Dynamics of Ice Streams: A Physical Statistical Approach

Geophysical models lie at the core of the approach, but are embellished by statistical modeling of various components of variability. One important component comes from the uncertainty in observations on basal elevation, surface elevation, and surface velocity. In this project, new observational data collected using remote-sensing techniques are used.

The various components, some of which are spatial, are combined hierarchically using Bayesian statistical methodology. All these are combined mathematically into a physical statistical model that yields the posterior distributions for basal and surface elevations, surface velocity fields, and stress fields, conditional on the data. Inference based on these distributions is carried out via Markov chain Monte Carlo techniques, to obtain estimates of these unknown fields along with uncertainty measures associated with them.