Mystery Behind the Uncanny Strength of a 2023 Solar Storm Solved by Scientists

In April 2023, Earth was hit by a surprisingly strong solar storm, and now scientists know the exact reason behind its unexpected strength. The storm unfolded on April 23 and was so strong that it managed to create intense auroras as far south as southern Texas, according to Daily Galaxy. The cause of this geomagnetic storm was deemed to be a particular coronal mass ejection (CME), essentially a cloud composed of magnetic fields and energetic particles released from the sun.

Scientists were surprised by the solar storm's strength, as the flare observed before this particular CME appeared to be weak. Solar flares and CMEs are interconnected phenomena often used by scientists to determine each other's strengths. According to the scientists' estimates, the solar flare and, by extension, the CME could not have produced such a strong storm. After around two years, scientists have finally resolved the mystery and explained it in The Astrophysical Journal.

Coronal Hole - Key to the Problem
The study claims that the solar storm's unexpected strength was due to the alignment between the CME's magnetic structure with respect to the Earth's magnetic structure. Researchers made this assertion based on data gathered by five heliophysics spacecraft across the inner solar system, according to NASA. The data helped the team detect a massive coronal hole near the CME's origin. Coronal holes are the areas where solar winds move at a higher-than-normal speed and influence the movement of CMEs.
Evangelos Paouris of the Johns Hopkins Applied Physics Laboratory in Laurel, Maryland, and the study's lead author, explained that the fast solar winds from this particular coronal hole acted as air currents and successfully moved the cloud away from its original straight-line path, forcing it closer to Earth's orbital plane. In addition to being deflected by the solar winds, the CME itself also rotated slightly during the whole phenomenon. The team suggests that the changes inflicted in the process caused the magnetic fields in CME to turn opposite to Earth's magnetic field. This state of affairs allowed more energy from the Sun to enter Earth's atmosphere and made the resultant solar storm stronger.
Intriguing Consequences of the Storm
NASA's GOLD (Global-scale Observations of Limb and Disk) mission observed a change in the thermosphere due to the storm. The mission gathered temperature readings of the middle thermosphere, the layer of atmosphere 85 to 120 miles above the surface, before, during, and after the storm. The readings indicated an increase in temperature during the solar storm. However, once it passed, there was not only a sharp decrease, but it was lower than what it was before the storm. There was a difference of around 90 to 198 degrees Fahrenheit between the prior and after storm temperatures in the middle thermosphere layer over the Americas.
These readings are significant, as they show how much drag can be experienced by Earth-orbiting satellites and space debris. "When the thermosphere cools, it contracts and becomes less dense at satellite altitudes, reducing drag," Xuguang Cai from the University of Colorado, Boulder, explained. "This can cause satellites and space debris to stay in orbit longer than expected, increasing the risk of collisions. Understanding how geomagnetic storms and solar activity affect Earth's upper atmosphere helps protect technologies we all rely on — like GPS, satellites, and radio communications," Cai added.
Predicting a Solar Storm
NASA scientists have a new and more accurate way to predict when a CME will trigger geomagnetic storms. For this new method, scientists have combined satellite observations with machine learning. Machine learning is essentially a kind of artificial intelligence, where a computer algorithm is fed data and instructed to identify patterns. The team has named it AI GeoCME and explained its features in the journal Solar Physics. Researchers took images collected by the NASA/ESA (European Space Agency) SOHO (Solar and Heliospheric Observatory). These images were focused on CMEs that reached the Earth, and the state of the Sun before, during, and after each CME. Thereafter, the researchers informed the AI which CMEs in the collection produced a geomagnetic storm.

Later, the AI was supplied a different set of images from SOHO, focusing on the same objects. The AI was able to predict all the CMEs that eventually triggered a geomagnetic storm, and out of the seven non-triggering CMEs, the AI predicted five of them correctly. "The algorithm shows promise," said heliophysicist Jack Ireland of NASA's Goddard Space Flight Center in Greenbelt, Maryland, who was not involved in the study. "Understanding if a CME will be geoeffective or not can help us protect infrastructure in space and technological systems on Earth. This paper shows that machine learning approaches to predicting geoeffective CMEs are feasible."