Ice sheet and ice shelf models rely on data from experiments to accurately represent the way ice moves. Performing experiments at the temperatures and stresses that are generally present in nature takes a long time, and so there are few of these datasets. Here, we test the method of speeding up an experiment by running it initially at a higher temperature, before dropping to a lower target temperature to generate the relevant data. We show that this method can reduce experiment time by 55 %.