arXiv subjects

Sanchita Pal

Publications and source records attributed to Sanchita Pal.

17 recordsLinked to original sources

arXiv2026

Unprecedented Multipoint Observation of Spatially Varying ICME Turbulence of Different Ages during October 2024 Extreme Solar Storm at 1 AU

Understanding turbulence in interplanetary coronal mass ejections (ICMEs) is fundamental to space plasma research and critical for assessing the impact of space weather on geospace. Turbulence governs energy cascade, plasma heating, magnetic reconnection, and solar wind magnetosphere coupling, thereby influencing both ICME evolution and geoeffectiveness. While previous event based and statistical studies have examined ICME turbulence and its radial evolution in great detail, no significant measurements of ICME magnetic turbulence at a single vantage point have been obtained from multiple observatories separated azimuthally. Here, we present the first multipoint analysis of magnetohydrodynamic (MHD) turbulence across ICME plasma regions, using four spacecraft at the Sun-Earth L1 point, separated by 80 RE (mesoscale) along the dawn-dusk direction. Using high-resolution magnetic field observations from ISRO's Aditya L1, NASA's Wind and ACE, and NOAA's DSCOVR, we analyze turbulence associated with the October 10, 2024, solar storm, which triggered the second strongest geomagnetic storm of solar cycle 25. Our results reveal significant variability and differing turbulence maturity across small separations, supported by analysis of field-aligned and perpendicular magnetic-field cascades, indicating strong anisotropies. Sheath turbulence is substantially modified by shock induced energy injection. Evidence of compressible turbulence and plasma energization at the flux rope interaction region indicates that internal processes, such as magnetic reconnection, strongly influence ICME plasma evolution, highlighting pronounced spatial variability in turbulence and plasma states observed by multiple L1 monitors near Earth and underscoring their potential role in space weather impacts.

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arXiv2026

Comprehensive MHD modelling of ten successive CMEs driving a historic geomagnetic storm -- The 2024 Mothers Day event

Interacting coronal mass ejections (CMEs) result in complex heliospheric structures that can dramatically enhance their geoeffectiveness compared to isolated events. A striking example of such complex structures is that of the Mothers Day event, which occurred during 10-14 May 2024, leading to the strongest geomagnetic storm in decades. It was driven by at least ten interacting CMEs accompanied by flare and filament eruptions from the solar western hemisphere. We aim to understand its solar and heliospheric origins, variation in plasma and magnetic characteristics, and predict its geoeffectiveness. Furthermore, we focus on bringing to the community the challenges and limitations faced during themodelling of such a complex, yet important environment. We use multi-point remote observations of CMEs and employ different methods to estimate their speeds and geometry. These parameters drive the 3D magnetohydrodynamic simulations of CME evolution and heliospheric propagation in the framework of the EUHFORIA model. The best-performing simulation reproduced the arrival time of the storm and peak intensity with a lead of 2 hours, and estimated the storm strength with about 70% accuracy. This work underscores the requirements and challenges involved in accurately modelling extreme events. The major bottleneck was to constrain the CME input parameters that dictate the accuracy of the data-driven simulations. Predicting the impacts of the complex heliospheric structures during this event required the modelling of the CME-CME interactions accurately. As a community, we need to invest more in observational infrastructure while improving the speed and accuracy of our MHD forecasting models.

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arXiv2026

Solar Wind Heating Near the Sun: A Radial Evolution Approach

Characterizing the plasma state in the near-Sun environment is essential to constrain the mechanisms that heat and accelerate the solar wind. In this study, we use Parker Solar Probe (PSP) observations from Encounters 1 through 24 to investigate the radial evolution of solar wind plasma and magnetic field properties in this region. Using intervals with high field-of-view ($>85\%$) coverage, we derive the radial profiles of magnetic field strength ($|B|$), proton density ($N$), bulk speed ($V$), total proton temperature ($T$), parallel ($T_\parallel$) and perpendicular ($T_\perp$) temperatures, temperature anisotropy ($T_\perp/T_\parallel$), plasma beta ($β$), Alfvén Mach number ($M_A$), and magnetic field fluctuations ($δB/B$) for sub and super-Alfvénic regions. In super-Alfvénic regions, power-law of $|B|$, $N$, $V$, and $T$ as a function of heliocentric distance are broadly consistent with previous \textit{Helios} results at $>0.3$ AU. The radial evolution of the components of the temperature tensor reveals distinct behavior: $T_\perp$ decreases monotonically with distance, whereas $T_\parallel$ exhibits a non-monotonic trend -- decreasing in the sub-Alfvénic region, increasing just beyond the Alfvén surface. We interpret the increase in $T_\parallel$ as a proxy for proton beam occurrence. We further examine the evolution of magnetic field fluctuations, finding decreasing radial/parallel fluctuations but enhanced tangential/normal/perpendicular fluctuations in sunward direction. These fluctuations may provide free energy for beam generation and particle heating via wave-particle interactions.

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arXiv2025

Magnetic interaction analysis of multiple interplanetary coronal mass ejections leading to a historic geomagnetic storm in May 2024

Interplanetary coronal mass ejections (ICMEs), the large-scale eruptive phenomena capable of shedding a huge amount of solar magnetic helicity and energy are potential in driving strong geomagnetic storms. They complexly evolve while preceded and followed by other large-scale structures e.g. ICMEs. Magnetic interaction among multiple ICMEs may result intense and long-lived geomagnetic storms. Our aim is to understand the reason of substantial changes in the geoeffectivity of two meso-scale separated counterparts of a complex solar wind structure through investigating their magnetic content e.g. helicity, energy and magnetic interaction among multiple ICMEs. We utilized the insitu observations of solar wind from Wind and Solar Terrestrial Relations Observatory-A (STA) spacecraft during the strongest geomagnetic storm period in past two decades on May 10-11, 2024 and heliospheric imagers onboard STA. Our investigation confirms complex interactions among five ICMEs resulting in distinct counterparts within a coalescing large-scale structure. These counterparts possess substantially different magnetic contents. We conclude that the complex counterpart resulted from the interaction among common-origin ICMEs observed by STA, favorably orientated for magnetic reconnection, had 1.6 and 2.8 times higher total magnetic energy and helicity, respectively, than the counterpart containing a left-handed filament-origin ICME observed by Wind. The left-handed ICME non-favorably oriented for magnetic reconnection with the surrounding right-handed, common-origin ICMEs. Therefore, two medium-separated counterparts despite belonging to a common solar wind structure, were potential to lead different geoeffectivity. This ultimately challenges space weather predictions based on early observations.

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arXiv2024

Classifying different types of solar wind plasma with uncertainty estimations using machine learning

Decades of in-situ solar wind measurements have clearly established the variation of solar wind physical parameters. These variable parameters have been used to classify the solar wind magnetized plasma into different types leading to several classification schemes being developed. These classification schemes, while useful for understanding the solar wind originating processes at the Sun and early detection of space weather events, have left open questions regarding which physical parameters are most useful for classification and how recent advances in our understanding of solar wind transients impact classification. In this work, we use neural networks trained with different solar wind magnetic and plasma characteristics to automatically classify the solar wind in coronal hole, streamer belt, sector reversal and solar transients such as coronal mass ejections comprised of both magnetic obstacles and sheaths. Furthermore, our work demonstrates how probabilistic neural networks can enhance the classification by including a measure of prediction uncertainty. Our work also provides a ranking of the parameters that lead to an improved classification scheme with ~96% accuracy. Our new scheme paves the way for incorporating uncertainty estimates into space weather forecasting with the potential to be implemented on real-time solar wind data.

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arXiv2024

Automatic detection of large-scale flux ropes and their geoeffectiveness with a machine learning approach

Detecting large-scale flux ropes (FRs) embedded in interplanetary coronal mass ejections (ICMEs) and assessing their geoeffectiveness are essential since they can drive severe space weather. At 1 au, these FRs have an average duration of 1 day. Their most common magnetic features are large, smoothly rotating magnetic fields. Their manual detection has become a relatively common practice over decades, although visual detection can be time-consuming and subject to observer bias. Our study proposes a pipeline that utilizes two supervised binary-classification machine learning (ML) models trained with solar wind magnetic properties to automatically detect large-scale FRs and additionally determine their geoeffectiveness. The first model is used to generate a list of auto-detected FRs. Using the properties of southward magnetic field the second model determines the geoeffectiveness of FRs. Our method identifies 88.6\% and 80\% large-scale ICMEs (duration $\ge 1$ day) observed at 1 au by Wind and Sun Earth Connection Coronal and Heliospheric Investigation (STEREO) mission, respectively. While testing with a continuous solar wind data obtained from Wind, our pipeline detected 56 of the 64 large-scale ICMEs during 2008 - 2014 period (recall= 0.875) but many false positives (precision= 0.56) as we do not take into account any additional solar wind properties than the magnetic properties. We found an accuracy of 0.88 when estimating the geoeffectiveness of the auto-detected FRs using our method. Thus, in space weather now-casting and forecasting at L1 or any planetary missions, our pipeline can be utilized to offer a first-order detection of large-scale FRs and geoeffectiveness.

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arXiv2024

Correcting Projection Effects in CMEs using GCS-based Large Statistics of Multi-viewpoint Observations

This study addresses the limitations of single-viewpoint observations of Coronal Mass Ejections (CMEs) by presenting results from a 3D catalog of 360 CMEs during solar cycle 24, fitted using the GCS model. The dataset combines 326 previously analyzed CMEs and 34 newly examined events, categorized by their source regions into active region (AR) eruptions, active prominence (AP) eruptions, and prominence eruptions (PE). Estimates of errors are made using a bootstrapping approach. The findings highlight that the average 3D speed of CMEs is $\sim$1.3 times greater than the 2D speed. PE CMEs tend to be slow, with an average speed of 432 km $s^{-1}$. AR and AP speeds are higher, at 723 km $s^{-1}$ and 813 km $s^{-1}$, respectively, with the latter having fewer slow CMEs. The distinctive behavior of AP CMEs is attributed to factors like overlying magnetic field distribution or geometric complexities leading to less accurate GCS fits. A linear fit of projected speed to width gives a gradient of 2 km $s^{-1}deg^{-1}$, which increases to 5 km $s^{-1}deg^{-1}$ when the GCS-fitted `true' parameters are used. Notably, AR CMEs exhibit a high gradient of 7 km $s^{-1}deg^{-1}$, while AP CMEs show a gradient of 4 km $s^{-1}deg^{-1}$. PE CMEs, however, lack a significant speed-width relationship. We show that fitting multi-viewpoint CME images to a geometrical model such as GCS is important to study the statistical properties of CMEs, and can lead to a deeper insight into CME behavior that is essential for improving future space weather forecasting.

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arXiv2024

On the Mesoscale Structure of CMEs at Mercury's Orbit: BepiColombo and Parker Solar Probe Observations

On 2022 February 15, an impressive filament eruption was observed off the solar eastern limb from three remote-sensing viewpoints, namely Earth, STEREO-A, and Solar Orbiter. In addition to representing the most-distant observed filament at extreme ultraviolet wavelengths -- captured by Solar Orbiter's field of view extending to above 6 $R_{\odot}$ -- this event was also associated with the release of a fast ($\sim$2200 km$\cdot$s$^{-1}$) coronal mass ejection (CME) that was directed towards BepiColombo and Parker Solar Probe. These two probes were separated by 2$^{\circ}$ in latitude, 4$^{\circ}$ in longitude, and 0.03 au in radial distance around the time of the CME-driven shock arrival in situ. The relative proximity of the two probes to each other and to the Sun ($\sim$0.35 au) allows us to study the mesoscale structure of CMEs at Mercury's orbit for the first time. We analyse similarities and differences in the main CME-related structures measured at the two locations, namely the interplanetary shock, the sheath region, and the magnetic ejecta. We find that, despite the separation between the two spacecraft being well within the typical uncertainties associated with determination of CME geometric parameters from remote-sensing observations, the two sets of in-situ measurements display some profound differences that make understanding of the overall 3D CME structure particularly challenging. Finally, we discuss our findings within the context of space weather at Mercury's distances and in terms of the need to investigate solar transients via spacecraft constellations with small separations, which has been gaining significant attention during recent years.

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arXiv2023

New Observations Needed to Advance Our Understanding of Coronal Mass Ejections

Coronal mass ejections (CMEs) are large eruptions from the Sun that propagate through the heliosphere after launch. Observational studies of these transient phenomena are usually based on 2D images of the Sun, corona, and heliosphere (remote-sensing data), as well as magnetic field, plasma, and particle samples along a 1D spacecraft trajectory (in-situ data). Given the large scales involved and the 3D nature of CMEs, such measurements are generally insufficient to build a comprehensive picture, especially in terms of local variations and overall geometry of the whole structure. This White Paper aims to address this issue by identifying the data sets and observational priorities that are needed to effectively advance our current understanding of the structure and evolution of CMEs, in both the remote-sensing and in-situ regimes. It also provides an outlook of possible missions and instruments that may yield significant improvements into the subject.

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arXiv2022

A Comparative Analysis of Machine-learning Models for Solar Flare Forecasting: Identifying High-performing Active Region Flare Indicators

Solar flares create adverse space weather impacting space and Earth-based technologies. However, the difficulty of forecasting flares, and by extension severe space weather, is accentuated by the lack of any unique flare trigger or a single physical pathway. Studies indicate that multiple physical properties contribute to active region flare potential, compounding the challenge. Recent developments in machine learning (ML) have enabled analysis of higher-dimensional data leading to increasingly better flare forecasting techniques. However, consensus on high-performing flare predictors remains elusive. In the most comprehensive study to date, we conduct a comparative analysis of four popular ML techniques (k-nearest neighbor, logistic regression, random forest classifier, and support vector machine) by training these on magnetic parameters obtained from the Helioseismic and Magnetic Imager (HMI) on board the Solar Dynamics Observatory (SDO) for the entirety of solar cycle 24. We demonstrate that the logistic regression and support vector machine algorithms perform extremely well in forecasting active region flaring potential. The logistic regression algorithm returns the highest true skill score of $0.967 \pm 0.018$, possibly the highest classification performance achieved with any strictly parametric study. From a comparative assessment, we establish that the magnetic properties like total current helicity, total vertical current density, total unsigned flux, R_VALUE, and total absolute twist are the top-performing flare indicators. We also introduce and analyze two new performance metrics, namely, severe and clear space weather indicators. Our analysis constrains the most successful ML algorithms and identifies physical parameters that contribute most to active region flare productivity.

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arXiv2022

A magnetic cloud prediction model for forecasting space weather relevant properties of Earth-directed coronal mass ejections

Coronal Mass Ejections (CMEs) are energetic storms in the Sun that result in the ejection of large-scale magnetic clouds (MCs) in interplanetary space that contain enhanced magnetic fields with coherently changing field direction. The severity of geomagnetic perturbations depends on the direction and strength of the interplanetary magnetic field (IMF), as well as the speed and duration of passage of the storm. The coupling between the heliospheric environment and Earth's magnetosphere is the strongest when the IMF direction is persistently southward for a prolonged period. Predicting the magnetic profile of such Earth-directed CMEs is crucial for estimating their geomagnetic impact. We aim to build upon and integrate diverse techniques towards development of a comprehensive magnetic cloud prediction (MCP) model that can forecast the magnetic field vectors, Earth-impact time, speed and duration of passage of solar storms. A novelty of our scheme is the ability to predict the passage duration of the storm without recourse to computationally intensive, time-dependent dynamical equations. Our methodology is validated by comparing the MCP model output with observations of ten MCs at 1 AU. In our sample, we find that eight MCs show a root mean square deviation of less than 0.1 between predicted and observed magnetic profiles and the passage duration of seven MCs fall within the predicted range. Based on the success of this approach, we conclude that predicting the near-Earth properties of MCs based on analysis and modelling of near-Sun CME observations is a viable endeavor with potential benefits for space weather assessment.

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arXiv2022

Eruption and Interplanetary Evolution of a Stealthy Streamer-Blowout CME Observed by PSP at ${\sim}$0.5~AU

Streamer-blowout coronal mass ejections (SBO-CMEs) are the dominant CME population during solar minimum. Although they are typically slow and lack clear low-coronal signatures, they can cause geomagnetic storms. With the aid of extrapolated coronal fields and remote observations of the off-limb low corona, we study the initiation of an SBO-CME preceded by consecutive CME eruptions consistent with a multi-stage sympathetic breakout scenario. From inner-heliospheric Parker Solar Probe (PSP) observations, it is evident that the SBO-CME is interacting with the heliospheric magnetic field and plasma sheet structures draped about the CME flux rope. We estimate that $18 \, \pm \, 11\%$ of the CME's azimuthal magnetic flux has been eroded through magnetic reconnection and that this erosion began after a heliospheric distance of ${\sim}0.35$ AU from the Sun was reached. This observational study has important implications for understanding the initiation of SBO-CMEs and their interaction with the heliospheric surroundings.

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arXiv2021

Predicting the Magnetic Fields of a Stealth CME Detected by Parker Solar Probe at 0.5 AU

Stealth coronal mass ejection (CMEs) are eruptions from the Sun that are not associated with appreciable low-coronal signatures. Because they often cannot be linked to a well-defined source region on the Sun, analysis of their initial magnetic configuration and eruption dynamics is particularly problematic. In this manuscript, we address this issue by undertaking the first attempt at predicting the magnetic fields of a stealth CME that erupted in 2020 June from the Earth-facing Sun. We estimate its source region with the aid of off-limb observations from a secondary viewpoint and photospheric magnetic field extrapolations. We then employ the Open Solar Physics Rapid Ensemble Information (OSPREI) modelling suite to evaluate its early evolution and forward-model its magnetic fields up to Parker Solar Probe, which detected the CME in situ at a heliocentric distance of 0.5 AU. We compare our hindcast prediction with in-situ measurements and a set of flux rope reconstructions, obtaining encouraging agreement on arrival time, spacecraft crossing location, and magnetic field profiles. This work represents a first step towards reliable understanding and forecasting of the magnetic configuration of stealth CMEs and slow, streamer-blowout events.

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arXiv2021

Uncovering Erosion Effects on Magnetic Flux Rope Twist

Magnetic clouds (MCs) are transient structures containing large-scale magnetic flux ropes from solar eruptions. The twist of magnetic field lines around the rope axis reveals information about flux rope formation processes and geoeffectivity. During propagation, MC flux ropes may erode via reconnection with the ambient solar wind. Any erosion reduces the magnetic flux and helicity of the ropes, and changes their cross-sectional twist profiles. This study relates twist profiles in MC flux ropes observed at 1 AU to the amount of erosion undergone by the MCs in interplanetary space. The twist profiles of two well-identified MC flux ropes associated with the clear appearance of post eruption arcades in the solar corona are analysed. To infer the amount of erosion, the magnetic flux content of the ropes in the solar atmosphere is estimated, and compared to estimates at 1 AU. The first MC shows a monotonically decreasing twist from the axis to periphery, while the second displays high twist at the axis, rising twist near the edges, and lower twist in between. The first MC displays a larger reduction in magnetic flux between the Sun and 1 AU, suggesting more erosion, than that seen in the second MC. In the second cloud, rising twist at the rope edges may have been due to an envelope of overlying coronal field lines with relatively high twist, formed by reconnection beneath the erupting flux rope in the low corona. This high-twist envelope remained almost intact from the Sun to 1 AU due to the low erosion levels. In contrast, the high-twist envelope of the first cloud may have been entirely peeled away via erosion by the time it reaches 1 AU.

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arXiv2021

Flux erosion of magnetic clouds by reconnection with the Sun's open flux

Magnetic clouds (MCs) are flux-rope magnetic structures forming a subset of solar coronal mass ejections which have significant space weather impacts. The geoeffectiveness of MCs depends on their properties which evolve during their interplanetary passage. Based on an analysis of observations spanning two solar cycles we establish that MCs interacting with the ambient solar wind magnetic field (i.e., heliospheric open flux) lose a substantial amount of their initial magnetic flux via magnetic reconnection, which in some cases, reduce their geoeffectiveness. We find a linear correlation between the eroded flux of MCs and solar open flux which is consistent with the scenario that MC erosion is mediated via the local heliospheric magnetic field draping around an MC during its interplanetary propagation. The solar open flux is governed by the sunspot cycle. This work therefore uncovers a hitherto unknown pathway for solar cycle modulation of the properties of MCs.

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arXiv2018

Dependence of coronal mass ejection properties on their solar source active region characteristics and associated flare reconnection flux

The near-Sun kinematics of coronal mass ejections (CMEs) determine the severity and arrival time of associated geomagnetic storms. We investigate the relationship between the deprojected speed and kinetic energy of CMEs and magnetic measures of their solar sources, reconnection flux of associated eruptive events and intrinsic flux rope characteristics. Our data covers the period 2010-2014 in solar cycle 24. Using vector magnetograms of source active regions we estimate the size and nonpotentiality. We compute the total magnetic reconnection flux at the source regions of CMEs using the post-eruption arcade method. By forward modeling the CMEs we find their deprojected geometric parameters and constrain their kinematics and magnetic properties. Based on an analysis of this database we report that the correlation between CME speed and their source active region size and global nonpotentiality is weak, but not negligible. We find the near-Sun velocity and kinetic energy of CMEs to be well correlated with the associated magnetic reconnection flux. We establish a statistically significant empirical relationship between the CME speed and reconnection flux that may be utilized for prediction purposes. Furthermore, we find CME kinematics to be related with the axial magnetic field intensity and relative magnetic helicity of their intrinsic flux ropes. The amount of coronal magnetic helicity shed by CMEs is found to be well correlated with their near-Sun speeds. The kinetic energy of CMEs is well correlated with their intrinsic magnetic energy density. Our results constrain processes related to the origin and propagation of CMEs and may lead to better empirical forecasting of their arrival and geoeffectiveness.

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arXiv2017

A Sun-to-Earth analysis of magnetic helicity of the 17-18 March 2013 interplanetary coronal mass ejection

We compare the magnetic helicity in the 17-18 March 2013 interplanetary coronal mass ejection (ICME) flux-rope at 1 AU and in its solar counterpart. The progenitor coronal mass ejection (CME) erupted on 15 March 2013 from NOAA active region 11692 and associated with an M1.1 flare. We derive the source region reconnection flux using post-eruption arcade (PEA) method (Gopalswamy et al. 2017a) that uses the photospheric magnetogram and the area under the PEA. The geometrical properties of the near-Sun flux rope is obtained by forward-modeling of white-light CME observations. Combining the geometrical properties and the reconnection flux we extract the magnetic properties of the CME flux rope (Gopalswamy et al. 2017b). We derive the magnetic helicity of the flux rope using its magnetic and geometric properties obtained near the Sun and at 1 AU. We use a constant-α force-free cylindrical flux rope model fit to the in situ observations in order to derive the magnetic and geometric information of the 1-AU ICME. We find a good correspondence in both amplitude and sign of the helicity between the ICME and the CME assuming a semi-circular (half torus) ICME flux rope with a length of π AU. We find that about 83% of the total flux rope helicity at 1 AU is injected by the magnetic reconnection in the low corona. We discuss the effect of assuming flux rope length in the derived value of the magnetic helicity. This study connecting the helicity of magnetic flux ropes through the Sun-Earth system has important implications for the origin of helicity in the interplanetary medium and the topology of ICME flux ropes at 1 AU and hence their space weather consequences.

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