A Hybrid Deep Neural Operator/Finite Element Method for Ice-Sheet Modeling

Understand

One of the most challenging and consequential problems in climate modeling is to provide probabilistic projections of sea level rise.

• A large part of the uncertainty of sea level projections is due to uncertainty in ice sheet dynamics.
• At the moment, accurate quantification of the uncertainty is hindered by the cost of ice sheet computational models.
• In this work, we develop a hybrid approach to approximate existing ice sheet computational models at a fraction of their cost.