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A Global Statistical Model of Extreme Geomagnetic Field Fluctuations

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Abstract

Published
Publication date1/02/2019
Host publicationGeophysical Research Abstracts
Place of PublicationMunich, Germany
PublisherCopernicus GmbH (Copernicus Publications) on behalf of the European Geosciences Union (EGU)
Number of pages1
Volume21
<mark>Original language</mark>English
EventEuropean Geosciences Union General Assembly 2019 - Austria Center Vienna (ACV), Vienna, Austria
Duration: 7/04/2019 → 12/04/2019
https://www.egu2019.eu/

Conference

ConferenceEuropean Geosciences Union General Assembly 2019
Abbreviated titleEGU 2019
Country/TerritoryAustria
CityVienna
Period7/04/19 → 12/04/19
Internet address

Publication series

NameGeophysical Research Abstracts
PublisherCopernicus GmbH (Copernicus Publications)
Volume21
ISSN (electronic)1029-7006

Conference

ConferenceEuropean Geosciences Union General Assembly 2019
Abbreviated titleEGU 2019
Country/TerritoryAustria
CityVienna
Period7/04/19 → 12/04/19
Internet address

Abstract

The statistics of unusually high rates of change in the horizontal component of the geomagnetic field (dB/dt) are a useful indicator of the likelihood of damaging geomagnetically induced currents (GIC) in ground-based infrastructure such as electricity networks. Using extreme value theory (Coles, 2001) we present a global model of the probability of extreme |dB/dt| based on several decades of measurements from 125 magnetometers worldwide,
with time cadences (dt) ranging from 1 to 60 minutes.

The occurrence rate of peaks in |dB/dt| above the 99.97th percentile is a function of magnetic latitude, magnetic local time, month, sunspot number, solar wind and interplanetary magnetic field conditions, and the direction of the field fluctuation. This information may be used to improve the extreme value model. The patterns of occurrence are presented and compared with previously studied distributions of Sudden Commencements, Pc5 ULF waves, and auroral substorm onsets, giving insight into the relative importance of these drivers in GIC modelling.

Reference:
S. Coles, An introduction to Statistical Modeling of Extreme Values, Springer-Verlag London ltd, 2001.

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