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Sudden Commencements and Geomagnetically Induced Currents in New Zealand: Correlations and Dependance
A. W. Smith, C. J. Rodger, D. H. Mac Manus, I. J. Rae, A. R. Fogg, C. Forsyth, P. Fisher, T. Petersen and M. Dalzell Space Weather 22(1) (2024) https://doi.org/10.1029/2023SW003731
Physics-Enhanced TinyML for Real- Time Detection of Ground Magnetic Anomalies
The Response of Ionospheric Currents to External Drivers Investigated Using a Neural Network‐Based Model
Xin Cao, Xiangning Chu, Jacob Bortnik, James M. Weygand, Jinxing Li, Homayon Aryan and Donglai Ma Space Weather 21(9) (2023) https://doi.org/10.1029/2023SW003506
A Survey of Uncertainty Quantification in Machine Learning for Space Weather Prediction
On the Considerations of Using Near Real Time Data for Space Weather Hazard Forecasting
A. W. Smith, C. Forsyth, I. J. Rae, T. M. Garton, C. M. Jackman, M. Bakrania, R. M. Shore, G. S. Richardson, C. D. Beggan, M. J. Heyns, J. P. Eastwood, A. W. P. Thomson and J. M. Johnson Space Weather 20(7) (2022) https://doi.org/10.1029/2022SW003098
The Correspondence Between Sudden Commencements and Geomagnetically Induced Currents: Insights From New Zealand
A. W. Smith, C. J. Rodger, D. H. Mac Manus, C. Forsyth, I. J. Rae, M. P. Freeman, M. A. Clilverd, T. Petersen and M. Dalzell Space Weather 20(8) (2022) https://doi.org/10.1029/2021SW002983
Global Geomagnetic Perturbation Forecasting Using Deep Learning
Vishal Upendran, Panagiotis Tigas, Banafsheh Ferdousi, Téo Bloch, Mark C. M. Cheung, Siddha Ganju, Asti Bhatt, Ryan M. McGranaghan and Yarin Gal Space Weather 20(6) (2022) https://doi.org/10.1029/2022SW003045
Multi-Variate LSTM Prediction of Alaska Magnetometer Chain Utilizing a Coupled Model Approach
Forecasting GICs and Geoelectric Fields From Solar Wind Data Using LSTMs: Application in Austria
R. L. Bailey, R. Leonhardt, C. Möstl, C. Beggan, M. A. Reiss, A. Bhaskar and A. J. Weiss Space Weather 20(3) (2022) https://doi.org/10.1029/2021SW002907
Predictability of Geomagnetically Induced Currents as a Function of Available Magnetic Field Information
Forecasting the Probability of Large Rates of Change of the Geomagnetic Field in the UK: Timescales, Horizons, and Thresholds
A. W. Smith, C. Forsyth, I. J. Rae, T. M. Garton, T. Bloch, C. M. Jackman and M. Bakrania Space Weather 19(9) (2021) https://doi.org/10.1029/2021SW002788
Comparison of Deep Learning Techniques to Model Connections Between Solar Wind and Ground Magnetic Perturbations
EUropean Heliospheric FORecasting Information Asset 2.0
Stefaan Poedts, Andrea Lani, Camilla Scolini, et al. Journal of Space Weather and Space Climate 10 57 (2020) https://doi.org/10.1051/swsc/2020055
A global climatological model of extreme geomagnetic field fluctuations
Neil C. Rogers, James A. Wild, Emma F. Eastoe, Jesper W. Gjerloev and Alan W. P. Thomson Journal of Space Weather and Space Climate 10 5 (2020) https://doi.org/10.1051/swsc/2020008
A Gray‐Box Model for a Probabilistic Estimate of Regional Ground Magnetic Perturbations: Enhancing the NOAA Operational Geospace Model With Machine Learning
E. Camporeale, M. D. Cash, H. J. Singer, C. C. Balch, Z. Huang and G. Toth Journal of Geophysical Research: Space Physics 125(11) (2020) https://doi.org/10.1029/2019JA027684
MMS SITL Ground Loop: Automating the Burst Data Selection Process
Impulsive disturbances of the geomagnetic field as a cause of induced currents of electric power lines
Vladimir Belakhovsky, Vyacheslav Pilipenko, Mark Engebretson, Yaroslav Sakharov and Vasily Selivanov Journal of Space Weather and Space Climate 9 A18 (2019) https://doi.org/10.1051/swsc/2019015
Dennis Albert, Thomas Halbedl, Herwig Renner, Rachel L. Bailey and Georg Achleitner 1 (2019) https://doi.org/10.1109/UPEC.2019.8893515