A High-Order Model of the Earth’s External and Induced Magnetic Field

A High-Order Model of the Earth's External and Induced Magnetic Field

Start date
30 June, 2012
End date
2 June, 2016

For centuries people have used magnetic compasses to guide them on their way and explore new territories. This has led scientists to embark on their own journeys of discovery about Earth’s magnetism, and to the discovery of electromagnetism that is at the heart of modern technology – phones, TVs, computers, etc.

Now, in the age of GPS, you might think that compasses are obsolete, but guidance by the Earth’s magnetic field is still vital to explore for oil and minerals below ground (where GPS can’t reach) and as a safety backup for planes etc. And ironically, GPS is affected by natural hazards caused by the Earth’s magnetic field.

In 2012 the European Space Agency launched a mission called Swarm; three satellites orbit the Earth surveying its magnetic field in unprecedented detail. These measurements will be used to improve models of the geomagnetic field. One target area is a better understanding and description of the relatively rapid and complex magnetic fluctuations caused by electrical currents flowing in the upper atmosphere and in Space, ultimately driven by disturbances happening on the Sun. This so-called external magnetic field also induces currents to flow in oceans and under the Earth’s surface which in turn creates additional magnetic fluctuations.

Together, the external and induced magnetic field (EIMF) limits the accuracy of geomagnetic field models such that they aren’t useful for surveys and navigation at places and times when the EIMF fluctuations are large, such as in the polar regions and during magnetic storms that may happen once a month and last several days. The EIMF also creates a natural hazard for large-scale electrically conducting systems such as power outages in electricity grids, corrosion in oil pipelines, and even phantom railway signals.

In this project we will study the EIMF using a solar cycle’s worth (11 years) of measurements made at over 300 different locations around the world,  collected together for the first time by an international project called SuperMAG. Our idea is to borrow mathematical techniques usually used by meteorologists for studying the weather and climate to identify the natural cycles and patterns of the EIMF. In conjunction with the Swarm mission, the resulting new descriptions and understanding of the EIMF “weather” and “climate” should help to improve the next generation of computer models of Earth’s magnetic field. It can also be used to as a basis to assess and predict the risk of power outages in UK’s National Grid caused by extreme EIMF fluctuations.

To provide the world’s first reanalysis model of the external and induced components of Earth’s magnetic field (EIMF) over an 11-year solar cycle and the Swarm mission, and to use this to answer the following questions:

  1. What are the major modes of variability of the EIMF?
  2. What is the impact of improved EIMF specification on the accuracy and efficiency of state-of-the-art geomagnetic field models?


The main beneficiaries of our research will be:

Surveyors of natural resources. Surveys to explore for natural underground resources use models of the geomagnetic field to guide their equipment. These models neglect most of the EIMF which means that they are unsuitable for surveying during geomagnetically active times and in the polar regions.  In addition, information on past EIMF variability and its controlling factors can help the exploration industry manage the risks of disruption to their surveys.

Electricity supply network managers. Rapid external magnetic field variations cause Geomagnetically Induced Currents (GIC) to flow in high voltage power grids, in polar, mid and low latitude power systems. Uncertainty in our understanding of GIC gives rise to large risks, with the UK government concluding that the potential impact of severe space weather on the national infrastructure is “one of the highest priority risk areas

Dr James Wild (Lancaster University)

Dr Gareth Dorrian (Lancaster University)

Prof Jesper Gjerloev (Johns Hopkins University Applied Physics Lab., University of Bergen),

Prof Nils Olsen (Technical University of Denmark)

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