Glaciology is not a branch of science where we have the privilege of large-scale, controlled experiments. Instead, we largely rely on numerical models to test hypotheses and make predictions. Models of varying complexity are an integral part of most our research.
Data-model integration
Modern ice-flow models can help us gain a more quantitative and detailed understanding of the ice sheets. For example, they can help us understand basal conditions or predict future behavior at individual glaciers. However, most models do not leverage all the available data for an area–they are simply not equipped to take in all the various types of information we might possess. Thinking about new ways to compare models and data is one of the main ways we are using models. A long-term group goal is to develop automatic methods to leverage internal ice-sheet structure, derived from radar data, in ice-flow models.
Process-oriented modeling
Current models do a reasonable job reproducing observations of changes to the ice sheets, but they are far from perfect. We know that there are important physical processes and properties, like fabric, that are not considered by such models. One of our research directions is thinking about how to improve the representation of neglected processes in ice-flow models.