Better Forecasting of Extreme Geomagnetic Storms Using Non‐Stationary Statistical Models
Abstract An assessment of the risk of extreme geomagnetic storms is critically important for modern society. However, current methods mainly focus on using stationary statistical models to analyze extreme geomagnetic events. These models ignore the non‐stationary nature of the data, caused by effect...
Saved in:
| Main Authors: | Ting Wang, David Fletcher, Matthew Parry, Craig J. Rodger, Andy W. Smith, Tanja Petersen |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2025-07-01
|
| Series: | Space Weather |
| Online Access: | https://doi.org/10.1029/2025SW004404 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Geomagnetically Induced Current Modeling in New Zealand: Extreme Storm Analysis Using Multiple Disturbance Scenarios and Industry Provided Hazard Magnitudes
by: D. H. Mac Manus, et al.
Published: (2022-12-01) -
Impact of the May 2024 Extreme Geomagnetic Storm on the Ionosphere and GNSS Positioning
by: Ekaterina Danilchuk, et al.
Published: (2025-04-01) -
Geomagnetically Induced Currents, Transformer Harmonics, and Reactive Power Impacts of the Gannon Storm in May 2024
by: M. A. Clilverd, et al.
Published: (2025-04-01) -
Extreme two-phase change of ionospheric electron temperature overshoot during geomagnetic storms
by: Artem Smirnov, et al.
Published: (2025-02-01) -
Wavelet analysis of geomagnetically induced currents during the strong geomagnetic storms
by: Aksenovich Tatyana, et al.
Published: (2022-12-01)