Search arXiv⌕ Search
Home/Archive/arXiv

arXiv · 2609.23725

Interhemispheric differences in field-aligned currents, ground magnetic perturbations, and TEC during the geomagnetic storms of May and October 2024

Sumanjit Chakraborty·Gopi K. Seemala
View original source ↗Read source document ↗Export metadata ↓

Abstract

This study investigates storm-to-storm variability and hemispheric differences in magnetosphere-ionosphere (MI) coupling during the extreme (G5) geomagnetic storm of May 10-11 and the severe (G4) storm of October 10-11, 2024. Global field-aligned current (FAC) patterns derived from the Active Magnetosphere and Planetary Dynamics Response Experiment (AMPERE), together with conjugate observations from ground-based magnetometers within the SuperMAG network and Global Positioning System (GPS)-derived total electron content (TEC), are analyzed to examine high-latitude electrodynamic and ionospheric responses in both hemispheres. The May event exhibits broad and relatively organized Region 1/Region 2 FAC systems encircling the polar caps across multiple local time sectors, accompanied by intervals of correspondence in conjugate magnetic perturbations and structured TEC enhancements with temporal offsets between hemispheres. In contrast, the October event shows more localized, asymmetric, and uneven FAC morphology with pronounced hemispheric and dawn-dusk asymmetries, together with greater divergence in conjugate magnetic responses and spatially heterogeneous TEC variability. These differences are consistent with enhanced mesoscale variability and asymmetric current closure under storm-time conditions. Overall, the results highlight that even under similarly strong solar wind driving, the coupled MI system can exhibit substantially different spatial organization and interhemispheric coupling, reflecting the combined influence of FAC morphology, ionospheric conductance, and local electrodynamic conditions.

Explore related subjects

physics.space-phastro-ph.EPastro-ph.SRphysics.geo-ph

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Sumanjit Chakraborty, Gopi K. Seemala. 2026-09-20. Interhemispheric differences in field-aligned currents, ground magnetic perturbations, and TEC during the geomagnetic storms of May and October 2024. https://arxiv.org/abs/2609.23725

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

arXiv2026

Coordinate Systems and Transforms in Space Physics: Terms, Definitions, Implementations, and Recommendations for Reproducibility

In space physics, acronyms for coordinate systems (e.g., \texttt{GEI}, \texttt{GSM}) are commonly used; however, differences in their definitions and implementations can prevent reproducibility. In this work, we compare definitions in online resources, software packages, and frequently cited journal articles and show that implementation differences can lead to transformations between same-named coordinate systems and position values from different data providers to differ significantly. Based on these comparisons and results, and to enable reproducibility, we recommend that (a) a standard for acronyms and definitions for coordinate systems is developed, similar to equivalents in astronomy or earth sciences; (b) a standards body develops a citable database of reference data needed for these transforms. For software that computes coordinate transforms, we also recommend that their developers provide explicit comparisons of their implementations with the results of (b) and documentation on implementation choices. Additionally, we provide recommendations for scientists and metadata developers to ensure that sufficient information is provided to enable reproducibility. Finally, we document that spacecraft positions from data providers can differ both because of differences in how they implemented transforms and because of differences in the original source of the position data, and provide recommendations to improve the documentation of spacecraft positional datasets.

physics.space-ph↗
arXiv2026

Aurora Hunter: A Two-Stage Framework for Probabilistic Visibility Forecasting

Aurora visibility at a given location requires two physically distinct conditions to hold at once: aurora occurring overhead, governed by solar wind-magnetosphere coupling, and observing conditions that permit detection, governed by cloud cover and moonlight. Approaches that conflate the two weaken the space-weather signal and limit cross-site generalizability. We develop Aurora Hunter, a two-stage cascade that separates occurrence prediction from observing-condition assessment. Stage 1 uses 43 physics-driven features to predict P(aurora identifiable in all-sky images) via gradient-boosted trees trained on joint Tromso+Kiruna data (about 16,600 hours, 2015-2023). Stage 2 models P(unobscured image class | identifiable) with logistic regression on 15 observing-condition features, trained on hours with identifiable aurora. The cascade P(visible) = P(identifiable) x P(unobscured | identifiable) achieves retrospective ROC-AUC of 0.958 (Tromso test, 2019-2020) and 0.933 (independent Kiruna, 2024), improving on the occurrence stage used alone by +0.095 and +0.097. Transfer to Skibotn, the one station withheld entirely (2022-2025), is limited. SHAP analysis identifies magnetic local time, the Kp x nightside interaction and the three-hour mean Kp as the dominant features (44% of attribution), consistent with auroral oval physics. Hemisphere-wide occurrence maps combine the Stage 1 amplitude, on a clear-sky basis, with the Feldstein oval parameterization. By providing location-specific visibility probabilities with measured reliability rather than coarse geomagnetic indices, the framework links space weather research to practical observation planning. An operational proof of concept is available at https://aurora-hunter.onrender.com

physics.space-ph↗
arXiv2026

Predicting low-latitude ionospheric Total Electron Content (TEC) over the Indian sector under variable space weather conditions using solar wind parameters

Accurate prediction of ionospheric Total Electron Content (TEC) during geomagnetically disturbed conditions remains challenging, particularly when empirical models perform poorly during storms and neural network (NN) approaches rely explicitly on geomagnetic indices such as Kp/Ap or Dst/SYM-H. In this study, we develop an NN-based model to predict TEC variations over the Indian longitude sector without incorporating geomagnetic indices as inputs. The model is trained on the full-year (2024) Global Ionospheric Map (GIM) TEC dataset at a 15-minute cadence, together with solar wind parameters: Interplanetary Magnetic Field (IMF) $B_z$, velocity ($V_{sw}$), and density ($N_p$), along with the F10.7 cm solar radio flux. Seasonal and diurnal variability are represented using sinusoidal transformations of Day of Year (DOY) and hour of day (HOD). An optimized architecture with 96 hidden neurons yields strong training performance ($R^2$ $\sim$ 0.96, RMSE $\sim$ 5.4, and MAE $\sim$ 3.8 TECU). Independent predictions for the year 2025 demonstrate robust generalization under both quiet and geomagnetically active conditions. Quiet-time residuals are generally confined within $\pm$10 TECU, while during moderate and strong storm-time conditions, the model maintains comparable error bounds across most of the Indian region, despite not being trained on geomagnetic indices. The results indicate that solar wind parameters, combined with the F10.7 solar flux and cyclical temporal encoding, contain sufficient information to reproduce geomagnetic storm-time TEC variability. This study therefore demonstrates the applicability of the proposed approach for regional TEC prediction and ionospheric nowcasting, with potential applications in GNSS positioning, satellite navigation, radio communication systems, and the future development of operational ionospheric forecasting tools.

physics.space-ph↗