arXiv subjects

Bibhuti Kumar Jha

Publications and source records attributed to Bibhuti Kumar Jha.

At least 19 recordsLinked to original sources

arXiv2026

A Probabilistic Framework for Incorporating Helioseismic Far-Side Active Regions into SFT Models

Surface Flux Transport (SFT) models are routinely used to model the Sun's photospheric magnetic field and provide inner boundary conditions for coronal and heliospheric models, yet they remain fundamentally limited by the lack of direct information about flux emergence on the far side of the Sun. To address this, we develop a framework for incorporating helioseismic images of far-side active regions (HIFAR), into the Advective Flux Transport (AFT) model. Using near-simultaneous magnetic flux maps (HIFARM) inferred from HIFAR, and STEREO/EUVI 304 A observations from 2010 May 13 to 2014 August 18, we develop a logistic regression model to estimate the probability that a helioseismic detection corresponds to an AR based on descriptors of magnetic flux, field strength, and location. The model achieves a precision of 0.93 for active region (AR) detections at a probability threshold of 0.73, selected to reject 90% of "ghost" ARs. We also derive an empirical scaling relationship between HIFARM and AFT flux to place HIFARM on the AFT flux scale and demonstrate that the framework reproduces the flux evolution of ARs consistent with near-side observations over multiple solar rotations. At the global scale, we find that conventional near-side-driven AFT simulations underestimate the total unsigned magnetic flux by ~10-20% of the Sun's total magnetic flux budget. The probabilistic AR detection model and the complete framework developed in this work provide a practical pathway for incorporating helioseismic far-side ARs into SFT models, a step toward realistic modeling of full-Sun magnetic field.

astro-ph.SR↗

arXiv2026

Large ephemeral regions and their tilt angles

The ephemeral regions (ERs), which are short-lived bipolar magnetic regions that emerge across the solar cycle but do not appear as sunspots, play a crucial role in the Sun's magnetic flux budget. However, their properties, particularly the tilt distribution, are poorly constrained by observations. In this study, we isolate ERs from the Automatic Tracking Algorithm for Bipolar Magnetic Regions (AutoTAB) catalog during Solar Cycles 24 and 25 by applying flux and footpoint-separation thresholds. Although AutoTAB was designed to track high-flux regions, it also records ephemeral regions with fluxes of 10^19 to 10^20 Mx, placing them at the upper end of the ER spectrum. The isolated ERs have an average lifetime of 1.2 days. Footpoint separation begins at supergranular scales (about 20 Mm), grows during the first half of the lifetime, and then saturates. ERs occur most frequently near solar minima, consistent with earlier studies and likely reflecting AutoTAB's greater sensitivity to weaker regions when strong BMRs are scarce. Tilt properties reveal a more complex picture. For lifetimes shorter than two days, ERs show a broad, noisy distribution with no systematic latitude dependence. Including longer-lived ERs produces a weak, though statistically insignificant, increasing trend with latitude, suggesting that short-lived ERs are shaped by turbulent convection, while stronger, longer-lived ERs may retain Coriolis-imparted tilts. Overall, these results support the view that ERs occupy the low-flux end of the BMR spectrum and contribute meaningfully to the solar dynamo.

astro-ph.SR↗

arXiv2026

Addressing Known Challenges in Solar Flare Forecasting I: Limb-Flare Prediction with a 4-pi Full-Heliosphere Framework

A demonstrated failure mode for operational solar flare forecasting is the inability to forecast flares that occur near, or just beyond, the solar limb. To address this shortcoming, we develop a "4pi" full-heliosphere event forecasting framework and evaluate its statistical classification ability against this specific challenge. A magnetic surface flux transport model is used to generate full-sun maps of the photospheric radial magnetic field from which active regions (ARs) are identified and tracked using a new labeling scheme that is observer-location agnostic and allows for post-facto modifications. Flare-relevant magnetic parameters couple to a "visibility" index that specifies AR location relative to the visible solar limb and expected flare detection. Flare labels are assigned according to peak Soft X-ray flux, and a statistical classification is performed using nonparametric discriminant analysis. A version where new or emerging ARs on the far ("invisible" side of the Sun are incorporated into the model by way of far-side helioseismology, is also tested. We evaluate the new framework by its performance specifically including the limb areas using Brier Skill Score and ROC Skill Score, finding improvement at the 2-sigma level or less. However, we do find that the number of False Negatives, or "missed" forecasts decreases, and find strong evidence that the additional information provided by the far-side helioseismology can help predict near- and just-beyond-limb flares, particularly for East-limb events. While individual components of this framework could be improved, we demonstrate that a known failure mode for solar flare forecasting can be mitigated with available resources.

astro-ph.SR↗

arXiv2025

Backtracking Bipolar Magnetic Regions to their emergence: Two groups and their implication in the tilt measurements

Bipolar Magnetic Regions (BMRs) that appear on the solar photosphere are surface manifestations of the Suns internal magnetic field. With modern observations and continuous data streams, the study of BMRs has moved from manual sunspot catalogs to automated detection and tracking methods. In this work, we present an additional module to the existing BMR tracking algorithm, AutoTAB, that focuses on identifying emerging signatures of BMRs. Specifically, for regions newly detected on the solar disk, this module backtracks the BMRs to their point of emergence. From a total of about 12,000 BMRs identified by AutoTAB, we successfully backtracked 3,080 cases. Within this backtracked sample, we find two distinct populations. One group shows the expected behavior of emerging regions, in which the magnetic flux increases significantly during the emerging phase. The other group consists of BMRs whose flux, however, does not exhibit substantial growth during their evolution, the instances where our algorithm fails to capture the initial emergence of the BMRs. We classify these as discarded BMRs and examine their statistical properties separately. Our analysis shows that these discarded BMRs do not display any preferred tilt angle distribution and do not show systematic latitudinal tilt dependence, in contrast to the trends typically associated with emerging BMRs. This indicates that including such regions in statistical studies of BMR properties can distort or mask the underlying physical characteristics. We therefore emphasise the importance of excluding the discarded population from the whole dataset when analysing the statistical behavior of BMRs.

astro-ph.SR↗

arXiv2025

Machine Learning Based Identification of Solar Disk and Plages in Kodaikanal Solar Observatory Historical Suncharts

Kodaikanal Solar Observatory (KoSO) is one of the oldest solar observatories, possessing an archive of multi-wavelength solar observations, including white light, Ca II K, and H-alpha images spanning over a century. In addition to these observations, KoSO has preserved hand-drawn suncharts (1904-2022), on which various solar features such as sunspots, plages, filaments, and prominences are marked on the Stonyhurst grid with distinct colour coding. In this study, we present the first comprehensive result that includes the entire data set from these suncharts using a supervised Machine Learning model called "Convolutional Neural Networks (CNNs)", firstly to identify the solar disks from the charts (1909-2007), secondly to identify the plages, spanning 9 solar cycles (1916-2007). We train the CNN with the manually identified solar disk and plage. We first detect the solar limb and the North-South line in the suncharts, which enables the extraction of disk centre coordinates, radius, and P-angle. Following that, we use a CNN similar architecture to achieve accurate image segmentation for the identification of plages. We compare plage areas derived from the suncharts with those obtained from Ca II K full-disk observations, and find good agreement that demonstrates the potential application of such an ML technique for historical data. The results of this study further demonstrate the potential application of sunchart data to fill the existing data gaps in the KoSO multi-wavelength observations and contribute toward constructing a composite series over the last century.

astro-ph.SR↗

arXiv2025

Historical Reconstruction of Solar Surface Magnetism from Cycle 1-24 Using the Synthetic Active Region Generator (SARG) and the Advective Flux Transport (AFT) Model

The historical reconstruction of the Sun's surface magnetic field remains a persistent challenge, limiting our ability to investigate the long-term global properties of the Sun, including the evolution of the large-scale magnetic field, solar cycle prediction, reconstruction of total solar irradiance (TSI), and secular solar variability. In this study, we employ the Advective Flux Transport (AFT) model in conjunction with our newly developed Synthetic Active Region Generator (SARG) to construct a catalog of synthetic active regions (ARs) spanning Solar Cycles 1-24 (1755-2020). We use the SIDC/SILSO sunspot number version 2.0 as the sole input governing the properties of the synthetic ARs in this catalog. This SARG catalog is then incorporated into the AFT model, which simulates the emergence of new ARs on the Sun, which are then transported under the influence of surface flows to produce maps of the full-Sun radial photospheric magnetic field over the entire 265-year period. We modulate the active region tilt for each cycle in order to ensure that the polar fields are consistent with the solar cycle amplitudes. We find that the polar fields derived from these simulations exhibit excellent correlation (r > 0.8) with observational proxies, including polar faculae counts and Ca ii K polar network indices. Daily synchronic maps from these simulations for the entire 265-year period are made publicly available to support a wide range of applications beyond those presented in this work.

astro-ph.SR↗

arXiv2025

Observed Joys law of Bipolar Magnetic Region tilts at the emergence supports the thin flux tube model

Bipolar sunspots, or more generally, Bipolar Magnetic Regions, BMRs, are the dynamic magnetic regions that appear on the solar surface and are central to solar activity. One striking feature of these regions is that they are often tilted with respect to the equator, and this tilt increases with the latitude of appearance, popularly known as Joys law. Although this law has been examined for over a century through various observations, its physical origin is still not established. An attractive theory that has been put forward behind Joys law is the Coriolis force acting on the rising flux tube in the convection zone, which has been studied using the thin flux tube model. However, observational support for this theory is limited. If the Coriolis force is the cause of the tilt, then we expect BMRs to hold Joys law at their initial emergence on the surface. By automatically identifying the BMRs over the last two solar cycles from high resolution magnetic observations, we robustly capture their initial emergence signatures on the surface. We find that from their appearance, BMRs exhibit tilts consistent with Joys law. This early tilt signature of BMRs suggests that the tilt is developed underneath the photosphere, driven by the Coriolis force and helical convection, as predicted by the thin flux tube model. Considerable scatter around Joys law observed during the emergence phase, which reduces in the post emergence phase, reflects the interaction of the vigorous turbulent convection with the rising flux tubes in the near surface layer.

astro-ph.SR↗

arXiv2025

Quantifying Uncertainties in Solar Wind Forecasting Due to Incomplete Solar Magnetic Field Information

Solar wind forecasting plays a crucial role in space weather prediction, yet significant uncertainties persist due to incomplete magnetic field observations of the Sun. Isolating the solar wind forecasting errors due to these effects is difficult. This study investigates the uncertainties in solar wind models arising from these limitations. We simulate magnetic field maps with known uncertainties, including far-side and polar field variations, as well as resolution and sensitivity limitations. These maps serve as input for three solar wind models: the Wang-Sheeley-Arge (WSA), the Heliospheric Upwind eXtrapolation (HUXt), and the European Heliospheric FORecasting Information Asset (EUHFORIA). We analyze the discrepancies in solar wind forecasts, particularly the solar wind speed at Earth's location, by comparing the results of these models to a created "ground truth" magnetic field map, which is derived from a synthetic solar rotation evolution using the Advective Flux Transport (AFT) model. The results reveal significant variations within each model with a RMSE ranging from 59-121 km/s. Further comparison with the thermodynamic Magnetohydrodynamic Algorithm outside a Sphere (MAS) model indicates that uncertainties in the magnetic field data can lead to even larger variations in solar wind forecasts compared to those within a single model. However, predicting a range of solar wind velocities based on a cloud of points around Earth can help mitigate uncertainties by up to 20-77%.

astro-ph.SR↗

arXiv2025

Open-source Flux Transport (OFT). I. HipFT -- High-performance Flux Transport

Global solar photospheric magnetic maps play a critical role in solar and heliospheric physics research. Routine magnetograph measurements of the field occur only along the Sun-Earth line, leaving the far-side of the Sun unobserved. Surface Flux Transport (SFT) models attempt to mitigate this by modeling the surface evolution of the field. While such models have long been established in the community (with several releasing public full-Sun maps), none are open source. The Open Source Flux Transport (OFT) model seeks to fill this gap by providing an open and user-extensible SFT model that also builds on the knowledge of previous models with updated numerical and data acquisition/assimilation methods along with additional user-defined features. In this first of a series of papers on OFT, we introduce its computational core: the High-performance Flux Transport (HipFT) code (github.com/predsci/hipft). HipFT implements advection, diffusion, and data assimilation in a modular design that supports a variety of flow models and options. It can compute multiple realizations in a single run across model parameters to create ensembles of maps for uncertainty quantification and is high-performance through the use of multi-CPU and multi-GPU parallelism. HipFT is designed to enable users to easily write extensions, enhancing its flexibility and adaptability. We describe HipFT's model features, validations of its numerical methods, performance of its parallel and GPU-accelerated code implementation, analysis/post-processing options, and example use cases.

astro-ph.SR↗

arXiv2025

Estimation of Polar Magnetic Fields using Ca II K Polar Network as a Proxy

The polar magnetic field plays a crucial role in the solar dynamo model and contributes to predicting future solar cycles. However, continuous and direct measurements of this polar field have been available only since 1976, with data provided by the Wilcox Solar Observatory (WSO). Recent findings suggest that the Ca ii K Polar Network Index (PNI) can serve as a promising proxy for estimating the polar field of the Sun. In this study, we aim to reconstruct the polar field for the pre-1976 period by leveraging Ca ii K data from the Kodaikanal Solar Observatory (KoSO; 1904-2007) and modern Ca ii K observations from the Rome Precision Solar Photometric Telescope (Rome-PSPT; 2000-2022). We employ an automatic adaptive threshold technique to detect polar networks and calculate PNI values. Then, we calibrate these PNI values with the WSO polar field to reconstruct the polar field over 119 years.

astro-ph.SR↗

arXiv2025

Ca II K Polar Network Index of the Sun: A Proxy for Historical Polar Magnetic Field

The Sun's polar magnetic field is pivotal in understanding solar dynamo processes and forecasting future solar cycles. However, direct measurements of the polar field is only available since the 1970s. The chromospheric Ca II K polar network index (PNI; the fractional area of the chromospheric network regions above a certain latitude) has recently emerged as a reliable proxy for polar magnetic fields. In this study, we derive PNI estimates from newly calibrated, rotation-corrected Ca II K observations from the Kodaikanal Solar Observatory (1904-2007) and modern data from the Rome Precision Solar Photometric Telescope (2000-2022). We use both of those Ca II K archives to identify polar network regions with an automatic adaptive threshold segmentation technique and calculate the PNI. The PNI obtained from both the archives shows a significant correlation with the measured polar field from WSO (Pearson correlation coefficient r > 0.93) and the derived polar field based on an Advective Flux Transport Model (r > 0.91). The PNI series also shows a significant correlation with faculae counts derived from Mount Wilson Observatory observations (r > 0.87) for both KoSO and Rome-PSPT data. Finally, we use the PNI series from both archives to reconstruct the polar magnetic field over a 119-year-long period, which includes last 11 solar cycles (Cycle 14-24). We also obtain a relationship between the amplitude of solar cycles (in 13-month smoothed sunspot number) and the strength of the reconstructed polar field at the preceding solar cycle minimum to validate the prediction of the ongoing solar cycle, Cycle 25.

astro-ph.SR↗

arXiv2025

Exploring the variation in the dynamic rotation profile of the hotter solar atmosphere using mutliwavelength data

The global rotational profile of the solar atmosphere and its variation at different layers, although crucial for a comprehensive understanding of the dynamics of the solar magnetic field, has been a subject to contradictory results throughout the past century. In this study, we thereby unify the results for different parts of the multi-thermal Solar atmosphere by utilizing 13 years of data in 7 wavelength channels of the Atmospheric Imaging Assembly (AIA) atop the Solar Dynamic Observatory (SDO). Using the method of image correlation, we find that the solar atmosphere exhibits a rotational profile that is up to 4.18% and 1.92% faster at the equator and comparatively less differential than that of the photosphere, as derived from Doppler measurements and sunspots, respectively and exhibits variation at different respective heights. Additionally, we find results suggestive of the role played by the rooting of different magnetic field structures on a comparison with helioseismology data.

astro-ph.SR↗

arXiv2024

Exploring the dynamic rotational profile of the hotter solar atmosphere: A multi-wavelength approach using SDO/AIA data

Understanding the global rotational profile of the solar atmosphere and its variation is fundamental to uncovering a comprehensive understanding of the dynamics of the solar magnetic field and the extent of coupling between different layers of the Sun. In this study, we employ the method of image correlation to analyze the extensive dataset provided by the Atmospheric Imaging Assembly of the Solar Dynamic Observatory in different wavelength channels. We find a significant increase in the equatorial rotational rate ($A$) and a decrease in absolute latitudinal gradient ($|B|$) at all temperatures representative of the solar atmosphere, implying an equatorial rotation up to $4.18\%$ and $1.92\%$ faster and less differential when compared to the rotation rates for the underlying photosphere derived from Doppler measurement and sunspots respectively. In addition, we also find a significant increase in equatorial rotation rate ($A$) and a decrease in differential nature ($|B|$ decreases) at different layers of the solar atmosphere. We also explore a possible connection from the solar interior to the atmosphere and interestingly found that $A$ at $r=0.94\,\mathrm{R}_{\odot}, 0.965\,\mathrm{R}_{\odot}$ show an excellent match with 171 Angstrom, 304 Angstrom and 1600 Angstrom, respectively. Furthermore, we observe a positive correlation between the rotational parameters measured from 1600 Angstrom, 131 Angstrom, 193 Angstrom and 211 Angstrom with the yearly averaged sunspot number, suggesting a potential dependence of the solar rotation on the appearance of magnetic structures related to the solar cycle or the presence of cycle dependence of solar rotation in the solar atmosphere.

astro-ph.SR↗

arXiv2024

Butterfly Diagram and Other Properties of Plage Areas from Kodaikanal Ca II K Photographs Covering 1904-2007

Ca II K observations of the Sun have a great potential for probing the Sun's magnetism and activity, as well as for reconstructing solar irradiance. The Kodaikanal Solar Observatory (KoSO) in India, houses one of the most prominent Ca II K archives, spanning from 1904 to 2007, obtained under the same experimental conditions over a century, a feat very few other sites have achieved. However, the KoSO Ca II K archive suffers from several inconsistencies (e.g., missing/incorrect timestamps of observations and orientation of some images) which have limited the use of the archive. This study is a step towards bringing the KoSO archive to its full potential. We did this by developing an automatic method to orient the images more accurately than in previous studies. Furthermore, we included more data than in earlier studies (considering images that could not previously be analyzed by other techniques as well as 2845 newly digitized images), while also accounting for mistakes in the observational date/time. These images were accurately processed to identify plage regions along with their locations, enabling us to construct the butterfly diagram of plage areas from the entire KoSO Ca II K archive covering 1904-2007. Our butterfly diagram shows significantly fewer data gaps compared to earlier versions due to the larger set of data used in this study. Moreover, our butterfly diagram is consistent with Spörer's law for sunspots, validating our automatic image orientation method. Additionally, we found that the mean latitude of plage areas calculated over the entire period is 20.5%+/-2.0 higher than that of sunspots, irrespective of the phase or the strength of the solar cycle. We also studied the North-South asymmetry showing that the northern hemisphere dominated plage areas during solar cycles 19 and 20, while the southern hemisphere dominated during solar cycles 21--23.

astro-ph.SR↗

arXiv2024

Analysis of BMR tilt from AutoTAB catalog: Hinting towards the thin flux tube model?

One of the intriguing mechanisms of the Sun is the formation of the bipolar magnetic regions (BMRs) in the solar convection zone which are observed as regions of concentrated magnetic fields of opposite polarity on photosphere. These BMRs are tilted with respect to the equatorial line, which statistically increases with latitude. The thin flux tube model, employing the rise of magnetically buoyant flux loops and their twist by Coriolis force, is a popular paradigm for explaining the formation of tilted BMRs. In this study, we assess the validity of the thin flux tube model by analyzing the tracked BMR data obtained through the Automatic Tracking Algorithm for BMRs (AutoTAB). Our observations reveal that the tracked BMRs exhibit the expected collective behaviors. We find that the polarity separation of BMRs increases over their normalized lifetime, supporting the assumption of a rising flux tube from the CZ. Moreover, we observe an increasing trend of the tilt with the flux of the BMR, suggesting that rising flux tubes associated with lower flux regions are primarily influenced by drag force and Coriolis force, while in higher flux regions, magnetic buoyancy dominates. Furthermore, we observe Joy's law dependence for emerging BMRs from their first detection, indicating that at least a portion of the tilt observed in BMRs can be attributed to the Coriolis force. Notably, lower flux regions exhibit a higher amount of fluctuations associated with their tilt measurement compared to stronger flux regions, suggesting that lower flux regions are more susceptible to turbulent convection.

astro-ph.SR↗

arXiv2024

Predicting the Timing of the the Solar Cycle 25 Polar Field Reversal

The process of the Sun's polar field cancellation reversal commences with the emergence of new cycle Hale's polarity active regions. Once the Sun undergoes polarity reversal, typically occurring near the peak of solar activity, it begins the process of accumulating the seed field for the forthcoming solar cycle. In recent years, the Advective Flux Transport (AFT) model has proven highly effective in forecasting the progression of polar fields by leveraging observations of surface flows and magnetic flux emergence. In this study, we make use of the predictive capability of the AFT model to simulate the evolution of the polar fields and estimate the timing of the Solar Cycle 25 polarity reversal in both hemispheres of the Sun. We use the statistical properties of active regions along with Solar Cycle~13, which closely resembles the current solar cycle (Cycle~25), to generate synthetic active regions in order to simulate future magnetic flux emergence in AFT to predict the evolution of the polar field. Based on our simulations, we anticipate that the Northern hemisphere of the Sun will undergo a polarity reversal between June 2024 and November 2024, with the center of our distribution at August 2024. In the Southern hemisphere, we anticipate a polarity reversal between November 2024 and July 2025, centered around February 2025. Additionally, assuming that the reversal of the axial dipole moment coincides with the peak of the solar cycle, our findings indicate that Cycle 25 is expected to peak in 2024 (likely between April to August 2024).

astro-ph.SR↗

arXiv2024

AutoTAB: An Algorithm to Track Bipolar Magnetic Regions and Initial results from the Tracked BMRs

AutoTAB is a state-of-the-art, fully automatic algorithm that tracks the Bipolar Magnetic Regions (BMRs) in magnetogram observations. AutoTAB employs identified BMR regions from Line-of-Sight magnetograms from MDI and HMI (1996--2022) to track the BMRs through their evolution on the nearside of the Sun. AutoTAB enables us to create a comprehensive and unique catalog of tracked information of 9232 BMRs in the mentioned time period. This dataset is used to study the collective statistical properties of BMRs and particularly to identify the correct theory for the BMR formation. Here, we discuss the algorithm's functionality and the initial findings obtained from the AutoTAB BMRs catalog.

astro-ph.SR↗

arXiv2024

Exploring the Quenching of Bipolar Magnetic Region Tilts using AutoTAB

The tilt of the bipolar magnetic region (BMR) is crucial in the Babcock-Leighton process for the generation of the poloidal magnetic field in the Sun. We extend the work of Jha et al. (2020) and analyze the recently reported tracked BMR catalogue based on AutoTAB Sreedevi et al. (2023) from Michelson Doppler Imager (1996-2011) and Helioseismic and Magnetic Imager (2010-2018). Using the tracked information of BMRs based on AutoTAB, we confirm that the distribution of bmax reported by Jha et al. (2020) is not because of the BMRs are picked multiple times at the different phases of their evolution instead it is also present if we consider each BMRs only once. Moreover, we find that the slope of Joy's law initially increases slowly with the increase of bmax. However, when bmax>2.5 kG, gamma_0 decreases. The decrease of observed $gamma_0$ with bmax provides a hint to a nonlinear tilt quenching in the Babcock-Leighton process.

astro-ph.SR↗