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Predicting extremes in European geomagnetic activity

By Ewan Dawson, Sarah Reay and Alan Thomson


Rapid variations in the geomagnetic field constitute a natural hazard, e.g. for navigation\ud and to power grids and pipeline networks. In order to better allocate resources\ud towards mitigating these risks, we must be able to model the recurrence of extremes of\ud geomagnetic activity over many years.\ud \ud However, the data we have from which to develop such a model, in the form of continuous\ud series of 1-minute samples of the geomagnetic field, typically stretch back less\ud than 40 years. Without a longer record, it is difficult to construct a clear picture of the\ud magnitude and frequency of extremes in geomagnetic activity.\ud \ud We therefore apply the statistical technique of ‘extreme value analysis’ on a number of\ud decades of geomagnetic data recorded at observatories across Europe, and in doing\ud so arrive at an estimate of the maximum field strength and time-variation that might be\ud observed once in every 100 and 200 years

Topics: Earth Sciences
Publisher: British Geological Survey
Year: 2010
OAI identifier:

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  1. (1208). (residual) dD/dt H (residual) dH/dt LER 100 year: 6.64 200 year: 7.59 (5.76, 7.51) (6.57, 8.62) 100 year: 2.90 200 year: 3.32 (2.30, 3.50) (2.63, 4.02) 100 year: 3441 200 year:
  2. 80˚ Figure 4. The measured maximum, 100-year return-level and 200-year return-level, for (top) and d /dt (bottom). The +/-95% confidence interval is represented by the translucent segments of each column.
  3. (2004). An Introduction to Statistical Modeling of Extreme Values, doi
  4. (2004). Data Preparation Extreme Value Theory Extreme Value Analysis Future Work We use a Generalised Pareto Distribution (GPD) to describe the tail of the distribution of geomagnetic activity (see e.g. Coles,
  5. (2005). Tutorial for the Extremes Toolkit: Weather and Climate Applications of Extreme Value Statistics, t. R Development Core Team,

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