We can learn about the flow of ice in Antarctica by evaluating the key parameters that control the flow speed. These parameters include the basal drag coefficient and the ice viscosity. They can be estimated by adjusting their values so that model velocities at the upper surface agree with satellite observations. This dataset was produced using inverse methods to obtain the parameter values. In this approach a cost function that describes the mismatch between model and satellite data is minimised iteratively by making small adjustments to the parameters at each iteration to improve the fit. The result is better information about the flow field in the Antarctic ice sheet. Once the flow field is available it can be used as an initial state from which begin temporally evolving simulations using the model. A number of different examples are included to show how varying different parameters alters the temporally evolving simulations.

The contributing datasets used to constrain the model are listed by Arthern et al (2015) and Arthern and Williams (2017). Multidecadal model simulations span up to 100 years of simulation time.

This work was funded by NERC standard grant NE/L005212/1.