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New solar prediction system gives time to prepare for the storms ahead

01 September 2010 Bradford, University of

A new method of predicting solar storms that could help to avoid widespread power and communications blackouts costing billions of pounds has been launched by researchers at the University of Bradford.

Solar storms involve the release of huge amounts of hot gas and magnetic forces from the surface of the sun into space at around a million miles an hour. The next major solar storms are expected in 2012-13 as part of the sun’s 11-year weather cycle. A 2008 US National Academy of Sciences report estimated that modern reliance on electronics and satellite communications means a major storm could cause twenty times more economic damage than Hurricane Katrina.

Although major solar eruptions (coronal mass ejections) normally take several days to reach the Earth, the largest recorded in 1859 took just eighteen hours. Solar flares – which can also cause significant disruption to communications systems – take just a few minutes. So advance warning is of vital importance to enable steps to be taken to avoid the worst effects of solar activity.

Up to now, solar weather prediction has been done manually, with experts looking at 2D satellite images of the sun and assessing the likelihood of future activity. But the team from the University of Bradford’s Centre for Visual Computing have created the first online automated prediction system, using 3D images generated from the joint NASA/ESA Solar and Heliospheric Observatory satellite (SOHO). The system can be seen at work at

Already in use by both NASA and the European Space Agency (ESA), the Bradford Automated Solar Activity Prediction system (ASAP) identifies and classifies sun spots and then feeds this information through a model which can predict the likelihood of solar flares. The system is able to accurately predict a solar flare six hours in advance and the team are working to achieve a similar accuracy for the prediction of major solar eruptions in the near future.

Reader in Visual Computing, Dr Rami Qahwaji, who led the EPSRC-funded research, says: “Solar weather prediction is still very much in its infancy, probably at about the point that normal weather forecasting was around 50 years ago.

“However, our system is a major step forward. By creating an automated system that can work in real time, we open up the possibility for much faster prediction and – with sufficient data – prediction of a wider range of activity. With NASA’s new Solar Dynamic Observatory satellite which came into operation in May, we have the chance to see the sun’s activity in much greater detail which will further improve our prediction capabilities.”

The ASAP model is based on historical data which was analysed to identify patterns in the sun’s activity. Dr Qahwaji is now applying for more funding to further improve the system and ensure it can be adapted to work with the latest sun monitoring satellites.

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