AI algorithm brings us closer to predicting the Northern Lights

A group of researchers used artificial intelligence to sort through nearly a billion images of the aurora borealis – the northern lights – which could help researchers understand and predict this fascinating natural phenomenon in the future.

The team developed a new algorithm to sort more than 706 million images of auroras in THEMIS all-sky images taken between 2008 and 2022. The algorithm sorted the images into six categories based on their characteristics, demonstrating the utility of software for classifying large-scale aerial datasets.

“This large data set is a valuable resource that can help researchers understand how the solar wind interacts with the Earth’s magnetosphere, the protective bubble that protects us from charged particles streaming from the sun,” said Jeremiah Johnson, a researcher at the University of New Hampshire. The lead author of the study is at a university He releases. “But so far, their sheer size limits how effectively we can use that data.”

Team research-published Last month in Journal of Geophysical Research: Machine Learning and Computation– Describes an algorithm trained to automatically label hundreds of millions of aurora images, which could help scientists quickly explore the ethereal phenomenon on a large scale.

He was there a lot to twilight this yearThis is partly because the Sun is at the peak of its solar cycle. The peak of the Sun’s 11-year solar cycle is marked by increased activity on the star’s surface, including explosions of solar material (coronal mass ejections, or CMEs), and solar flares.

These events send charged particles into space, and when those particles interact with particles in Earth’s atmosphere, they cause an ethereal glow in the sky: the aurora borealis. Molecules can too Disable electronics and Energy networks On Earth and in space, but we’re only talking about beautiful natural phenomena right now, not about the harsh chaos that space weather could rain down on humanity.

“A disaggregated database could reveal more insight into aurora dynamics, but at a very basic level, we aimed to organize the THEMIS all-sky image database so that researchers could use the vast amount of historical data it contains more effectively and provide more information,” Johnson said. “Large enough sample for future studies.”

Intensity of solar storms It’s hard to predict Because scientists can’t accurately measure the solar flares they come from until the particles are within an hour of reaching Earth.

The team sorted hundreds of millions of images into six categories: arc, diffuse, discrete, cloudy, lunar, and clear/no aurora. Scientists may benefit from comparing the aurora to atmospheric data from when the aurora occurred and link the phenomenon to the solar event that ultimately caused the light show.

A better understanding of the chemical mix of solar particles and those in Earth’s atmosphere will help scientists determine which types of aurora arise from each scenario, and be able to quickly interrogate hundreds of millions of images (comparable to the rate at which this work is done by humans). ) could be a boon for aurora research.