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soumya shree sadangaya8/17/26, 11:10 AMHeliophysics & Space WeatherOral
We investigate the post-flare amplification of chromospheric 3-minute oscillations within a sunspot umbra following the SOL2024-08-08 X1.3-class flare. Utilizing high-resolution data from the DKIST Visible Broadband Imager at 450 nm and the AR30THz telescope focused on AR13777, we demonstrate the global dominance of 5-minute oscillations and the strict localization of 3-minute modes within the...
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Besma Guesmi (Ubotica Technologies)8/17/26, 3:00 PMSpace Weather Forecasting & OperationsOral
Geoeffective coronal mass ejections (CMEs) can disrupt satellites, power grids, and navigation systems, making accurate early warning critical for space weather operations. We present CMEAT, a curated multimodal dataset and fusion framework for predicting CME Earth impact and Sun–Earth transit time. CMEAT pairs CDAW LASCO observations (1996-2025) with ICME arrival labels and upstream L1...
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97. The new Solar Ultraviolet to Near-infrared Spectrometer (SUNS): searching for white-light flaresPaulo Simões (Universidade Presbiteriana Mackenzie)8/17/26, 3:20 PMInstrumentation & Observational SystemsOral
Since the first observation of a solar flare in 1859 by Carrington and Hodgson, explaining the origin of the excess visible continuum emission (white-light flares, WLFs) remains a challenge in the understanding of these events. Identifying the radiation mechanism involved is crucial for understanding the transport and deposition of energy in the solar atmosphere. However, spectral data for...
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Yuliang Shen (naoc)8/18/26, 9:40 AM1Instrumentation & Observational SystemsOral
Magnetic field is the most important observational quantity in contemporary solar physics, as nearly all solar activities are closely associated with the solar magnetic field and its evolution. Currently, measurements of the solar magnetic field are primarily based on the Zeeman effect, where longer wavelengths offer higher detection precision and sensitivity. Therefore, conducting solar...
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Dr OLUDEHINWA Irewola Aaron (Department of Physics, Federal University of Agriculture, Abeokuta, Nigeria.)8/18/26, 11:30 AMMachine Learning in Space, Earth & Atmospheric SciencesOral
Solar active region detection from high-cadence EUV imagery is important for data-driven space weather monitoring, yet robust pixel-level characterization remains challenging because active and non-active bright structures can overlap in intensity and morphology. We present an interpretable machine-learning framework for solar active region detection in 193 Å images from the Atmospheric...
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Alisson Dal Lago (INPE - National Institute for Space Research)8/18/26, 2:40 PMInstrumentation & Observational SystemsOral
One important topic within Heliophysics is the modulation of <100GeV cosmic rays due to solar activity. Since 2001, a prototype of a multidirectional muon detector is in operation at the Southern Space Observatory, in Sao Martinho da Serra (SMS), Brazil. It is part of the Global Muon Detector Network (GMDN), composed by detectors in Nagoya (Japan), Kingston (Australia), Sao Martinho da Serra...
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Alexandre da Silva Santos (Federal University of Maranhão), Roger Pinheiro Presoti (Universidade Federal do Maranhão (UFMA))8/18/26, 3:00 PMMachine Learning in Space, Earth & Atmospheric SciencesOral
Deep space missions beyond Low Earth Orbit expose crews to significant doses of galactic cosmic radiation (GCR), composed of high-energy protons and high-atomic-number, high-energy (HZE) ions including ⁵⁶Fe, ²⁸Si, ⁴⁸Ti, ¹⁶O, and ⁴He. Unlike the protection offered by Earth's magnetosphere, GCR cannot be attenuated by available spacecraft materials, and its cumulative effects on the central...
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Mariano Sanchez Toledo (Grupo de Estudios en Heliofísica de Mendoza, Universidad de Mendoza, Mendoza, Argentina)8/18/26, 3:20 PMMachine Learning in Space, Earth & Atmospheric SciencesOral
The study of space weather critically depends on the three-dimensional (3D) morphological and kinematic characterization of coronal mass ejections (CMEs). This process can be done via generic 3D point position estimation (using e.g., tie-pointing plus triangulation, differential emission measure tomography, polarization ratio or neural radiation fields techniques) or model-based 3D...
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Eduardo Ferraz de Campos (Federal Institute of São Paulo)8/19/26, 3:00 PMMachine Learning in Space, Earth & Atmospheric SciencesOral
Forecasting solar flares is essential for mitigating space weather risks that threaten technological infrastructures. This research investigated the most relevant attributes for predicting solar flares by comparing the predictive performance of models based on two different predictive philosophies: an "Effect-to-Effect" approach based on X-ray inertia, and a "Cause-to-Effect" approach focused...
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Dr Matheus Alves de Barros (Topotech - Soluções em Topografia e Georreferenciamento)8/19/26, 4:50 PMMachine Learning in Space, Earth & Atmospheric SciencesOral
The stability of tailings storage structures represents one of the major challenges in contemporary geotechnical engineering, particularly considering the environmental, social, and economic impacts associated with geotechnical failures. The increasing adoption of filtered tailings systems and dry stacking methods has expanded the use of tailings piles as an alternative to conventional...
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95. A CNN Classifier for Hidden Solar Flares in Historical UV Spectroscopic Plates From Skylab SO82BTiago Mendes Ferrer (@Mackenzie), Paulo Simões (Universidade Presbiteriana Mackenzie)8/19/26, 5:10 PMMachine Learning in Space, Earth & Atmospheric SciencesOral
The NRL SO82B spectrograph on board of Skylab captured more than 6,000 far-ultraviolet photographic exposures of the Sun between 1973 and 1974. UV flare spectra are still rare with only a few reported during the mission. This work presents a supervised binary image classifier based on a ResNet-18 convolutional neural network (CNN) to identify uncatalogued flares in the SO82B data. The CNN was...
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Nouhaïla Bouhadi8/20/26, 9:40 AMMachine Learning in Space, Earth & Atmospheric SciencesOral
We investigated the ionospheric response to the 17 March 2015 geomagnetic storm, the most severe event of solar cycle 24 (SYM-H = -233 nT), using GPS-derived total electron content (TEC) observations from the RABT station in Morocco (34°N, 7°W). Vertical TEC (VTEC) was derived from dual-frequency GPS measurements using differential code bias corrections and a 30° elevation cutoff. The results...
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Besma Guesmi (Ubotica Technologies)8/20/26, 11:50 AMSpace Weather Forecasting & OperationsOral
In the evolving landscape of 21st-century space science, forecasting space weather events such as solar flares and Coronal Mass Ejections (CMEs) are crucial yet challenging. Solar flares are intense bursts of radiation caused by the release of magnetic energy in active regions and are often accompanied by CMEs. These events can significantly impact Earth’s space environment, causing...
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Caroline Botelho (Instituto Nacional de Pesquisas Espaciais), PAULO RICARDO JAUER (Instituto Nacional de Pesquisas Espaciais INPE)8/20/26, 2:40 PMHeliophysics & Space WeatherOral
This work aims to identify and characterize the critical Alfvén surface, which marks the boundary of the solar corona. Within this surface, the solar plasma is in a sub-Alfvénic regime, whereas beyond it, the solar wind becomes super-Alfvénic. The study presents theoretical foundations on the solar structure, plasma characteristics and Alfvén waves in the solar corona. The analysis was...
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Solomon Perriyil (Centro de Rádio-Astronomia e Astrofísica Mackenzie - CRAAM)Heliophysics & Space WeatherOral
Accurate and timely detection of solar flares is essential for advancing our understanding of solar activity and improving space weather forecasting capabilities. In this work, we evaluate the performance of an automated flare identification system by comparing its trigger outputs against two independent solar flare catalogs. The analysis highlights how detection performance depends critically...
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Akshita Bhardwaj (Indian institute of technology Roorkee)Machine Learning in Space, Earth & Atmospheric SciencesOral
Dusty plasma comprises charged dust particles, ions, electrons, etc. They are prevalent outside of Earth as well. In this work, we aim to study the plasma environment outside of Jupiter. Specifically, the shock waves that form when solar wind interacts with Jupiter’s magnetosphere. We also draw comparisons from shock waves in Earth’s and Saturn’s magnetospheres. The methodology comprises Lie...
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Dr Jean Carlo Santos (instituto nacional de pesquisas espaciais)Heliophysics & Space WeatherOral
Solar filaments are dark, thread-like structures of cool, dense plasma seen on the Suns’s surface. They usually mark a boundary between two opposite magnetic regions and may last for multiple days, changing their form, but eventually they vanish. Their disappearance may end up with a CME associated with geomagnetic storms that affect the geospace. Therefore filament tracking is an important...
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Quan Wang (National Astronomical Observatories of the Chinese Academy of Sciences)Heliophysics & Space WeatherOral
Magnetic helicity is an important concept in solar physics, with a number of theoretical statements pointing out the important role of magnetic helicity in solar flares and coronal mass ejections (CMEs). Here we construct a sample of 47 solar flares, which contains 18 no-CME-associated confined flares and 29 CME-associated eruptive flares. We calculate the change ratios of magnetic helicity...
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Raul Toscano FariaSpace Weather Forecasting & OperationsOral
Solar flares represent a major focus in space weather research due to their potential to disrupt satellite operations and critical terrestrial technologies. These phenomena are characterized by rapid variations in X-ray flux, resulting in intense energy releases within the solar atmosphere. To better understand their behavior, this study has utilized the sunpy library to access the X-ray flux...
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Nicolas Campos (Universidad de Santiago de Chile (USACH))Machine Learning in Space, Earth & Atmospheric SciencesOral
Solar flares are transient energy release events in the solar atmosphere, typically associated with magnetic reconnection in active regions. While the Geostationary Operational Environmental Satellite X-ray Sensor (GOES/XRS) provides continuous monitoring of flare activity, its lack of spatial resolution limits the identification, localization, and characterization of flaring events. In this...
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Dr Eduardo Flandez (Universidad de Chile)Heliophysics & Space WeatherOral
This study investigates how magnetic reconnection reshapes coronal-hole (CH) boundaries during eruptive events. Using high-cadence EUV and magnetogram observations from the Solar Dynamics Observatory on 2015 June 4, we apply Correlation Dimension Mapping (CDM), a technique designed to quantify the geometric complexity of CH boundaries across multiple spatial scales.
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We find that localized jet... -
Dr Balveer Singh Rathore (Government Holkar Science College, Indore)Space Weather Forecasting & OperationsOral
Today’s challenge for space weather research is to quantitatively predict the
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dynamics of the magnetosphere from measured solar wind and interplanetary mag
netic field (IMF) conditions. Correlative studies between geomagnetic storms (GMSs)
and the various interplanetary (IP) field/plasma parameters have been performed to
search for the causes of geomagnetic activity and develop models for... -
Reinaldo Rosa (National Institute for Space Research (INPE))Space Weather Forecasting & OperationsOral
Operational space weather monitoring requires not only accurate forecasts but also transparent and interpretable decision support tools. We present an Explainable Artificial Intelligence (XAI) prototype designed for the EMBRACE-INPE environment. The system integrates GOES X-ray flux, SYM-H index, and AE index, capturing the causal propagation from solar activity to geomagnetic and auroral...
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Marco Antonio Ridenti (Instituto Tecnológico de Aeronáutica)Space Weather Forecasting & OperationsOral
The ionosphere poses challenges for accurate forecasting due to its complexity and variability. Irregularities in the lower ionosphere are influenced by local time, season, geographic location, solar activity and space weather, complicating precise predictions. However, understanding this region is crucial for radio communication, navigation and Global Navigation Satellite System (GNSS)...
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Suzana Silva (University of Sheffield)Heliophysics & Space WeatherOral
Coronal mass ejections are well-established drivers of large-scale wave phenomena in the low corona, yet the wave dynamics operating in the extended corona and inner heliosphere have remained almost entirely unexplored. We report here the first combined observational and numerical evidence of coherent, global compressive oscillations propagating through the outer corona and inner heliosphere. ...
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Abhilash Sarwade (U. R. Rao Satellite Centre, ISRO)Machine Learning in Space, Earth & Atmospheric SciencesOral
Solar Low-Energy X-ray Spectrometer (SoLEXS) is a Sun-as-a-star payload onboard the Aditya-L1 mission designed to monitor solar coronal emissions and flare energetics. It has been in continuous operation at the L1 Lagrangian point for almost two years, capturing solar soft X-ray (SXR) spectra at a 1-second cadence. The stability of the instrument and its observing conditions has produced a...
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javier silva (Instituto Nacional de Pesquisas Espaciais)Machine Learning in Space, Earth & Atmospheric SciencesOral
In this study, we applied machine learning techniques to perform an unsupervised clustering of THEMIS satellite orbits to detect magnetosheath crossings. We used the DBSCAN algorithm to analyze crossings within a range of less than 40 Earth radii, focusing on data from the THEMIS-B (THB) and THEMIS-C (THC) spacecraft during 2008 and 2009. These spacecraft were selected due to their eccentric...
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Leonardo MollietSpace Weather Forecasting & OperationsOral
Low Earth Orbit (LEO) satellites, such as Brazil’s Amazonia-1, are subject to atmospheric drag resulting from
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variations in thermospheric density, which intensify during periods of elevated solar activity. This study
investigates how space weather phenomena—specifically geomagnetic storms and solar flares—influence the
orbital decay of Amazonia-1 between 2021 and 2023. Real orbital data... -
Raphael Malagoli Thereza (Universidade Presbiteriana Mackenzie - CRAAM)Heliophysics & Space WeatherOral
The flux of Galactic Cosmic Rays (GCR) reaching the solar atmosphere is a key ingredient for studies of heliospheric modulation and secondary-particle production. The transport of charged particles in the interplanetary medium is commonly described by Parker’s transport equation (Parker, 1965), which provides the theoretical framework for diffusion, convection by the solar wind,...
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Felipe Portela Aguilar de Oliveira (Christianne Andrea Portela Aguilar)Autonomous Platforms & Remote SensingOral
The increasing reliance on Commercial Off-The-Shelf (COTS) components for small satellite propulsion and suborbital platforms, such as the Brazilian Suborbital Microgravity Platform (PSM), introduces significant vulnerabilities to space weather phenomena. This study investigates the intersection between heliophysics data and the operational reliability of electrospray propulsion systems and...
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Nouhaïla BouhadiHeliophysics & Space WeatherOral
We investigated the ionospheric response to the geomagnetic storm of March 17, 2015, using GPS total electron content (TEC) measurements from the IGS station RABT in Rabat, Morocco (34°N, 7°W). This storm, with a minimum SYM-H of -233 nT, was the most severe of solar cycle 24. Vertical TEC was derived from dual-frequency pseudorange measurements using a single-layer mapping function (H=350...
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Dr Liyue Tong (National Astronomical Observatory of the Chinese Academy of Sciences)Instrumentation & Observational SystemsOral
Solar observation faces complex challenges that conventional automated observation systems struggle to address, including rapidly changing weather conditions, potentially anomalous data, and the need for prompt follow-up observations of eruptive phenomena. The rapid advancement of artificial intelligence technologies offers new possibilities for tackling these challenges. This paper presents...
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Isaac Wright (University of Texas at Dallas)Machine Learning in Space, Earth & Atmospheric SciencesOral
Ionospheric scintillation refers to rapid phase and amplitude fluctuations of radio signals as they pass through ionospheric irregularities. While commercial scintillation monitors have been used extensively to study scintillation, their relatively high costs have limited scientific use. To address this, we have been developing low-cost scintillation monitors based on single-board computers...
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Marjori Klinczak (Unifatec)Machine Learning in Space, Earth & Atmospheric SciencesOral
This study presents a benchmark of machine learning models for forecasting geomagnetic indices, specifically Kp and Dst, using NASA’s OMNI dataset with hourly resolution over the period from 2015 to 2024. The input variables include solar wind parameters and interplanetary magnetic field components, such as total magnetic field intensity, Bx, By, and Bz components, solar wind speed and...
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Allen John Darin J (Mahendra Engineering College)Machine Learning in Space, Earth & Atmospheric SciencesOral
Satellite thermal management systems are critical for maintaining the operational integrity of spacecraft, yet they are typically designed as reactive systems. This study presents a novel methodology for predictive thermal health monitoring using Physics-Informed Neural Networks (PINNs) to safeguard satellites against extreme space weather events. The primary objective is to differentiate...
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Sergey Nikiforov (NYUAD)Machine Learning in Space, Earth & Atmospheric SciencesOral
Modeling the Martian nightside thermosphere is challenging due to the absence of direct solar illumination and highly irregular in-situ sampling. We present a multi task physics informed neural network (MT-PINN) trained on more than a decade of MAVEN/NGIMS observations (MY 32-38) to reconstruct the densities of O, CO₂, N₂, and Ar. To represent coupling with space weather drivers, the model...
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Andre O. Kovacs (Center for Radio Astronomy and Astrophysics Mackenzie (CRAAM))Machine Learning in Space, Earth & Atmospheric SciencesOral
Context. The solar and stellar magnetic activity can cause spots and faculae on the photosphere that imprints variability signals on its brightness. Many different approaches have been proposed in the literature to reconstruct the signals of magnetic activity on the stellar surface from the brightness measurements, such as Doppler imaging, photometric surface mapping, and planetary transit...
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Manjunath Hegde (Indian Institute of Astrophysics)Space Weather Forecasting & OperationsOral
Coronal mass ejections (CMEs) are significant drivers of space weather, and accurately predicting their propagation speed is crucial for mitigating their impact on Earth’s environment. In this study, we leverage machine learning techniques to model and predict CME speed at 20R utilizing data from the Coordinated Data Analysis Workshop catalog. We considered data from Solar Cycles 23 and 24,...
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Daniele da Silva Ferreira Medeiros (CBJLSW/INPE)Machine Learning in Space, Earth & Atmospheric SciencesOral
Magnetic reconnection is a fundamental physical process that occurs in magnetized plasmas and serves as an efficient mechanism for accelerating charged particles by converting magnetic energy into kinetic and thermal energy. In the interaction between the solar wind and Earth's magnetosphere, particularly during periods of southward interplanetary magnetic field orientation (Bz < 0), magnetic...
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Dr Juan Jesús Soria-Quijaite (Escuela Profesional de Ingeniería Ambiental, Universidad Peruana Unión, Lima, 150118, Perú), Dr Manuel A. Bravo (Centro de Instrumentación Científica, Universidad Adventista de Chile, Chillán, 3780000, Chile), Orlando Poma Porras (Escuela Profesional de Ingeniería Ambiental, Universidad Peruana Unión, Lima, 150118, Perú)Space Weather Forecasting & OperationsOral
Atmospheric electric field forecasting represents a significant challenge in space weather monitoring applications due to the complex interaction among geomagnetic disturbances, atmospheric dynamics, and local meteorological variability. This study proposes a hybrid machine learning model based on Stacking Ensemble Learning for atmospheric electric field forecasting using geomagnetic and...
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