Time–distance helioseismology uses solar surface Doppler observations to measure areas that are not directly observable, such as solar interior, far side, and sunquake sources. In this work, we briefly review recent advancements in time–distance helioseismology, focusing on meridional circulation measurements, far-side imaging, and sunquakes. Solar deep meridional flows are crucial for understanding the dynamics of the solar interior, but precise measurements of these flows are challenging. This review explores recent developments in this area, particularly highlighting new findings related to systematic effects that have long challenged meridional circulation determination. We also review recent progress in solar far-side imaging, which is useful in improving space weather forecasting. Recent developments in far-side imaging using time–distance techniques and Deep Learning are introduced. Additionally, we review a new approach in sunquake reconstruction by incorporating observation-based Green’s functions constructed by time–distance helioseismology.

Active regions (ARs) appear in the solar atmosphere as a consequence of the emergence of magnetic flux ropes (FRs). Due to the presence of twist, the photospheric line-of-sight (LOS) magnetograms of emerging ARs show an elongation of the polarities known as magnetic tongues. These tongues can affect the estimation of tilt angles during their emergence phase. In this work, we propose a Bayesian method to model LOS magnetograms of emerging ARs using a half-torus twisted FR model. We apply this model to 21 emerging ARs observed during Solar Cycle 23. We find that the Bayesian method corrects the tilt when compared to other methods, removing the spurious rotation of the polarities produced by the retraction of the tongues during the emergence. We find a variation in Joy’s law with the stage of the AR emergence and the method used for its estimation.

Low-lying loops in the quiet Sun are a reliable source of energy for atmospheric heating, but the mechanisms by which they evolve are somewhat enigmatic. To address the origins of atmospheric heating events in the quiet Sun, we utilize our stratified, convection-driven, 3D MHD simulation Bifrost to explore the evolution and eventual major reconnection between several magnetic features; one of which is a magnetic flux rope. We zoom in on the buildup of the magnetic flux rope, which self-orders in the corona via an inverse cascade of helicity. We also discover that the flux rope attempts to relax to a linear force-free field according to Taylor’s theory, but cannot do so completely. Finally, we demonstrate that the eventual nanoflare-scale reconnection event could potentially be observed in the 171 Å channels of SDO/AIA and the future MUSE mission. We also determine that the spectral resolution of MUSE is sensitive enough to capture the kinematics of the bi-directional plasma jets emanating from the reconnection region.

We investigate the evolution of subsurface flows during the emergence and the active phase of sunspot regions using the time–distance helioseismology analysis of the full-disk Dopplergrams from the Helioseismic and Magnetic Imager (HMI) onboard the Solar Dynamics Observatory (SDO). We present an analysis of emerging active regions of various types, including delta-type active regions and regions with the reverse polarity order (‘anti-Hale active regions’). The results reveal strong vortical and shearing flows during the emergence of magnetic flux, as well as the process of formation of large-scale converging flow patterns around developing active regions, predominantly in the top 6 Mm deep layers of the convection zone. Our analysis revealed a significant correlation between the flow divergence and helicity in the active regions with their flaring activity, indicating that measuring characteristics of subsurface flows can contribute to flare forecasting.

We develop an adaptive method to automatically identify ARs from radial synoptic maps observed by SOHO/MDI and SDO/HMI, calibrate the detections between HMI and MDI data based on identified ARs flux and area and further derive a homogeneous dataset including ARs’ area and flux over the last two solar cycles. The data are compared with sunspot number, USAF/NOAA sunspot area, SMARPs and SHARPs and BARD area and flux, which show reasonable agreement. The identified ARs during the overlap period of MDI and HMI have the same areas as a whole while the AR flux based on MDI maps is about 1.36 times as large as that of HMI maps. Based on our dataset, we find strong ARs (|flux| > 1022Mx) contribute most to the difference between cycles 23 and 24 while other ARs (|flux| < 1022Mx) are similar in the two cycles in both area and flux.

MHD avalanches involve small, narrowly localized instabilities spreading across neighbouring areas in a magnetic field. Cumulatively, many small events release vast amounts of stored energy. Straight cylindrical flux tubes are easily modelled, between two parallel planes, and can support such an avalanche: one unstable flux tube causes instability to proliferate, via magnetic reconnection, and then an ongoing chain of like events. True coronal loops, however, are visibly curved, between footpoints on the same solar surface. With 3D MHD simulations, we verify the viability of MHD avalanches in the more physically realistic, curved geometry of a coronal arcade. MHD avalanches thus amplify instability across strong solar magnetic fields and disturb wide regions of plasma. Contrasting with the behaviour of straight cylindrical models, a modified ideal MHD kink mode occurs, more readily and preferentially upwards in the new, curved geometry. Instability spreads over a region far wider than the original flux tubes and than their footpoints. Consequently, sustained heating is produced in a series of ‘nanoflares’ collectively contributing substantially to coronal heating. Overwhelmingly, viscous heating dominates, generated in shocks and jets produced by individual small events. Reconnection is not the greatest contributor to heating, but is rather the facilitator of those processes that are. Localized and impulsive, heating shows no strong spatial preference, except a modest bias away from footpoints, towards the loop’s apex. Remarkable evidence emerges of ‘campfire’ like events, with simultaneous, reconnection-induced nanoflares at separate sites along coronal strands, akin to recent results from Solar Orbiter. Effects of physically realistic plasma parameters, and the implications for thermodynamic models, with energetic transport, are discussed.

We carry out the first statistical study that investigates the flare-coronal mass ejections (CMEs) association rate as function of the flare intensity and the total unsigned magnetic flux (ΦAR) of ARs that produces the flare. Our results show that flares of the same GOES class but originating from an AR of larger ΦAR, are much more likely confined. This implies that ΦAR is a decisive quantity describing the eruptive character of a flare, as it provides a global parameter relating to the strength of the background field confinement. We also calculated the mean twist values α in regions close to the polarity inversion line and proposed a new parameter α / ΦAR to measure the probability for a large flare to be associated with a CME. We find that the new parameter α/ ΦAR is well able to distinguish eruptive flares from confined flares.

In this review, we introduce our recent applications of deep learning to solar and space weather data. We have successfully applied novel deep learning methods to the following applications: (1) generation of solar farside/backside magnetograms and global field extrapolation based on them, (2) generation of solar UV/EUV images from other UV/EUV images and magnetograms, (3) denoising solar magnetograms using supervised learning, (4) generation of UV/EUV images and magnetograms from Galileo sunspot drawings, (5) improvement of global IRI TEC maps using IGS TEC ones, (6) one-day forecasting of global TEC maps through image translation, (7) generation of high-resolution magnetograms from Ca II K images, (8) super-resolution of solar magnetograms, (9) flare classification by CNN and visual explanation by attribution methods, and (10) forecasting GOES solar X-ray profiles. We present major results and discuss them. We also present future plans for integrated space weather models based on deep learning.

The butterfly diagram of the solar cycle is the equatorward migration of sunspot’s emergence latitudes as the solar cycle evolves, which was attributed to the equatorward flow at the base of the convection zone. However, helioseismological studies indicate controversial forms of the flow, and even present poleward flow at the base, which poses a big challenge to the wide-accepted mechanism. So we aim to propose a new mechanism, that is the latitude-dependent radial flux transport.

During 2017, when the Sun was moving toward the minimum phase of solar cycle 24, an exceptionally eruptive active region (AR) NOAA 12673 emerged on the Sun during August 28-September 10. During the highest activity level, the AR turned into a δ-type sunspot region, which manifests the most complex configuration of magnetic fields from the photosphere to the coronal heights. The AR 12673 produced four X-class and 27 M-class flares, along with numerous C-class flares, making it one of the most powerful ARs of solar cycle 24. Notably, it produced the largest flare of solar cycle 24, namely, the X9.3 event on 2017 September 6. In this work, we highlight the results of our comprehensive analysis involving multi-wavelength imaging and coronal magnetic field modeling to understand the evolution and eruptivity from AR 12673. We especially focus on the morphological, spectral and kinematical evolution of the two X-class flares on 6 September 2017. We explore various large- and small-scale magnetic field structures of the active region which are associated with the triggering and subsequent outbursts during the powerful solar transients.

The magnetic power spectrum analysis provides an effective way to understand the observed distribution of the photospheric magnetic fields and their interaction with plasma motions. We aim to investigate the power spectra using spherical harmonic decomposition of SOHO/MDI and SDO/HMI synoptic magnetograms for cycles 23 and 24. We find that the calibration factor between MDI and HMI power spectral density is spatial scale-dependent. The magnetic power spectra show two peaks at the AR scale (l≈30) and supergranular scale (l≈120). The power law indices between these show a good anti-correlation with the amplitude of magnetic activity.

The National Science Foundation (NSF) Daniel K. Inouye Solar Telescope (DKIST) has started operations at the summit of Haleakalā (Hawai’i). DKIST joins the nominal science phases of the NASA and ESA Parker Solar Probe and Solar Orbiter encounter missions. By combining in-situ measurements of the near-Sun plasma environment and detailed remote observations of multiple layers of the Sun, the three observatories form an unprecedented multi-messenger constellation to study the magnetic connectivity in the solar system. This work outlines the synergistic science that this multi-messenger suite enables.

It is believed that the tilt in the bipolar magnetic regions (BMRs) is produced due to a torque induced by the Coriolis force, acting on the diverging flow from the apex of the rising flux tube of the toroidal field in the solar convection zone (SCZ).The BMRs with a strong magnetic field are expected to have reduced tilt as they rise very quickly in the SCZ. This effect can provide the required nonlinear quenching mechanism to suppress the growth of magnetic filed in the dynamo models. Here, we use the magnetograms of the Michelson Doppler Imager (1996–2011) and Helioseismic and Magnetic Imager (2010–2018) to automatically detect the BMRs and look for the signature of tilt quenching. Based on the Bayesian inference method, our results show that the posterior distribution of quenching parameters is Gaussian, and the mean of this distribution agrees with the earlier findings.

Properties of bipolar magnetic regions (BMRs), particularly, the tilt angle play critical roles in generating the observed polar magnetic field and its reversal. Hence, a long-term study of BMR over its lifetime is crucial not only to understand the solar dynamo but also to identify the origin of the properties of BMR. In our work, we have developed an automatic algorithm to detect and track the BMRs from the line-of-sight (LOS) magnetograms of Michelson Doppler Imager (MDI) for the period of Solar Cycle 23 over its lifetime/disk passage. Here, we present the details of our algorithm and the features of BMR, particularly the tilt angle, magnetic field strength and lifetime.

The Aditya-L1 is the first space-based solar observatory of the Indian Space Research Organization (ISRO). The spacecraft will carry seven payloads providing uninterrupted observations of the Sun from the first Lagrangian point. Aditya-L1 comprises four remote sensing instruments, viz. a coronagraph observing in visible and infrared, a full disk imager in Near Ultra-Violet (NUV), and two full-sun integrated spectrometers in soft X-ray and hard X-ray. In addition, there are three instruments for in-situ measurements, including a magnetometer, to study the magnetic field variations during energetic events. Aditya-L1 is truly a mission for multi-messenger solar astronomy from space that will provide comprehensive observations of the Sun across the electromagnetic spectrum and in-situ measurements in a broad range of energy, including magnetic field measurements at L1.

The Solar Orbiter spacecraft, launched in February 2020, is equipped with both remote-sensing (RS) and in-situ (IS) instruments to record novel and unprecedented measurements of the solar atmosphere and the inner heliosphere. To take full advantage of these new datasets, we have developed tools and techniques to facilitate multi-instrument and multi-spacecraft studies. In particular the yet inaccessible low solar corona below 2 R⊙ can only be observed remotely and techniques must be used to retrieve coronal plasma properties in time and in 3-D space. These properties are useful to drive numerical models and test the different theories proposed to describe the fundamental processes of the solar atmosphere. In addition, the last decades of research have shown that the coupling between the solar corona and the heliosphere is most efficiently studied by combining RS with IS data. During one of the last Solar Orbiter remote sensing windows (March 2022), planned for the Solar Orbiter instruments, we ran complex observation campaigns to maximize the likelihood of linking IS data to their source region near the Sun, by directing some RS instruments to specific targets on the solar disk just days before data acquisition. We show how it is possible to achieve these results directed to improve our understanding of how heliospheric probes connect magnetically to the solar disk.

Regular observations of the solar magnetic field are available only for about the last five cycles. Thus, to understand the origin of the variation of the solar magnetic field, it is essential to reconstruct the magnetic field for the past cycles, utilizing the proxies of the magnetic field from other data sets. Long-term uniform observations for the past 100 yrs, as recorded at the Kodaikanal Solar Observatory (KoSO), in multi-wavelengths provide such an opportunity. Various automatic techniques have been developed to extract these features from KoSO data. We analyzed the properties of these extracted features to understand global solar magnetism in the past.

We use a continuous wavelet transform to analyse the daily hemispheric sunspot area data from the Greenwich Royal Observatory during cycles 12–24 and then study the cause of the appearance or disappearance of the Rieger-type periodicity in the northern and southern hemispheres during a certain cycle. The Rieger-type periodicity in the northern and southern hemispheres should be developed independently in the two hemispheres. This periodicity in the northern hemisphere is generally anti-correlated with the long-term variations in the mean solar cycle strength of hemispheric activity, but the correlation of the two parameters in the southern hemisphere shows a weak correlation. The appearance or disappearance of Rieger-type periodicity in the northern and southern hemispheres during a certain solar cycle is not directly correlated with their corresponding hemispheric mean activity strength but should be related to the strength of the hemispheric activity during sunspot maximum times, which hints the Rieger-type periodicity is more related to temporal evolution of toroidal magnetic field. The Rieger-type periodicity in the two hemispheres disappears in those solar cycles with relatively weak hemispheric activity during sunspot maximum times. The reason for the disappearance of this periodicity may be due to the combined influence of relatively weak toroidal magnetic fields and torsional oscillations, the differential rotation parameters vary through the solar cycle and may not remain more or less unchanged during some time, which does not permit the strong growth of magnetic Rossby waves.

A number of solar filaments/prominences demonstrate failed eruptions, when a filament at first suddenly starts to ascend and then decelerates and stops at some greater height in the corona. The mechanism of the termination of eruptions is not clear yet. One of the confining forces able to stop the eruption is the gravity force. Using a simple model of a partial current-carrying torus loop anchored to the photosphere and photospheric magnetic field measurements as the boundary condition for the potential magnetic field extrapolation into the corona, we estimated masses of 15 eruptive filaments. The values of the filament mass show rather wide distribution in the range of $4\times10^{15}$ – $270\times10^{16}$ g. Masses of the most of filaments, laying in the middle of the range, are in accordance with estimations made earlier on the basis of spectroscopic and white-light observations.

Computational heliophysics has shed light on the fundamental physical processes inside the Sun, such as the differential rotation, meridional circulation, and dynamo-generation of magnetic fields. However, despite the substantial advances, the current results of 3D MHD simulations are still far from reproducing helioseismic inferences and surface observations. The reason is the multi-scale nature of the solar dynamics, covering a vast range of scales, which cannot be solved with the current computational resources. In such a situation, significant progress has been achieved by the mean-field approach, based on the separation of small-scale turbulence and large-scale dynamics. The mean-field simulations can reproduce solar observations, qualitatively and quantitatively, and uncover new phenomena. However, they do not reveal the complex physics of large-scale convection, solar magnetic cycles, and the magnetic self-organization that causes sunspots and solar eruptions. Thus, developing a synergy of these approaches seems to be a necessary but very challenging task.