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Abstract We must be able to predict and mitigate against geomagnetically induced current (GIC) effects to minimize socio‐economic impacts. This study employs the space weather modeling framework (SWMF) to model the geomagnetic response over Fennoscandia to the September 7–8, 2017 event. Of key importance to this study is the effects of spatial resolution in terms of regional forecasts and improved GIC modeling results. Therefore, we ran the model at comparatively low, medium, and high spatial resolutions. The virtual magnetometers from each model run are compared with observations from the IMAGE magnetometer network across various latitudes and over regional‐scales. The virtual magnetometer data from the SWMF are coupled with a local ground conductivity model which is used to calculate the geoelectric field and estimate GICs in a Finnish natural gas pipeline. This investigation has lead to several important results in which higher resolution yielded: (1) more realistic amplitudes and timings of GICs, (2) higher amplitude geomagnetic disturbances across latitudes, and (3) increased regional variations in terms of differences between stations. Despite this, substorms remain a significant challenge to surface magnetic field prediction from global magnetohydrodynamic modeling. For example, in the presence of multiple large substorms, the associated large‐amplitude depressions were not captured, which caused the largest model‐data deviations. The results from this work are of key importance to both modelers and space weather operators. Particularly when the goal is to obtain improved regional forecasts of geomagnetic disturbances and/or more realistic estimates of the geoelectric field.
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Revealing Novel Connections Between Space Weather and the Power Grid: Network Analysis of Ground‐Based Magnetometer and Geomagnetically Induced Currents (GIC) Measurements
Abstract The growing depth and breadth of data spanning the solar‐terrestrial environment requires new ways of representing and analyzing the available information. This paper applies one such new data representation—network analysis—to the study of Geomagnetically Induced Currents (GICs) in electric power lines. This work uses newly available electric current data collected by power utilities through the the Electric Power Research Institute (EPRI) SUNBURST project and magnetometer data from the Super Magnetometer Initiative. The magnetometer data are analyzed using wavelet analysis. This new analysis method shows deviations to be more likely for equatorial stations close to water, which may be caused by the coast effect. The deviation likelihood is a complex function of latitude and magnetic local time. The GIC data are analyzed using “Quiet Day Curves” (QDCs) which help isolate geomagnetic disturbances. We find that current deviations are more common in the early morning sector, but this trend differs from station to station. These current and magnetometer data are represented in a network as nodes which are connected when both the current and magnetic measurements have a statistically significant deviation from their baseline behavior. This network is used to study the link between space weather and GICs. To do this, times when a current deviation exists are compared to times when magnetic deviations exist for each magnetometer ‐ current sensor pair. Current deviations are, on average, 1.83 times more likely when there are magnetic deviations. However, some magnetometer deviations are more indicative than others, with the strongest probability multipliers reaching 3.
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- PAR ID:
- 10367751
- Publisher / Repository:
- DOI PREFIX: 10.1029
- Date Published:
- Journal Name:
- Space Weather
- Volume:
- 20
- Issue:
- 2
- ISSN:
- 1542-7390
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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