Scientists develop new method to forecast geomagnetic storms
Scientists say they have developed a new method for analysing the Earth’s magnetic field data that could provide better short-term forecasting of geomagnetic storms. The Earth’s magnetic field extends from pole to pole and is strongly affected by solar wind from the Sun, according to the research published in the journal Chaos. This “wind” is a stream of charged particles constantly ejected from the Sun’s surface.
Occasional sudden flashes of brightness known as solar flares release even more particles into the wind, said researchers at Potsdam Institute for Climate Impact Research in Germany. Sometimes, the flares are followed by coronal mass ejections that send plasma into space. The resulting flux of charged particles travels millions of miles from the Sun to the Earth. The storms are serious and interfere with a number of important technologies, including GPS signalling and satellite communications. They can also cause damage to surface electrical grids. Solar activity appears random, making it difficult for us to predict these storms.
The researchers at Potsdam Institute developed the method that relies on a technique developed for systems in a state far from equilibrium. Earth’s magnetic field fits this paradigm because the field is driven far away from equilibrium by the solar wind. Systems that are far from equilibrium often undergo abrupt changes, such as the sudden transition from a quiescent state to a storm. The researchers used hourly values of the Disturbance storm-time, or Dst, index. Dst values give the average deviation of the horizontal component of the Earth’s magnetic field from its normal value.
This deviation occurs when a large burst of charged particles arrives from the Sun and weakens the field generated by the Earth. The Dst values form a single stream of numbers known as a time series, researchers said. The time series data can then be recast into a 2D or 3D image by plotting one data point against another at a fixed amount of time into the future for forecasting, they said.
