A framework for quantifying parametric ice sheet model uncertainty

Ice sheet models, calibrated using observational data, provide a means of projecting our current best state of the knowledge of the system state into the future, so as to obtain information about possible future behaviour. However it is important to be able to estimate the uncertainty associated with these projections. The problem of quantifying ice sheet parametric uncertainty is considered, focusing specifically on the problem of quantifying the posterior uncertainty in inferred basal sliding and rheology coefficients. These measures of uncertainty are projected forwards in time to obtain measures of uncertainty in future quantities of interest. Automated code generation and automated differentiation tools are utilised, leading to an extensible approach. The role of the observational error model in defining parametric uncertainty is considered.