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Title:
First-principles modeling of geomagnetically induced electromagnetic fields and currents from upstream solar wind to the surface of the Earth
Authors:
Pulkkinen, A.; Hesse, M.; Kuznetsova, M.; Rastätter, L.
Affiliation:
AA(Goddard Earth Sciences and Technology Center, University of Maryland, Baltimore, MD, USA; NASA/GSFC, Greenbelt, Code 674, MD 20771, USA ), AB(NASA/GSFC, Greenbelt, Code 674, MD 20771, USA), AC(NASA/GSFC, Greenbelt, Code 674, MD 20771, USA), AD(NASA/GSFC, Greenbelt, Code 674, MD 20771, USA; Catholic University, Washington D.C., USA)
Publication:
Annales Geophysicae, Volume 25, Issue 4, 2007, pp.881-893 (AnGeo Homepage)
Publication Date:
05/2007
Origin:
EGU
Bibliographic Code:
2007AnGeo..25..881P

Abstract

Our capability to model the near-space physical phenomena has gradually reached a level enabling module-based first-principles modeling of geomagnetically induced electromagnetic fields and currents from upstream solar wind to the surface of the Earth. As geomagnetically induced currents (GIC) pose a real threat to the normal operation of long conductor systems on the ground, such as high-voltage power transmission systems, it is quite obvious that success in accurate predictive modeling of the phenomenon would open entirely new windows for operational space weather products.

Here we introduce a process for obtaining geomagnetically induced electromagnetic fields and currents from the output of global magnetospheric MHD codes. We also present metrics that take into account both the complex nature of the signal and possible forecasting applications of the modeling process. The modeling process and the metrics are presented with the help of an actual example space weather event of 24-29 October 2003. Analysis of the event demonstrates that, despite some significant shortcomings, some central features of the overall ionospheric current fluctuations associated with GIC can be captured by the modeling process. More specifically, the basic spatiotemporal morphology of the modeled and "measured" GIC is quite similar. Furthermore, the presented user-relevant utility metrics demonstrate that MHD-based modeling can outperform simple GIC persistence models.
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