End of nuclear secrecy? Underground weapon tests 'now detectable with 99% accuracy'
End of nuclear secrecy? Underground weapon tests 'now detectable with 99% accuracy'
Royal Astronomical Society press release
RAS PR 24/04
For immediate release
Secret underground nuclear tests could now be a thing of the past thanks to a major scientific breakthrough in ways to identify them.
A team of Earth scientists and statisticians say they can now tell with 99 per cent accuracy if such an explosion has taken place. This is up from 82 per cent and is based on a dataset of known tests in the US, according to the new study published in Geophysical Journal International.
It has previously been tricky to differentiate between nuclear explosions and other seismic sources, such as naturally-occurring earthquakes or man-made noise above ground.
“The explosion goes off and you have all this energy that radiates out, which can be measured on seismometers,” said lead author Dr Mark Hoggard, of The Australian National University (ANU).
“So, the science problem becomes how do we tell the difference between that and a naturally-occurring earthquake?”
This was an issue seven years ago, when several of the existing methods used to identify underground nuclear explosions failed to establish that North Korea had carried out such a test.
The secretive communist state later confirmed it had successfully tested a weapon with a force of between 100-370 kilotons. For comparison, a 100 kiloton bomb is six times more powerful than the one the US dropped on Hiroshima in 1945.
North Korea is the only country known to have carried out an underground nuclear test in the 21st century, but satellite imagery revealed last year that Russia, the US and China have all built new facilities at their nuclear test sites in recent years.
Although there is no suggestion the three superpowers are planning to resume such experiments, the war in Ukraine has made the global security landscape uncertain.
“By using some revised mathematics and more advanced statistical treatment, we have managed to improve the classification success rate from 82 per cent to 99 per cent for a series of 140 known explosions in the US,” Dr Hoggard said.
“Nuclear testing in the US has largely been carried out in Nevada – in the desert – and there is a thorough seismic record of all those tests, so it provides a really helpful dataset.
“Our new method also successfully identifies all six of the tests conducted in North Korea from 2006 to 2017.”
Dr Hoggard said there may still be instances of underground nuclear tests being carried out surreptitiously in some parts of the world, and the sheer volume of earthquakes makes it difficult to investigate each event to determine if it is suspicious or not.
“This makes effective methods like ours all the more important,” he added.
“It also doesn’t require any new kit - you don’t have to put up satellites or anything like that, we’re just using standard seismic data.”
Dr Hoggard described the model as “pretty fast”, making it “more or less suitable for real-time monitoring”.
The research was carried out by a team of Earth scientists and statisticians working at ANU and the Los Alamos government research lab in the US.
They say the new approach “provides a means to rapidly assess the likelihood of an event being an explosion”.
The mathematical model was built by analysing the physical differences in the pattern of rock deformation at the source of nuclear explosions and earthquakes, allowing experts to determine which seismic event a recorded noise is more likely to belong to.
International efforts shifted to monitoring significant seismic waves in the aftermath of the Cuban Missile Crisis and Partial Nuclear Test Ban Treaty in the 1960s, which limited the testing of nuclear weapons to underground only.
The agreement was introduced following years of environmentally-damaging experiments carried out at the surface and/or underwater. These polluted many locations and in some instances led to catastrophic levels of radioactive fallout.
But the new monitoring it required brought about its challenges - primarily how to differentiate between nuclear explosions and other seismic sources.
It has taken more than six decades, but the scientists behind the new research believe their innovative method could now make this a lot easier for groups such as the Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO), which is tasked with international surveillance of nuclear testing.
Dr Hoggard said his team’s mathematical model would be “another tool in CTBTO’s armoury for detecting any potential underground tests that are conducted in secret”.
He added: “A ban on all future tests is unlikely given that several major nations remain unwilling to ratify the Comprehensive Nuclear-Test-Ban Treaty.
“Well-supported monitoring programs are therefore critical for ensuring that all governments are held accountable for the environmental and societal impacts of nuclear weapons testing.”
The paper ‘Seismic moment tensor classification using elliptical distribution functions on the hypersphere’ has been published in Geophysical Journal Internationa
Images and captions
The images in this release are public domain.
1. Castle Bravo mushroom cloud Credit: Wikipedia
The 1954 Castle Bravo mushroom cloud, which was one of the most environmentally damaging nuclear tests ever carried out. It was a main contributor to the banning of all surface nuclear tests in 1963.
2. Earthquakes vs explosions diagram Credit: ANU
This diagram shows 140 explosions and 1,149 earthquakes analysed by researchers. It reveals the explosions previously misidentified as earthquakes (red diamonds) and earthquakes wrongly classified as nuclear blasts (green diamonds).
Science contacts
Dr Mark Hoggard, Australian National University
Tel: +61 434 403 585
Further information
The paper is available via the following link: https://academic.oup.com/gji/article/237/1/1/7597260
Notes for editors
About the Royal Astronomical Society
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JOURNAL
Geophysical Journal International
METHOD OF RESEARCH
Data/statistical analysis
SUBJECT OF RESEARCH
Not applicable
ARTICLE TITLE
‘Seismic moment tensor classification using elliptical distribution functions on the hypersphere’
ARTICLE PUBLICATION DATE
7-Feb-2024
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