Mapping the eye of extreme weather events

Mapping the eye of extreme weather events

Researchers have been able to use high-energy muon particles to explore the structures of extreme weather events such as storms

For the first time, high-energy muon particles created in the atmosphere have allowed researchers to explore the structures of storms in a way that traditional visualisation techniques, such as satellite imaging, cannot.

The detail offered by this new technique could aid researchers modelling storms and related weather effects. This could also lead to more accurate early warning systems.

It’s hard not to notice the number of stories in the news about heavy storms in different parts of the world, often attributed to climate change.

Weather prediction and early warning systems have always been important, but with increased storm activity it seems especially so these days.

A team of researchers, led by Professor Hiroyuki Tanaka from Muographix at the University of Tokyo, offer the world of meteorology a novel way of detecting and exploring tropical cyclones using a quirk of particle physics that takes place above our heads all the time.

Tanaka said: “You’ve probably seen photographs of cyclones taken from above, showing swirling vortices of clouds. But I doubt you’ve ever seen a cyclone from the side, perhaps as a computer graphic, but never as actual captured sensor data.

“What we offer the world is the ability to do just this, visualise large-scale weather phenomena like cyclones from a 3D perspective, and in real time too.

“We do this using a technique called muography, which you can think of like an X-ray, but for seeing inside truly enormous things.”

See also: UN outlines $160m emergency relief plan for flood-hit Pakistan

atmospheric weather systems

Muography creates X-ray-like images of large objects, including volcanoes, the pyramids, bodies of water, and now, for the first time, atmospheric weather systems.

Special sensors called scintillators are joined together to make a grid, a little like the pixels on your smartphone’s camera sensor.

However, these scintillators don’t see optical light, but instead see particles called muons which are created in the atmosphere when cosmic rays from deep space collide with the atoms in the air.

Muons are special because they pass through matter easily without scattering as much as other types of particles.

But the small amount they do deviate by as they pass through solid, liquid, or even gaseous matter, can reveal details of their journey between the atmosphere and the sensors.

By capturing a large number of muons passing through something, an image of it can be reconstructed.

Tanaka advised: “We successfully imaged the vertical profile of a cyclone, and this revealed density variations essential to understanding how cyclones work.

“The images show cross sections of the cyclone which passed through Kagoshima Prefecture in western Japan. I was surprised to see clearly it had a low-density warm core that contrasted dramatically with the high-pressure cold exterior.

“There is absolutely no way to capture such data with traditional pressure sensors and photography.”

approaching storms

The detector the researchers used has a viewing angle of 90 degrees, but Tanaka envisages combining similar sensors to create hemispherical and therefore omnidirectional observation stations which could be placed along the length of a coastline.

These could potentially see cyclones as far away as 300km. Although satellites already track these storms, the extra detail offered by muography could improve predictions about approaching storms.

Tanaka added: “One of the next steps for us now will be to refine this technique in order to detect and visualise storms at different scales.

“This could mean better modelling and prediction not only for larger storm systems, but more local weather conditions as well.”

Image: The redder areas are low-pressure warm air, and the green areas are higher-pressure cooler air. The cyclone in this image is about 15km tall. A line drawing approximating the shape overlays the visualisation data. © 2022 Hiroyuki KM Tanaka.

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