Aug 17 – 21, 2026
National Institute for Space Research, São José dos Campos, SP, Brazil
America/Sao_Paulo timezone

Session

Oral Contributions

Aug 17, 2026, 2:40 PM
Fernando de Mendonça - LIT (National Institute for Space Research, São José dos Campos, SP, Brazil)

Fernando de Mendonça - LIT

National Institute for Space Research, São José dos Campos, SP, Brazil

Av. dos Astronautas, 1758 - Jardim da Granja, São José dos Campos - SP, 12227-010

Conveners

Oral Contributions

  • Paulo Simões (Universidade Presbiteriana Mackenzie)
  • Daniele da Silva Ferreira Medeiros (CBJLSW/INPE)

Oral Contributions: Heliophysics & Space Weather

  • Icaro da Silva Vieira (Unicamp)
  • Luis Eduardo Antunes Vieira (Instituto Nacional de Pesquisas Espaciais)
  • Robert Jarolim (High Altitude Observator, NSF NCAR)

Oral Contributions

  • Adriany Barbosa (INPE)
  • Bruno Fernandes Garcia

Oral Contributions

  • Marcos Silveira (INPE)
  • PAULO RICARDO JAUER (Instituto Nacional de Pesquisas Espaciais INPE)

Oral Contributions

  • Adriany Barbosa (INPE)
  • Reinaldo Rosa (National Institute for Space Research (INPE))

Oral Contributions

  • Icaro da Silva Vieira (Unicamp)
  • Hadassa Raquel Peixoto Jácome (INPE)

Oral Contributions

  • Ivana Yoshie Sumida (INPE)
  • David Jess (Queen's University Belfast)

Oral Contributions

  • Victor Pinto (Universidad de Santiago de Chile)
  • Jean Santos (instituto nacional de pesquisas espaciais)

Oral Contributions

  • Francisco Iglesias (CONICET)
  • Marcos Silveira (INPE)

Oral Contributions

  • Luis Eduardo Antunes Vieira (Instituto Nacional de Pesquisas Espaciais)
  • Tino Riethmüller

Oral Contributions

  • Franciele Carlesso (INPE)
  • Ricardo Cotrin Teixeira (INPE)

Oral Contributions

  • Hadassa Raquel Peixoto Jácome (INPE)
  • Paulo Ernesto Marchezi (Unicamp)

Presentation materials

There are no materials yet.

  1. Abhilash Sarwade (U. R. Rao Satellite Centre, ISRO)
    8/17/26, 2:40 PM
    Machine Learning in Space, Earth & Atmospheric Sciences
    Oral

    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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  2. Idowu Raji (National Institute for Space Research (INPE))
    8/17/26, 3:00 PM
    Machine Learning in Space, Earth & Atmospheric Sciences
    Oral

    F10.7 is a solar radio flux measured at a wavelength of 10.7, which represents the vital proxy of solar activity. In this study, the impact of solar ultraviolet (UV) radiation on the upper atmosphere of Earth is considered by F10.7. This study aims to develop a predictive system for solar radio flux at F10.7 for short-term prediction from 1 to 3 days ahead. We implemented a multi-stage...

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  3. soumya shree sadangaya
    8/17/26, 3:20 PM
    Heliophysics & Space Weather
    Oral

    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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  4. Marco Antonio Ridenti (Instituto Tecnológico de Aeronáutica)
    8/17/26, 4:50 PM
    Space Weather Forecasting & Operations
    Oral

    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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  5. Leonardo Molliet
    8/17/26, 5:10 PM
    1
    Space Weather Forecasting & Operations
    Oral

    Low Earth Orbit (LEO) satellites, such as Brazil’s Amazonia-1, are subject to atmospheric drag resulting from
    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...

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  6. Yuliang Shen (naoc)
    8/18/26, 9:40 AM
    1
    Instrumentation & Observational Systems
    Oral

    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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  7. Dr Liyue Tong (National Astronomical Observatory of the Chinese Academy of Sciences)
    8/18/26, 10:00 AM
    Instrumentation & Observational Systems
    Oral

    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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  8. 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)
    8/18/26, 10:20 AM
    Space Weather Forecasting & Operations
    Oral

    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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  9. Reinaldo Rosa (National Institute for Space Research (INPE))
    8/18/26, 11:50 AM
    Space Weather Forecasting & Operations
    Oral

    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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  10. Isaac Wright (University of Texas at Dallas)
    8/18/26, 12:10 PM
    Machine Learning in Space, Earth & Atmospheric Sciences
    Oral

    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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  11. Alisson Dal Lago (INPE - National Institute for Space Research)
    8/18/26, 2:40 PM
    Instrumentation & Observational Systems
    Oral

    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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  12. Alexandre da Silva Santos (Federal University of Maranhão), Roger Pinheiro Presoti (Universidade Federal do Maranhão (UFMA))
    8/18/26, 3:00 PM
    Machine Learning in Space, Earth & Atmospheric Sciences
    Oral

    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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  13. Mariano Sanchez Toledo (Grupo de Estudios en Heliofísica de Mendoza, Universidad de Mendoza, Mendoza, Argentina)
    8/18/26, 3:20 PM
    Machine Learning in Space, Earth & Atmospheric Sciences
    Oral

    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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  14. José Matheus Rocha (INPE)
    8/18/26, 4:50 PM
    Heliophysics & Space Weather
    Oral

    Understanding the solar photospheric magnetic field is vital for space weather forecasting. While Milne-Eddington (ME) inversion of spectropolarimetric data (Stokes I, Q, U, V for Fe I lines) is the standard for retrieving atmospheric parameters, it is computationally expensive, often taking hours per active region map on standard computers. To overcome this bottleneck, we apply a...

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  15. Dr OLUDEHINWA Irewola Aaron (Department of Physics, Federal University of Agriculture, Abeokuta, Nigeria.)
    8/18/26, 5:10 PM
    Machine Learning in Space, Earth & Atmospheric Sciences
    Oral

    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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  16. Besma Guesmi (Ubotica Technologies)
    8/19/26, 9:40 AM
    Space Weather Forecasting & Operations
    Oral

    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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  17. Nicolas Campos (Universidad de Santiago de Chile (USACH))
    8/19/26, 10:00 AM
    Machine Learning in Space, Earth & Atmospheric Sciences
    Oral

    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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  18. Solomon Perriyil (Centro de Rádio-Astronomia e Astrofísica Mackenzie - CRAAM)
    8/19/26, 10:20 AM
    Heliophysics & Space Weather
    Oral

    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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  19. Quan Wang (National Astronomical Observatories of the Chinese Academy of Sciences)
    8/19/26, 11:50 AM
    Heliophysics & Space Weather
    Oral

    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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  20. Raphael Malagoli Thereza (Universidade Presbiteriana Mackenzie - CRAAM)
    8/19/26, 12:10 PM
    Heliophysics & Space Weather
    Oral

    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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  21. Andre O. Kovacs (Center for Radio Astronomy and Astrophysics Mackenzie (CRAAM))
    8/19/26, 2:00 PM
    Machine Learning in Space, Earth & Atmospheric Sciences
    Oral

    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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  22. Bruno Fernandes Garcia
    8/19/26, 2:20 PM
    Heliophysics & Space Weather
    Oral

    We present a data-driven and artificial intelligence-based method for the three-dimensional characterization of magnetic field lines in the solar atmosphere, applied to NOAA AR 3663, one of the most complex and eruptive active regions of Solar Cycle 25. The method is based on the extrapolation of the nonlinear force-free coronal magnetic field (NLFFF) via Physically Informed Neural Networks...

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  23. Marjori Klinczak (Unifatec)
    8/19/26, 2:40 PM
    Machine Learning in Space, Earth & Atmospheric Sciences
    Oral

    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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  24. Eduardo Ferraz de Campos (Federal Institute of São Paulo)
    8/19/26, 3:00 PM
    Machine Learning in Space, Earth & Atmospheric Sciences
    Oral

    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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  25. Dr Jean Carlo Santos (instituto nacional de pesquisas espaciais)
    8/19/26, 3:20 PM
    Heliophysics & Space Weather
    Oral

    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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  26. Thiago Sant Anna (National Observatory (ON))
    8/19/26, 4:10 PM
    Space Weather Forecasting & Operations
    Oral

    The main factors governing the variability patterns of high-energy electron flux in the outer radiation belt are well established in the literature and are modulated by external physical mechanisms. These correspond to different solar wind structures, such as Interplanetary Coronal Mass Ejections (ICMEs) and High-Speed Solar Wind Streams (HSSs). These processes are associated with low-energy...

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  27. Besma Guesmi (Ubotica Technologies)
    8/19/26, 4:30 PM
    Space Weather Forecasting & Operations
    Oral

    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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  28. javier silva (Instituto Nacional de Pesquisas Espaciais)
    8/19/26, 4:50 PM
    Machine Learning in Space, Earth & Atmospheric Sciences
    Oral

    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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  29. Tiago Mendes Ferrer (@Mackenzie), Paulo Simões (Universidade Presbiteriana Mackenzie)
    8/19/26, 5:10 PM
    Machine Learning in Space, Earth & Atmospheric Sciences
    Oral

    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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  30. Mr Hugo Bernardes (INPE - Instito Nacional de Pesquisas Espaciais)
    8/20/26, 9:40 AM
    Instrumentation & Observational Systems
    Poster

    This work presents a study on optical neural network implementations aimed at contributing to adaptive optics applications for ground-based telescopes. The tests and proposals focus on solar telescopes. The approach offers processing-time advantages, as the systems involve optical stages for image interpretation that operate at the speed of light. Optical systems are proposed to assist in...

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  31. Felipe Portela Aguilar de Oliveira (Christianne Andrea Portela Aguilar)
    8/20/26, 10:00 AM
    Autonomous Platforms & Remote Sensing
    Oral

    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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  32. Daniele da Silva Ferreira Medeiros (CBJLSW/INPE)
    8/20/26, 10:20 AM
    Machine Learning in Space, Earth & Atmospheric Sciences
    Oral

    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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  33. Manjunath Hegde (Indian Institute of Astrophysics)
    8/20/26, 2:00 PM
    Space Weather Forecasting & Operations
    Oral

    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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  34. Caroline Botelho (Instituto Nacional de Pesquisas Espaciais), PAULO RICARDO JAUER (Instituto Nacional de Pesquisas Espaciais INPE)
    8/20/26, 2:20 PM
    Heliophysics & Space Weather
    Oral

    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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  35. Yasmin Machuca (CONICET - Grupo de Estudios en Heliofísica de Mendoza - Universidad de Mendoza)
    8/20/26, 2:40 PM
    Machine Learning in Space, Earth & Atmospheric Sciences
    Oral

    Coronal Mass Ejections (CMEs) are critical drivers of space weather, requiring precise kinematic and morphological characterization to predict their geoeffectiveness. We previously demonstrated that fine-tuning the deep neural model Mask R-CNN on synthetic CME images, generated via Graduated Cylindrical Shell (GCS) shapes and raytracing, allows the automated segmentation of CME outer envelopes...

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