Global Oscillation Network Group Research Articles

Physically Motivated Deep Learning to Superresolve and Cross Calibrate Solar Magnetograms

Superresolution (SR) aims to increase the resolution of images by recovering detail. Compared to standard interpolation, deep learning-based approaches learn features and their relationships to leverage prior knowledge of what low-resolution patterns look like in higher resolution. Deep neural networks can also perform image cross-calibration by learning the systematic properties of the target images. While SR for natural images aims to create perceptually convincing results, SR of scientific data requires careful quantitative evaluation. In this work, we demonstrate that deep learning can increase the resolution and calibrate solar imagers belonging to different instrumental generations. We convert solar magnetic field images taken by the Michelson Doppler Imager (resolution ∼2″ pixel−1; space based) and the Global Oscillation Network Group (resolution ∼2.″5 pixel−1; ground based) to the characteristics of the Helioseismic and Magnetic Imager (resolution ∼0.″5 pixel−1; space based). We also establish a set of performance measurements to benchmark deep-learning-based SR and calibration for scientific applications.

Connection between Subsurface Layers and Surface Magnetic Activity over Multiple Solar Cycles Using GONG Observations

We investigate the spatiotemporal evolution of high-degree acoustic-mode frequencies of the Sun and surface magnetic activity over the course of multiple solar cycles, to improve our understanding of the connection between the solar interior and atmosphere. We focus on high-degree p-modes due to their ability to characterize conditions in the shear layer just below the solar surface, and analyze 22 yr of oscillation frequencies obtained from the Global Oscillation Network Group. Considering 10.7 cm radio flux measurements, the sunspot number, and the local magnetic activity index as solar-activity proxies, we find strong correlation between the mode frequencies and each activity index. We further investigate the hemispheric asymmetry associated with oscillation frequencies and magnetic activity proxies, and find that both were dominant in the southern hemisphere during the descending phase of cycle 23, while in cycle 24 these quantities fluctuated between northern and southern hemispheres. Analyzing the frequencies at different latitudes with the progression of solar cycles, we observe that the variations at midlatitudes were dominant in the southern hemisphere during the maximum-activity period of cycle 24, but the values overlap as the cycle advances toward the minimum phase. The mode frequencies at the beginning of cycle 25 are found to be dominant in the southern hemisphere following the pattern of magnetic activity. The analysis provides added evidence that the variability in oscillation frequencies is caused by both strong and weak magnetic fields.

A Transfer Learning Method to Generate Synthetic Synoptic Magnetograms

AbstractCurrent magnetohydrodynamics (MHD) models largely rely on synoptic magnetograms, such as the ones produced by the Global Oscillation Network Group (GONG). Magnetograms are currently available mostly from the front side of the Sun, which significantly reduces the accuracy of MHD modeling. Extreme Ultraviolet (EUV) images can instead be obtained from other vantage points. To investigate the potential, we explore the possibility of using EUV information from the Atmospheric Imaging Assembly (AIA) to directly generate the input for the state‐of‐the‐art 3D MHD model European Heliospheric FORecasting Information Asset (EUHFORIA). Toward this goal, we develop a method called Transfer‐Solar‐GAN which combines a conditional generative adversarial network with a transfer learning approach to overcome training data set limitations. The source domain data set is constructed from multiple pairs of the central portion of co‐registered AIA and Helioseismic and Magnetic Imager (HMI) line of sight (LOS) full‐disk images, while the target domain is constructed from pairs of portions of AIA and GONG sine‐latitude synoptic maps that we call segments. We evaluate Transfer‐Solar‐GAN by comparing modeled and measured solar wind velocity and magnetic field density parameters at the L1 Lagrange point and along the Parker Solar Probe (PSP) trajectory which were determined with EUHFORIA using both empirical GONG and artificial‐intelligence (AI)‐synthetic synoptic magnetograms as inputs. Our results demonstrate that the Transfer‐Solar‐GAN model can provide the necessary information to run solar physics models by EUV information. Our proposed model is trained with only 528 paired image segments and enforces a reliable data division strategy.

Global solar photospheric and coronal magnetic field over activity cycles 21–25

The evolution of the global solar magnetic field from the beginning of cycle 21 (mid-1970s) until the currently-ascending cycle 25 is described using photospheric full-disk and synoptic magnetograms from NSO Kitt Peak Vacuum Telescope (KPVT) 512-channel and Spectromagnetograph (SPMG) and the Synoptic Optical Long-term Investigation of the Sun (SOLIS) Vector Spectro-Magnetograph (VSM) and Global Oscillations Network Group (GONG), and Stanford University’s Wilcox Solar Observatory (WSO). The evolving strength and symmetry of the global coronal field are described by potential-field source-surface models decomposed into axisymmetric and non-axisymmetric, and even- and odd-ordered magnetic multipoles. The overall weakness of the global solar magnetic field since cycle 23 splits the 50-year observing window into the stronger, simpler, more hemispherically symmetric cycles 21 and 22 and the weaker, more complex cycles 23 and 24. An anomalously large decrease in the global solar field strength occurred during cycles 23, and an anomalously weak axial/polar field resulted from that cycle, accompanied by an anomalously weak radial interplanetary magnetic field (IMF) during cycle 23 activity minimum and a weakened radial IMF overall since cycle 23. The general long-term decline in solar field strength and the development during cycle 24 of strong swings of hemispheric and polar asymmetry are analyzed in detail, including their transfer through global coronal structural changes to dominate mean in situ interplanetary field measurements for several years. Although more symmetric than cycle 24, the rise phase of cycle 25 began with the southern leading the northern hemisphere, but the north has recovered to lead this cycle’s polar field reversal. The mean polar flux (poleward of ±60°) has reversed at each pole, so far more symmetrically than the cycle 23 and 24 polar reversals.

Helioseismic Investigation of Quasi-biennial Oscillation Source Regions

We studied the temporal evolution of quasi-biennial oscillations (QBOs) using acoustic mode oscillation frequencies from the Global Oscillation Network Group. The data used here span more than 25 yr, covering solar cycles 23 and 24 and the ascending phase of cycle 25. The analysis reveals that QBO-like signals are present in both the cycles, but with different periods. The dominant QBO period in cycle 23 is found to be about 2 yr, while it is about 3 yr in cycle 24. Furthermore, the quasi-biennial oscillatory signals are present only during the ascending and high-activity phases of cycle 23 and quickly weaken around 2005, during the declining phase. In comparison, the QBO signals are present throughout cycle 24, starting from 2009 to 2017. We also explored the depth dependence in QBO signals and obtained a close agreement at all depths, except in the near-surface shear layer. A detailed analysis of the near-surface shear layer suggests that the source region of QBOs is probably within a few thousand kilometers just below the surface.

Near-Sun In Situ and Remote-sensing Observations of a Coronal Mass Ejection and its Effect on the Heliospheric Current Sheet

During the thirteenth encounter of the Parker Solar Probe (PSP) mission, the spacecraft traveled through a topologically complex interplanetary coronal mass ejection (ICME) beginning on 2022 September 5. PSP traversed through the flank and wake of the ICME while observing the event for nearly two days. The Solar Probe ANalyzer and FIELDS instruments collected in situ measurements of the plasma particles and magnetic field at ∼13.3 R S from the Sun. We observe classical ICME signatures, such as a fast-forward shock, bidirectional electrons, low proton temperatures, low plasma β, and high alpha particle to proton number density ratios. In addition, PSP traveled through two magnetic inversion lines, a magnetic reconnection exhaust, and multiple sub-Alfvénic regions. We compare these in situ measurements to remote-sensing observations from the Wide-field Imager for Solar PRobe Plus instrument on board PSP and the Sun Earth Connection Coronal and Heliospheric Investigation on the Solar Terrestrial Relations Observatory. Based on white-light coronagraphs, two CMEs are forward modeled to best fit the extent of the event. Furthermore, Air Force Data Assimilative Flux Transport magnetograms modeled from Global Oscillation Network Group magnetograms and Potential Field Source Surface modeling portray a global reconfiguration of the heliospheric current sheet (HCS) after the CME event, suggesting that these eruptions play a significant role in the evolution of the HCS.

Three-dimensional inversion of corona structure and simulation of solar wind parameters based on the photospheric magnetic field deduced from the Global Oscillation Network Group

In this research, the Potential Field Source Surface–Wang–Sheeley–Arge (PFSS–WSA) solar wind model is used. This model consists of the Potential Field Source Surface (PFSS) coronal magnetic field extrapolation module and the Wang–Sheeley–Arge (WSA) solar wind velocity module. PFSS is implemented by the POT3D package deployed on Tianhe 1A supercomputer system. In order to obtain the three–dimensional (3D) distribution of the coronal magnetic field at different source surface radii (Rss), the model utilizes the Global Oscillation Network Group (GONG) photospheric magnetic field profiles for two Carrington rotations (CRs), CR2069 (in 2008) and CR2217 (in 2019), as the input data, with the source surface at Rss = 2Rs, Rss = 2.5Rs and Rss = 3Rs, respectively. Then the solar wind velocity, the coronal magnetic field expansion factor, and the minimum angular distance of the open magnetic field lines from the coronal hole boundary are estimated within the WSA module. The simulated solar wind speed is compared with the value for the corona extrapolated from the data observed near 1 AU, through the calculations of the mean square error (MSE), root mean square error (RMSE) and correlation coefficient (CC). Here we extrapolate the solar wind velocity at 1 AU back to the source surface via the Parker spiral. By comparing the evaluation metrics of the three source surface heights, we concluded that the solar source surface should be properly decreased with respect to Rss = 2.5Rs during the low solar activity phase of solar cycle 23.

Examining the Source Regions of Solar Energetic Particles Using an AI-generated Synchronic Potential Field Source Surface Model

We study the source regions of six solar energetic particle (SEP) events accelerated near or behind the limbs of the Sun. We use AI-generated farside magnetograms at a near real-time basis developed by Jeong et al. and AIHMI-PFSS extrapolations up to 2.5R ⊙ computed using the input of the synchronic data combining AI-generated farside and HMI magnetograms. By comparing the AIHMI, HMI, Global Oscillations Network Group (GONG) synoptic magnetograms, and Air force Data Assimilative Photospheric flux Transport synchronic magnetograms, as well as the PFSS extrapolations, we find interesting differences between them in view of SEP source regions and magnetic field configurations. First, the structures and sizes of the source active regions (ARs) are changed. The total unsigned magnetic field fluxes of the ARs are mostly stronger in the AIHMI than in the HMI and GONG magnetograms. Second, newly emerging ARs are observed in the SEP source regions in the AIHMI magnetograms for two events. Third, the alterations in the magnetic flux, the emergence, and the dissipation of ARs lead to modifications in the locations of the global polarity inversion lines (PILs). The EUV wave propagation is typically observed to be oriented nearly perpendicular with respect to the local PIL, suggesting that the AIHMI-PFSS extrapolations around the source region are more realistic. This study shows that the continuous farside evolution of AR magnetic fields, which is accomplished by our AI synchronic magnetograms, can lead to an improved understanding of SEP source ARs.

Generating Space-based SDO/HMI-like Solar Magnetograms from Ground-based Hα Images by Deep Learning

Recently, the method of estimating magnetic field through monochromatic images by deep learning has been proposed, demonstrating good morphological similarity but somewhat poor magnetic polarity consistency relative to real observation. In this paper, we propose to estimate magnetic field from Hα images by using a conditional generative adversarial network (cGAN) as the basic framework. The Hα images from the Global Oscillation Network Group are used as the inputs and the line-of-sight magnetograms of the Helioseismic Magnetic Imager (HMI) are used as the targets. First, we train a cGAN model (Model A) with shuffling training data. However, the estimated magnetic polarities are not very consistent with real observations. Second, to improve the accuracy of estimated magnetic polarities, we train a cGAN model (Model B) with the chronological Hα and HMI images, which can implicitly exploit the magnetic polarity constraint of time-series observation to generate more accurate magnetic polarities. We compare the generated magnetograms with the target HMI magnetograms to evaluate the two models. It can be observed that Model B has better magnetic polarity consistency than Model A. To quantitatively measure this consistency, we propose a new metric called pixel-to-pixel polarity accuracy (PPA). With respect to PPA, Model B is superior to Model A. This work gives us an insight that the time-series constraint can be implicitly exploited through organizing training data chronologically, and this conclusion also can be applied to other similar tasks related to time-series data.

Why “Solar Tsunamis” Rarely Leave Their Imprints in the Chromosphere

Solar coronal waves frequently appear as bright disturbances that propagate globally from the eruption center in the solar atmosphere, just like the tsunamis in the ocean on Earth. Theoretically, coronal waves can sweep over the underlying chromosphere and leave an imprint in the form of Moreton wave, due to the enhanced pressure beneath their coronal wave front. Despite the frequent observations of coronal waves, their counterparts in the chromosphere are rarely detected. Why the chromosphere rarely bears the imprints of solar tsunamis remained a mystery since their discovery three decades ago. To resolve this question, all coronal waves and associated Moreton waves in the last decade have been initially surveyed, though the detection of Moreton waves could be hampered by utilizing the low-quality Hα data from the Global Oscillations Network Group. Here, we present eight cases (including five in the Appendix) of the coexistence of coronal and Moreton waves in inclined eruptions where it is argued that the extreme inclination is key to providing an answer to address the question. For all these events, the lowest part of the coronal wave front near the solar surface appears very bright, and the simultaneous disturbances in the solar transition region and the chromosphere predominantly occur beneath the bright segment. Therefore, evidenced by observations, we propose a scenario for the excitation mechanism of the coronal-Moreton waves in highly inclined eruptions, in which the lowest part of a coronal wave can effectively disturb the chromosphere even for a weak (e.g., B-class) solar flare.

A Compact Full-disk Solar Magnetograph Based on Miniaturization of the GONG Instrument* *Submitted January XX, 2023.

The design of compact instruments is crucial for the scientific exploration by smaller spacecraft such as CubeSats and deep space missions, as these missions require minimal instrument mass. In this proof-of-concept study, we demonstrate the miniaturization of the Global Oscillation Network Group (GONG) instrument. GONG instruments routinely produce full-disk maps of the Sun’s photosphere using the Ni i 676 nm absorption line, measuring Doppler shifts and magnetic fields. To miniaturize the GONG optical design, we propose replacing the bulky Lyot filter with a narrow-band interference filter. We validate this concept through numerical modeling and proof-of-concept observations. Finally, we propose a simple optical design for building a compact version of GONG.

Formation of an Intermediate Filament Driven by Small-scale Magnetic Reconnection

We present the formation process of a filament in NOAA active region 12765 from 2020 June 5 to 8, using observations from the New Vacuum Solar Telescope, the Solar Dynamics Observatory, and the Global Oscillation Network Group. We found that intermittent small-scale magnetic reconnection occurs at the northern part of the filament, and the small-scale magnetic reconnection shows the characteristics of the oscillatory reconnections. During the magnetic reconnection process, a large amount of material is continuously injected into the filament channel. Furthermore, there are bidirectional inflow and outflow, current sheets, and bright cusp-shaped structures. The velocities of the material injections range from 17 to 183 km s−1 with an average velocity of about 57 km s−1. A total of 53 material injections were found from 03:10 UT on 2020 June 5 to 00:10 UT on June 8. The total mass carried by the injection events is about 7.39 × 1014 g, and the total kinetic energy released through magnetic reconnection is approximately 3.09 × 1021 J. The projection area of the filament increased from less than 1 × 102 Mm2 to around 7 × 102 Mm2. We conclude that the filament is formed by direct material injection into the filament channel due to the small-scale magnetic reconnections.

Precision and systematic errors in global helioseismology mode fitting and inversions: Leveraging some 25 years of nearly uninterrupted observations

We have on hand some 25 years of nearly uninterrupted high-quality and high-cadence global helioseismic data. The Global Oscillations Network Group (GONG) project has been producing science quality data since 1995, the Michelson Doppler Imager (MDI) started in 1996, and the Helioseismic and Magnetic Imager (HMI) took over in 2010. Fundamental new constraints have been imposed by helioseismic inferences, yet global helioseismology data processing seems somewhat frozen in time for some of its methodologies. I review and discuss some specific aspects of global helioseismology data analysis, with an emphasis on the issues and challenges presented by mode fitting and inversion techniques. I compare and contrast results derived by different fitting methods, whether using different techniques, different lengths of time series, or different fitting parameters, like leakage matrices or the inclusion or omission of the mode profile asymmetry, leading to our current best handle on the residual systematic errors.

Radial gradient of the solar rotation rate in the near-surface shear layer of the Sun

We study the radial gradient of the solar rotation rate in the near-surface shear layer (NSSL) from about .950 R⊙ to the solar surface and its variation during Solar Cycles 23 and 24 with ring-diagram analysis applied to Global Oscillation Network Group (GONG) and Helioseismic and Magnetic Imager (HMI) Dopplergrams. The average radial gradient is ∂ log Ω/∂ log r = − 1.0 ± .1 at .990 R⊙ in agreement with previous studies. The average radial gradient is ∂ log Ω/∂ log r = − .11 ± .01 at the base of the NSSL at .950R⊙, while it is steeper than −1 closer to the surface between .990R⊙ and .997R⊙. The average radial gradient is rather flat within ±40° latitude from about .970 R⊙ to the solar surface. The radial gradient of the solar rotation rate varies with the solar cycle. At locations of high magnetic activity, the radial gradient is more negative than average from about .970 R⊙ to .990 R⊙, while in quiet regions the radial gradient is less negative than average at these depths. Close to the surface at .997 R⊙, this relationship appears to be reversed. Prominent features of the solar-cycle variation of large-scale flows, such as poleward branches or precursor flows, are not obviously present. The variation of the radial gradient thus more likely indicates the presence or absence of magnetic flux above a certain threshold. The temporal variations derived from the different HMI and GONG data sets agree within one error bar at most depths and latitudes, while their amplitudes might be different.

Update on Global Helioseismic Observations of the Solar Torsional Oscillation

We present an up-to-date latitude–time map of the solar zonal flows at 0.99 R ⊙ from global helioseismology using data from the Global Oscillation Network Group, the Michelson Doppler Imager, and the Helioseismic and Magnetic Imager.

Deep-learning Reconstruction of Sunspot Vector Magnetic Fields for Forecasting Solar Storms

Solar magnetic activity produces extreme solar flares and coronal mass ejections, which pose grave threats to electronic infrastructure and can significantly disrupt economic activity. It is therefore important to appreciate the triggers of explosive solar activity and develop reliable space weather forecasting. Photospheric vector magnetic field data capture sunspot magnetic field complexity and can therefore improve the quality of space weather prediction. However, state-of-the-art vector field observations are consistently only available from Solar Dynamics Observatory/Helioseismic and Magnetic Imager (HMI) since 2010, with most other current and past missions and observational facilities, such as Global Oscillations Network Group (GONG), only recording line-of-sight (LOS) fields. Here, using an inception-based convolutional neural network (CNN), we reconstruct HMI sunspot vector field features from LOS magnetograms of HMI and GONG with high fidelity (∼90% correlation) and sustained flare forecasting accuracy. We rebuild vector field features during the 2003 Halloween storms, for which only LOS field observations are available, and the CNN-estimated electric current helicity accurately captures the observed rotation of the associated sunspot prior to the extreme flares, showing a striking increase. Our study thus paves the way for reconstructing three solar cycles worth of vector field data from past LOS measurements, which are of great utility in improving space weather forecasting models and gaining new insights about solar activity.

Comparison of Two Methods for Deriving the Magnetic Field in a Filament Channel

Understanding the magnetic structure of filament channels is difficult but essential for identifying the mechanism (s) responsible for solar eruptions. In this paper we characterize the magnetic field in a well-observed filament channel with two independent methods, prominence seismology and magnetohydrodynamics flux-rope modeling, and compare the results. In 2014 May and June, active region 12076 exhibited a complex of filaments undergoing repeated oscillations over the course of 12 days. We measure the oscillation periods in the region with both Global Oscillation Network Group Hα and Solar Dynamics Observatory (SDO) Advanced Imaging Assembly EUV images, and then utilize the pendulum model of large-amplitude longitudinal oscillations to calculate the radius of curvature of the fields supporting the oscillating plasma from the derived periods. We also employ the regularized Biot–Savart laws formalism to construct a flux-rope model of the field of the central filament in the region based on an SDO Helioseismic and Magnetic Imager magnetogram. We compare the estimated radius of curvature, location, and angle of the magnetic field in the plane of the sky derived from the observed oscillations with the corresponding magnetic-field properties extracted from the flux-rope model. We find that the two models are broadly consistent, but detailed comparisons of the model and specific oscillations often differ. Model observation comparisons such as these are important for advancing our understanding of the structure of filament channels.

Sub-surface plasma flows and the flare productivity of solar active regions

The extreme space weather conditions resulting from high energetic events likes solar flares and Coronal Mass Ejections demand for reliable space weather forecasting. The magnetic flux tubes while rising through the convection zone gets twisted by the turbulent plasma flows, energizing the system and resulting in flares. We investigate the relationship between the subsurface plasma flows associated with flaring active regions and their surface magnetic flux and current helicity. The near-surface horizontal velocities derived from the ring-diagram analysis of active region patches using Global Oscillation Network Group Doppler velocity measurements are used to compute the fluid dynamics descriptors like vertical divergence, vorticity and kinetic helicity used in this work. The flaring active regions are observed to have large value of vertical vorticity and kinetic helicity. Also, the horizontal flow divergence, vorticity, flux, kinetic and current helicities are observed to be significantly correlated and evolve in phase with each other. We observe that the integrated values of the above flow and magnetic parameters observed 1 day prior to the flare are significantly correlated with the integrated flare intensity of the active region. Hence, we show that strong vorticity/kinetic helicities lead to larger active region twisting, presumably generating high-intensity flares.

Cycle dependence of a quasi-biennial variability in the solar interior

ABSTRACT We investigated the solar cycle dependence on the presence and periodicity of the Quasi-Biennial Oscillation (QBO). Using helioseismic techniques, we used solar oscillation frequencies from the Global Oscillations Network Group (GONG), Michelson Doppler Imager (MDI), and Helioseismic and Magnetic Imager (HMI) in the intermediate-degree range to investigate the frequency shifts over Cycles 23 and 24. We also examined two solar activity proxies, the F10.7 index and the Mg ii index, for the last four solar cycles to study the associated QBO. The analyses were performed using Empirical Mode Decomposition (EMD) and the Fast Fourier Transform (FFT). We found that the EMD analysis method is susceptible to detecting statistically significant Intrinsic Mode Functions (IMFs) with periodicities that are overtones of the length of the data set under examination. Statistically significant periodicities, which were not due to overtones, were detected in the QBO range. We see a reduced presence of the QBO in Cycle 24 compared to Cycle 23. The presence of the QBO was not sensitive to the depth to which the p-mode travelled, nor the average frequency of the p-mode. The analysis further suggested that the magnetic field responsible for producing the QBO in frequency shifts of p-modes is anchored above approximately 0.95 R⊙.

A Double-decker Filament Formation Driven by Sunspot Rotation and Magnetic Reconnection

In this paper, through analyzing data from the Solar Dynamics Observatory (SDO) and the Global Oscillation Network Group (GONG), we present a study on the formation of a double-decker filament in NOAA Active Region 12665 from 2017 July 8 to 14. We find that magnetic reconnection occurs between two smaller filaments to form a longer filament. According to the evolution of the leading sunspot, it is obvious that the sunspot experiences a continuous rotation around its umbra. During the period from 03:00 UT on July 11 to 10:00 UT on July 14, the average speed of sunspot rotation is about 3.°7 hr–1. The continuous rotation of sunspot stretches the filament and results in the formation of a reversed S-shaped filament. Due to the motion of the magnetic field and internal magnetic reconnection, the filament splits into two branches and forms a double-decker filament structure. In the process of filament separation, internal magnetic reconnection can also accelerate the filament separation. Nonlinear force-free field extrapolation indicates that there are two magnetic flux ropes, which are consistent with the observed results. Eventually, the upper filament erupts and produces an M-class flare and a halo coronal mass ejection.