Project Goals

Our ONR-MURI program seeks to develop a computational toolkit to enhance the quality of sea ice modeling prediction by combining state-of-the-art extraction methods from multiple data acquisition modalities and improved understanding of the underlying dynamics. The algorithms we develop use tools from computational inverse problems, Bayesian data assimilation, machine learning, numerical ODE and PDE modeling, and statistics. We are developing a set of benchmark problems to contain features important to sea ice modeling to test our methods and ensure their accuracy, efficiency, and robustness.

Our team consists of five multi-university leading researchers with multi-disciplinary backgrounds, including expertise in mathematics, statistics, engineering, and physics.