Modelling ice fabric evolution and its effect on viscous anisotropy

The loss of ice from Antarctica and Greenland is the main source of uncertainty for sea-level rise predictions under a warming climate. Ice fabrics - the distribution of crystal orientations within a polycrystal - are key for understanding the dynamics of ice. Understanding ice fabrics enables us to infer processes occurring within ice sheets. In addition, ice fabrics can cause the flow rate to vary by a factor of 9 in different directions. Despite this, it is still a challenge to model ice fabrics both accurately and efficiently. I develop the first fully constrained continuum model for fabric evolution which agrees with experimental results and has only temperature and velocity gradient as inputs, with low computational cost. Using this model I explore fabrics generated across a spectrum of two-dimensional deformations and temperatures. Results show that intermediate deformation regimes between pure and simple shear result in a smooth transition between a fabric characterised by a cone-shape and a secondary cluster pattern. Highly-rotational deformation regimes produce a weak girdle fabric. I also predict fabrics within an ice stream and compare results to measured ice fabrics from cores at the East Greenland Ice Core Project (EGRIP) site by tracing the flow path upstream using satellite data. This approach correctly predicts the fabric pattern at EGRIP - a girdle/horizontal maxima perpendicular to the flow. The results also provide insights into properties deep within the ice sheet such as the level of basal slip. In summary, the fabric model and its applications presented in this thesis enable prediction of ice fabrics much more accurately and easily than previously. Due to its numerical efficiency the developed and tested fabric evolution model presented in this work can now be coupled to large-scale ice-sheet models and provide a reliable basis for estimating the effect of viscous anisotropy