciplines, each feeding into fundamentally different types of models. Modern deep learning technology is beginning to unify these two disciplines and will produce a new class of predictively powerful space weather models that combine the physical insights gained by data and theory. We call on NASA to invest in the research and infrastructure necessary for the heliophysics' community to take advantage of these advances.
James Paul Mason, Phillip C. Chamberlin, Thomas N. Woods, Andrew Jones, Astrid M. Veronig, Karin Dissauer, Michael Kirk, SunCET Team
Sep 11, 2020·astro-ph.SR·PDF By 2050, we expect that CME models will accurately describe, and ideally predict, observed solar eruptions and the propagation of the CMEs through the corona. We describe some of the present known unknowns in observations and models that would need to be addressed in order to reach this goal. We also describe how we might prepare for some of the unknown unknowns that will surely become challenges.
James Paul Mason, Phillip C. Chamberlin, Daniel Seaton, Joan Burkepile, Robin Colaninno, Karin Dissauer, Francis G. Eparvier, Yuhong Fan, Sarah Gibson, Andrew R. Jones, Christina Kay, Michael Kirk, Richard Kohnert, W. Dean Pesnell, Barbara J. Thompson, Astrid M. Veronig, Matthew J. West, David Windt, Thomas N. Woods
Jan 22, 2021·astro-ph.SR·PDF The Sun Coronal Ejection Tracker (SunCET) is an extreme ultraviolet imager and spectrograph instrument concept for tracking coronal mass ejections through the region where they experience the majority of their acceleration: the difficult-to-observe middle corona. It contains a wide field of view (0-4~\Rs) imager and a 1~Å spectral-resolution-irradiance spectrograph spanning 170-340~Å. It leverages new detector technology to read out different areas of the detector with different integration times, resulting in what we call "simultaneous high dynamic range", as opposed to the traditional high dynamic range camera technique of subsequent full-frame images that are then combined in post-processing. This allows us to image the bright solar disk with short integration time, the middle corona with a long integration time, and the spectra with their own, independent integration time. Thus, SunCET does not require the use of an opaque or filtered occulter. SunCET is also compact -- $\sim$15 $\times$ 15 $\times$ 10~cm in volume -- making it an ideal instrument for a CubeSat or a small, complementary addition to a larger mission. Indeed, SunCET is presently in a NASA-funded, competitive Phase A as a CubeSat and has also been proposed to NASA as an instrument onboard a 184 kg Mission of Opportunity.
Luiz F. G. dos Santos, Ayris Narock, Teresa Nieves-Chinchilla, Marlon Nuñez, Michael Kirk
Aug 30, 2020·astro-ph.SR·PDF Among the current challenges in Space Weather, one of the main ones is to forecast the internal magnetic configuration within Interplanetary Coronal Mass Ejections (ICMEs). Currently, a monotonic and coherent magnetic configuration observed is associated with the result of a spacecraft crossing a large flux rope with helical magnetic field lines topology. The classification of such an arrangement is essential to predict geomagnetic disturbance. Thus, the classification relies on the assumption that the ICME's internal structure is a well organized magnetic flux rope. This paper applies machine learning and a current physical flux rope analytical model to identify and further understand the internal structures of ICMEs. We trained an image recognition artificial neural network with analytical flux rope data, generated from the range of many possible trajectories within a cylindrical (circular and elliptical cross-section) model. The trained network was then evaluated against the observed ICMEs from WIND during 1995-2015. The methodology developed in this paper can classify 84% of simple real cases correctly and has a 76% success rate when extended to a broader set with 5% noise applied, although it does exhibit a bias in favor of positive flux rope classification. As a first step towards a generalizable classification and parameterization tool, these results show promise. With further tuning and refinement, our model presents a strong potential to evolve into a robust tool for identifying flux rope configurations from in situ data.
M. S. Kirk, K. S. Balasubramaniam, J. Jackiewicz, B. J. McNamara, R. T. J. McAteer
We present a new automated algorithm to identify, track, and characterize small-scale brightening associated with solar eruptive phenomena observed in Hα. The temporal spatially-localized changes in chromospheric intensities can be separated into two categories: flare ribbons and sequential chromospheric brightenings (SCBs). Within each category of brightening we determine the smallest resolvable locus of pixels, a kernel, and track the temporal evolution of the position and intensity of each kernel. This tracking is accomplished by isolating the eruptive features, identifying kernels, and linking detections between frames into trajectories of kernels. We fully characterize the evolving intensity and morphology of the flare ribbons by observing the tracked flare kernels in aggregate. With the location of SCB and flare kernels identified, they can easily be overlaid on top of complementary data sets to extract Doppler velocities and magnetic field intensities underlying the kernels. This algorithm is adaptable to any dataset to identify and track solar features.
The SunPy Community, Stuart J Mumford, Steven Christe, David Pérez-Suárez, Jack Ireland, Albert Y Shih, Andrew R Inglis, Simon Liedtke, Russell J Hewett, Florian Mayer, Keith Hughitt, Nabil Freij, Tomas Meszaros, Samuel M Bennett, Michael Malocha, John Evans, Ankit Agrawal, Andrew J Leonard, Thomas P Robitaille, Benjamin Mampaey, Jose Iván Campos-Rozo, Michael S Kirk
May 11, 2015·astro-ph.IM·PDF This paper presents SunPy (version 0.5), a community-developed Python package for solar physics. Python, a free, cross-platform, general-purpose, high-level programming language, has seen widespread adoption among the scientific community, resulting in the availability of a large number of software packages, from numerical computation (NumPy, SciPy) and machine learning (scikit-learn) to visualisation and plotting (matplotlib). SunPy is a data-analysis environment specialising in providing the software necessary to analyse solar and heliospheric data in Python. SunPy is open-source software (BSD licence) and has an open and transparent development workflow that anyone can contribute to. SunPy provides access to solar data through integration with the Virtual Solar Observatory (VSO), the Heliophysics Event Knowledgebase (HEK), and the HELiophysics Integrated Observatory (HELIO) webservices. It currently supports image data from major solar missions (e.g., SDO, SOHO, STEREO, and IRIS), time-series data from missions such as GOES, SDO/EVE, and PROBA2/LYRA, and radio spectra from e-Callisto and STEREO/SWAVES. We describe SunPy's functionality, provide examples of solar data analysis in SunPy, and show how Python-based solar data-analysis can leverage the many existing tools already available in Python. We discuss the future goals of the project and encourage interested users to become involved in the planning and development of SunPy.
Andrew R. Inglis, Rachel E. O'Connor, W. Dean Pesnell, Michael S. Kirk, Nishu Karna
Small-scale ephemeral coronal holes may be a recurring feature on the solar disk, but have received comparatively little attention. These events are characterized by compact structure and short total lifetimes, substantially less than a solar disk crossing. We present a systematic search for these events, using Atmospheric Imaging Assembly EUV image data from the Solar Dynamics Observatory, covering the time period 2010 - 2015. Following strict criteria, this search yielded four clear examples of the ephemeral coronal hole phenomenon. The properties of each event are characterized, including their total lifetime, growth and decay rates, and areas. The magnetic properties of these events are also determined using Helioseismic and Magnetic Imager data. Based on these four events, ephemeral coronal holes experience rapid initial growth of up to 3000 Mm2/hr, while the decay phases are typically more gradual. Like conventional coronal holes, the mean magnetic field in each ephemeral coronal hole displays a consistent polarity, with mean magnetic flux densities generally < 10 G. No evidence of a corresponding signature is seen in solar wind data at 1 AU. Further study is needed to determine whether ephemeral coronal holes are under-reported events or a truly rare phenomenon.
Jeremy A. Grajeda, Laura E. Boucheron, Michael S. Kirk, Andrew Leisner, C. Nick Arge
Aug 10, 2023·astro-ph.SR·PDF Coronal Holes (CHs) are regions of open magnetic field lines, resulting in high speed solar wind. Accurate detection of CHs is vital for space weather prediction. This paper presents an intramethod ensemble for coronal hole detection based on the Active Contours Without Edges (ACWE) segmentation algorithm. The purpose of this ensemble is to develop a confidence map that defines, for all on disk regions of a Solar extreme ultraviolet (EUV) image, the likelihood that each region belongs to a CH based on that region's proximity to, and homogeneity with, the core of identified CH regions. By relying on region homogeneity, and not intensity (which can vary due to various factors including line of sight changes and stray light from nearby bright regions), to define the final confidence of any given region, this ensemble is able to provide robust, consistent delineations of the CH regions. Using the metrics of global consistency error (GCE), local consistency error (LCE), intersection over union (IOU), and the structural similarity index measure (SSIM), the method is shown to be robust to different spatial resolutions maintaining a median IOU $>0.75$ and minimum SSIM $>0.93$ even when the segmentation process was performed on an EUV image decimated from $4096\times4096$ pixels down to $512\times512$ pixels. Furthermore, using the same metrics, the method is shown to be robust across short timescales, producing segmentation with a mean IOU of 0.826 from EUV images taken at a 1 hour cadence, and showing a smooth decay in similarity across all metrics as a function of time, indicating self-consistent segmentations even when corrections for exposure time have not been applied to the data. Finally, the accuracy of the segmentations and confidence maps are validated by considering the skewness (i.e., unipolarity) of the underlying magnetic field.
Jeremy A. Grajeda, Laura E. Boucheron, Michael S. Kirk, Andrew Leisner, C. Nick Arge, Jaime A. Landeros
Jan 22, 2025·astro-ph.SR·PDF Coronal holes (CHs) are magnetically open regions that allow hot coronal plasma to escape from the Sun and form the high-speed solar wind. This wind can interact with Earth's magnetic field. For this reason, developing an accurate understanding of CH regions is vital for understanding space weather and its effects on Earth. The process of identifying CH regions typically relies on extreme ultraviolet (EUV) imagery, leveraging the fact that CHs appear dark at these wavelengths. Accurate identification of CHs in EUV, however, can be difficult due to a variety of factors, including stray light from nearby regions, limb brightening, and the presence of filaments (which also appear dark, but are not sources of solar wind). In order to overcome these issues, this work incorporates photospheric magnetic field data into a classical EUV-based segmentation algorithm based on the active contours without edges (ACWE) segmentation method. In this work magnetic field data are incorporated directly into the segmentation process, serving both as a method for removing non-CH regions in advance, and as a method to constrain evolution of the segmented CH boundary. This reduces the presence of filaments while allowing the segmentation to include CH regions that may be difficult to identify due to inconsistent intensities.
Michael S. Kirk, W. Dean Pesnell, C. Alex Young, Shea A. Hess Webber
A new method for automated detection of polar coronal holes is presented. This method, called perimeter tracing, uses a series of 171, 195, and 304 Å full disk images from the Extreme ultraviolet Imaging Telescope (EIT) on SOHO over solar cycle 23 to measure the perimeter of polar coronal holes as they appear on the limbs. Perimeter tracing minimizes line-of-sight obscurations caused by the emitting plasma of the various wavelengths by taking measurements at the solar limb. Perimeter tracing also allows for the polar rotation period to emerge organically from the data as 33 days. We have called this the Harvey rotation rate and count Harvey rotations starting 4 January 1900. From the measured perimeter, we are then able to fit a curve to the data and derive an area within the line of best fit. We observe the area of the northern polar hole area in 1996, at the beginning of solar cycle 23, to be about 4.2% of the total solar surface area and about 3.6% in 2007. The area of the southern polar hole is observed to be about 4.0% in 1996 and about 3.4% in 2007. Thus, both the north and south polar hole areas are no more than 15% smaller now than they were at the beginning of cycle 23. This compares to the polar magnetic field measured to be about 40% less now than it was a cycle ago.
David B. Jess, Chris J. Dillon, Michael S. Kirk, Fabio Reale, Mihalis Mathioudakis, Samuel D. T. Grant, Damian J. Christian, Peter H. Keys, S. Krishna Prasad, Scott J. Houston
Dec 17, 2018·astro-ph.SR·PDF Small-scale magnetic reconnection processes, in the form of nanoflares, have become increasingly hypothesized as important mechanisms for the heating of the solar atmosphere, for driving propagating disturbances along magnetic field lines in the Sun's corona, and for instigating rapid jet-like bursts in the chromosphere. Unfortunately, the relatively weak signatures associated with nanoflares places them below the sensitivities of current observational instrumentation. Here, we employ Monte Carlo techniques to synthesize realistic nanoflare intensity time series from a dense grid of power-law indices and decay timescales. Employing statistical techniques, which examine the modeled intensity fluctuations with more than 10^7 discrete measurements, we show how it is possible to extract and quantify nanoflare characteristics throughout the solar atmosphere, even in the presence of significant photon noise. A comparison between the statistical parameters (derived through examination of the associated intensity fluctuation histograms) extracted from the Monte Carlo simulations and SDO/AIA 171Å and 94Å observations of active region NOAA 11366 reveals evidence for a flaring power-law index within the range of 1.82 - 1.90, combined with e-folding timescales of 385 +/- 26 s and 262 +/- 17 s for the SDO/AIA 171Å and 94Å channels, respectively. These results suggest that nanoflare activity is not the dominant heating source for the active region under investigation. This opens the door for future dedicated observational campaigns to not only unequivocally search for the presence of small-scale reconnection in solar and stellar environments, but also quantify key characteristics related to such nanoflare activity.
Peter R. Young, Nicholeen M. Viall, Michael S. Kirk, Emily I. Mason, Lakshmi Pradeep Chitta
The Atmospheric Imaging Assembly (AIA) onboard the Solar Dynamics Observatory (SDO) returns high-resolution images of the solar atmosphere in seven extreme ultraviolet (EUV) wavelength channels. The images are processed on the ground to remove intensity spikes arising from energetic particles hitting the instrument, and the despiked images are provided to the community. In this article a three-hour series of images from the 171 A channel obtained on 28 February 2017 was studied to investigate how often the despiking algorithm gave false positives caused by compact brightenings in the solar atmosphere. The latter were identified through spikes appearing in the same detector pixel for three consecutive frames. 1096 examples were found from the 900 image frames. These "three-spikes" were assigned to 126 dynamic solar features, and it is estimated that the three-spike method identifies 20% of the total number of features affected by despiking. For any ten-minute sequence of AIA 171 A images there are therefore around 35 solar features that have their intensity modified by despiking. The features are found in active regions, quiet Sun, and coronal holes and, in relation to solar surface area, there is a greater proportion within coronal holes. In 96% of the cases, the despiked structure is a compact brightening of size two arcsec or less and the remaining 4% have narrow, elongated structures. By applying an EUV burst detection algorithm, we found that 96% of the events could be classed as EUV bursts. None of the spike events are} rendered invisible by the AIA processing pipeline, but the total intensity over an event's lifetime can be reduced by up to 67%. Users are recommended to always restore the original intensities to AIA data when studying short-lived or rapidly evolving features that exhibit fine-scale structure.
Atefeh Khoshkhahtinat, Ali Zafari, Piyush M. Mehta, Nasser M. Nasrabadi, Barbara J. Thompson, Michael S. F. Kirk, Daniel da Silva
NASA's Solar Dynamics Observatory (SDO) mission collects large data volumes of the Sun's daily activity. Data compression is crucial for space missions to reduce data storage and video bandwidth requirements by eliminating redundancies in the data. In this paper, we present a novel neural Transformer-based video compression approach specifically designed for the SDO images. Our primary objective is to efficiently exploit the temporal and spatial redundancies inherent in solar images to obtain a high compression ratio. Our proposed architecture benefits from a novel Transformer block called Fused Local-aware Window (FLaWin), which incorporates window-based self-attention modules and an efficient fused local-aware feed-forward (FLaFF) network. This architectural design allows us to simultaneously capture short-range and long-range information while facilitating the extraction of rich and diverse contextual representations. Moreover, this design choice results in reduced computational complexity. Experimental results demonstrate the significant contribution of the FLaWin Transformer block to the compression performance, outperforming conventional hand-engineered video codecs such as H.264 and H.265 in terms of rate-distortion trade-off.