The three-year grant from the Office of Naval Research, awarded in February, will allow mathematicians at NPS and the Naval Research Lab in Washington, D.C., (NRL-DC) to apply new approaches, including machine learning, to high-fidelity computer models to more accurately and efficiently model hurricanes. This will enable the Navy to best predict – and mitigate – these storms’ impact on marine battlespace environments the world over.
“This is a game-changer,” said Dr. Frank Giraldo, Distinguished Professor and Chair of the Applied Mathematics department and co-lead on the project along with Assistant Professor Anthony Austin, who leads the machine learning aspects of the project. “The novelty of our approach is, in my opinion, the only possible way to ever make weather models scalable on exascale computers.”
The Department of Energy is slated to bring the first exascale computers – next generation computers capable of a billion billion operations per second – online within the next few years. Given computing limitations, current weather models are incapable of fully drilling down to the necessary scale for accurate prediction.