A new 3D full-Stokes calving algorithm within Elmer/Ice (v9.0) - Wheel, Iain Alexander; Benn, Doug I; Crawford, Anna J.; Todd, Joe; Zwinger, Thomas (Geoscientific Model Development, 2024)
Funding: This research has been supported by the Natural Environment Research Council (grant no. NE/S006605/1) and the HORIZON EUROPE European Research Council (grant no. 730897). Thomas Zwinger has been supported by the Finnish Academy COLD consortium (grant no. 322978). A new calving algorithm is developed in the glacier model Elmer/Ice that allows unrestricted calving and terminus advance in 3D. The algorithm uses the meshing software Mmg to implement anisotropic remeshing and allow mesh adaptation at each time step. The development of the algorithm, along with the implementation of the crevasse depth law, produces a new full-Stokes calving model capable of simulating calving and terminus advance across an array of complex geometries. Using a synthetic tidewater glacier geometry, the model is tested to highlight the numerical model parameters that can alter calving when using the crevasse depth law. For a system with no clear attractor at a pinning point, the model time step and mesh resolution are shown to alter the simulated calving. In particular, the vertical mesh resolution has a large impact, increasing calving, as the frontal bending stresses are better resolved. However, when the system has a strong attractor, provided by basal pinning points, numerical model parameters have a limited effect on the terminus evolution. Conversely, transient systems with no clear attractors are highly influenced by the choice of numerical model parameters. The new algorithm is capable of implementing unlimited terminus advance and retreat, as well as unrestricted calving geometries, applying any vertically varying melt distribution to the front for use in conjunction with any calving law or potentially advecting variables downstream. In overcoming previous technical hurdles, the algorithm opens up the opportunity to improve both our understanding of the physical processes and our ability to predict calving. Peer reviewed