COVEN: Providing a Variety of Threshold‐Based Forecasts for the Outer Radiation Belt
Abstract We present a suite of VAMPIRE (Van Allen belt Multi‐day Predictions by Implementing a Random Forest for Electrons) models capable of predicting if the outer radiation belt crosses set percentile thresholds. We use Random Forest classification models to predict if the daily ∼2 MeV electron flux level across the outer radiation belt exceeds ...
D. J. Weston +3 more
wiley +1 more source
Detection of pre-seismic magnetic field anomalies using Swarm satellite data: a case study of the 2025 Mw7.7 Myanmar earthquake. [PDF]
Alimoradi H, Rahimi H, De Santis A.
europepmc +1 more source
Multi‐Wavelength Transformer‐Based 24‐Hour Solar Flare Forecasting at the Active‐Region Level
Abstract Solar flare forecasting remains challenging due to the complex spatiotemporal evolution of solar active regions (ARs) and the severe class imbalance associated with high‐impact events. In this work, we investigate a transformer‐based framework for active‐region–level solar flare forecasting using short sequences of multi‐wavelength ...
Dunia Alatoom, Nikos Nikolaou
wiley +1 more source
Exploring the Potential Observations Between Geomagnetic Activity and Cardiovascular Events: A Scoping Review. [PDF]
Belenko J, Cancel G, Mayrovitz HN.
europepmc +1 more source
Investigating Potential Benefits of Future Sub‐L1 Missions With STEREO‐A
Abstract We present the first statistical study of geomagnetic storm forecasting using in situ data from the STEREO‐A spacecraft as a sub‐L1 monitor. Between November 2022 and June 2024, STEREO‐A crossed the Sun–Earth line, covering longitudinal and radial separations of ±15° $\pm 15{}^{\circ}$ from the Sun–Earth line and 0.01–0.06 au from Earth.
E. Weiler +6 more
wiley +1 more source
The spatiotemporal development of the midlatitude troughs and subauroral ion drift during a geomagnetic storm observed by multiple DMSP satellites. [PDF]
Cha H +4 more
europepmc +1 more source
Comprehensive Validation of Novel Deep Learning Architectures to Forecast Geomagnetic Substorms
Abstract Magnetic substorms are disturbances in the terrestrial magnetosphere that can have significant space weather impacts, although forecasting their onset accurately remains an open problem. In this study, we develop multiple novel machine learning architectures based on convolutional neural networks, long short‐term memory networks, extreme ...
A. Essop, N. Mbatha, J. A. E. Stephenson
wiley +1 more source
A hybrid statistical-machine learning framework for evaluating geomagnetic storm effects on MisrSat2 satellite power subsystems. [PDF]
Mostafa MS +5 more
europepmc +1 more source
An HHT–ANN Framework for Short‐Term Kp Forecasting
Abstract The geomagnetic activity index Kp is an important indicator of solar wind–magnetosphere coupling, and accurate 3‐hr‐ahead forecasting is important for space‐weather monitoring and warning. Because upstream solar wind and interplanetary magnetic field (IMF) signals are strongly nonlinear and nonstationary, methods based only on conventional ...
P. Yang +5 more
wiley +1 more source
User-Side Long-Baseline Undifferenced Network RTK Positioning Under Geomagnetic Storm Conditions Using a Power Spectral Density-Constrained Ionospheric Delay Model. [PDF]
Wang Y, Zhu H, Xu Q, Li J, Song C, Li B.
europepmc +1 more source

