Solar flares could soon be on the increase, says University of Bradford professor
Artificial intelligence solar flare detector used by NASA, developed in Bradford
Solar flares could be on the increase over the next few years as the sun moves towards the most active part of its 11-year cycle, says one Bradford professor.
Moreover, our increasing reliance on technology means we’re more vulnerable than ever to solar flares, which can cause massive power blackouts.
However, a system used by NASA to monitor sunspots and predict solar flares - which was developed at the University of Bradford (UK) - could give us more warning.
Space weather
Most of us are familiar with checking weather reports before we go on holiday but very few of us ever consider what the weather is like in space.
Rami Qahwaji, Professor of Visual Computing in the Faculty of Engineering & Informatics at the University of Bradford is one who does.
He invented a system which has been used by NASA since 2011 to analyse latest satellite images and sunspots data to predict solar flares. The Automated Solar Activity Prediction (ASAP) system makes prediction of solar activity faster, automated and more accurate and is even incorporated into the NASA Space Weather portal and app.
Sunspot activity has a huge effect on the Earth. The greater the number of complex sunspots, the more chance of significant solar flares, which throw huge amounts of radiation into space, some of which reaches earth. When it does, it can damage satellites and even knock out power grids on Earth.
The sun has an 11-year sunspot cycle and at the moment, we’re in the middle of that cycle but headed towards the ‘solar maximum’, which is expected to occur in 2025.
“That means, we could see more sunspots in the coming years,” says Professor Qahwaji. “The last few years have seen relatively few sunspots but as we progress through the cycle, they tend to increase in frequency and complexity.
“The problem is that today we rely so much on technology for things like satellite navigation and communication and all of these things can be adversely affected by increased solar activity.”
Power blackouts
Solar storms were first recognised as detrimental to power systems in Quebec, Canada in 1989, when millions of people were left without power after a series of space weather events. Another powerful solar storm, known as The Halloween solar storm (because they happened from mid-October to early November) happened in 2003 and resulted in the largest solar flare ever recorded, leading to power outages in Sweden and a visible aurora as far south as some Mediterranean countries.
Prof Qahwaji adds: “The power grids affected in the 1989 storm were knocked out in just 90 seconds. People are familiar with the Northern Lights and this is one visible effect of solar radiation. However, in addition to affecting our technology, it can also have an effect on us. For example, if you were to fly over the North Pole, you would be exposed to increased radiation. Solar and Cosmic radiation is also one of the primary concerns for any manned mission to Mars.”
Prof Qahwaji’s ASAP system uses AI to detect, record and predict sunspot activity and is the world’s first automated real-time system for the 24/7 monitoring and prediction of extreme solar flares. It has a high percentage accuracy for flare prediction.
Find out more by visiting their website: spaceweather.inf.brad.ac.uk
Factfile
- Sunspots have been studied for over 400 years (since the invention of the telescope), thereby making it the longest running scientific experiment in human history
- The sun has an 11-year cycle, which includes a ‘solar minimum’ with fewer sunspots and a maximum, when more typically occur
- In 1989, a geomagnetic storm caused by solar flares led to a nine-hour power outage in parts of Canada
- In 1645, the so-called Maunder Minimum period began, when there were almost no sunspots. It lasted roughly 70 years and coincided with the ‘Little Ice Age’, which saw major rivers freeze across Europe and North America
- Prior to the ASAP project, sunspots had to be analysed by human experts, which made predictions more difficult, slower and subjective