Space researchers, spearheaded by MIT, plan on creating a software solution to better predict cosmic disturbances, known as space storms.
On a night devoid of moonlight, August 28, 1859, witnessed a spectacular, global aurora. This celestial display, usually confined to the Arctic and Antarctic regions, extended its fiery fingers across the globe, transforming the night sky into a vibrant canvas of crimson hues. From cobblestone streets in New England to the outback in Australia, people gathered in awe, captivated by the ethereal spectacle and grappling with a dash of fear as the night sky danced in a Technicolor ballet. However, the breathtaking beauty came with a torment. The resplendent display brought chaos to the telegraph system, responsible for nearly all long-distance communication at the time. Operators were shocked as they received electric shocks while sending and receiving messages; sparks flew from cable pylons. The telegraph was silent for days.
This remarkable aurora and the ensuing havoc were attributed to a geomagnetic storm caused by a series of coronal mass ejections (CMEs) that blasted from the sun's surface, zoomed through the solar system, and pummeled our atmosphere with devastating magnetic solar energy. In modern times, such a storm could spell worldwide catastrophe. A storm of such magnitude could result in global blackouts, massive network failures, and wide-scale satellite damage, not to mention potential human health risks from increased radiation exposure. Unlike terrestrial storms, solar storms' arrival and intensity can be elusive to predict. Without a better understanding of space weather, we may not even see the next great solar storm approaching until it's too late.
To tackle this challenge, Richard Linares, an assistant professor in MIT's Department of Aeronautics and Astronautics, takes the helm of a diverse team of researchers. Their mission: develop software that significantly advances our ability to forecast space weather. With improved models, historical observational data can provide more accurate predictions for space weather events, such as CMEs, solar wind, and other space plasma phenomena as they interact with our atmosphere.
Linares and his MIT collaborators, including Phillip Erickson, Jaime Peraire, Youssef Marzouk, Ngoc Cuong Nguyen, Alan Edelman, and Christopher Rackauckas, are set to create a model-focused composable software framework. This groundbreaking software will ingest a vast array of observation data from around the world into a global model of the ionosphere/thermosphere system. External collaborators, Aaron Ridley from the University of Michigan, and Boris Kramer from the University of California at San Diego, will also contribute their expertise.
"Together, we aim to close the gap in space weather prediction by creating a powerful, flexible software platform," says Linares. This platform will employ state-of-the-art computational tools to process and analyze vast volumes of data, making it easy for researchers to share and reproduce their findings. The platform will also be designed to evolve with computer technology, accommodating new researchers and machines.
Julia, a high-performance programming language developed by Alan Edelman, promises to play a pivotal role in this project. Julia's versatility will enable researchers worldwide to tailor the software to their data without starting from scratch.
"I am thrilled that Julia, already garnering attention as the language of scientific machine learning, can contribute significantly to space weather applications," says Edelman.
The project ultimately seeks to lay the foundation for a space weather prediction system that can be expanded and enhanced over time, benefiting the global community and transforming our space weather forecasting capabilities.
- The research team at MIT, led by Richard Linares, aims to develop software that improves our ability to forecast space weather.
- The software will focus on advancing models for space weather events, like coronal mass ejections and solar wind.
- Linares and his team are creating a composable software framework to help predict space weather more accurately.
- This framework will gather observation data from around the world and create a global model of the ionosphere/thermosphere system.
- Collaborators from the University of Michigan and the University of California at San Diego will also contribute to the project.
- Julia, a high-performance programming language, will play a crucial role in the development of this software.
- Julia's versatility will enable researchers to tailor the software to their data, without starting from scratch.
- The project's ultimate goal is to establish a space weather prediction system that can evolve and improve over time, benefiting the global community and enhancing space weather forecasting capabilities.
