MIT research team launches project to predict weather in space.

Richard Linares, an assistant professor in the Department of Aeronautics and Astronautics (AeroAstro) at MIT, is leading a multidisciplinary team of researchers to develop software to forecast space weather events, according to a release from MIT.

The team will focus on developing better models with the aim of using historical observational data to better predict the impact of space weather events like coronal mass ejections (CMEs), solar wind, and other space plasma phenomena as they interact with our atmosphere.

The team was awarded a $3 million grant for their proposal “Composable Next Generation Software Framework” by the Space Weather with Quantified Uncertainties (SWQU) program, a partnership between the U.S. National Science Foundation (NSF) and NASA.

“By bringing together experts in geospace sciences, uncertainty quantification, software development, management, and sustainability, we hope to develop the next generation of software for space weather modeling and prediction,” Linares said in the MIT press release. “Improving space weather predictions is a national need, and we saw a unique opportunity at MIT to combine the expertise we have across campus to solve this problem.”

Linares’ will be joined by MIT collaborators including Philip Erickson, assistant director at MIT Haystack Observatory and head of Haystack’s atmospheric and geospace sciences group; Jaime Peraire, the H.N. Slater Professor of Aeronautics and Astronautics; Youssef Marzouk, professor of aeronautics and astronautics; Ngoc Cuong Nguyen, a research scientist in AeroAstro; Alan Edelman, professor of applied mathematics; and Christopher Rackauckas, instructor in the Department of Mathematics. External collaborators include Aaron Ridley (University of Michigan) and Boris Kramer (University of California at San Diego). 

The goal of the project is to utilize cutting-edge computational tools to create a powerful, flexible software platform to collect and analyze huge sets of observational data that can be easily circulated among researchers. The platform will aim to be future proof by being designed to work even as computer technology rapidly advances and new researchers contribute to the project from new places, using new machines. Edelman has developed Julia, a high-performance programming language so researchers from all over the world will be able to tailor the software for their own purposes to contribute their data without having to rewrite the program from scratch.

Linares said that the composable software framework can be used as a foundation that can be expanded and improved over time, improving space weather prediction capabilities and the space weather modeling community itself.