New Machine Learning Model Can Predict Radiation Storms

Researchers are now able to take preventive actions against energetic electrons through a two-day notice delivered by a sophisticated computer model. A new machine learning computer system precisely foresees harmful radiation storms triggered by the Van Allen belts two days before the storm takes place. It is the most developed notice that currently exists, as per a new study published in the journal Space Weather. "Radiation storms from the Van Allen belts can damage or even knock out satellites orbiting in medium and high altitudes above the Earth, but predicting these storms has always been a challenge," said Yue Chen, a space scientist at Los Alamos National Laboratory and principal investigator on the project funded by both NASA and NOAA. "Given that the Van Allen Probes, which provided important data about space weather, recently de-orbited, we no longer have direct measurements about what's happening in the outer electron radiation belt. Our new model uses existing data sets to'learn' patterns and predict future storms so satellite operators can take protective measures, including temporarily shutting down part of or even the whole satellite to avoid damage," Chen added.