Optimal numerical solvers for transient simulations of ice flow using the Ice Sheet System Model (ISSM).

Identifying fast and robust numerical solvers is a critical issue that needs to be addressed in order to improve projections of polar ice sheets evolving in a changing climate. This work evaluates the impact of using sophisticated numerical solvers for transient ice flow simulations using the NASA-JPL/UCI Ice Sheet System Model (ISSM). We identify optimal numerical solvers by testing them on a commonly used ice flow benchmark test, the Ice Sheet Model Intercomparison Project for Higher-Order ice sheet Models (ISMIP-HOM) Experiment F. Three types of analyses are considered: mass transport, horizontal stress balance, and vertical stress balance. A broad suite of solvers is tested, ranging from direct sparse solvers to preconditioned iterative methods. The results of the fastest solvers for each analysis type are ranked based on their scalability across mesh size for each basal sliding conditions specified in Experiment F. We find that the fastest iterative solvers are ~1.5-100 times faster than the default direct solver used in ISSM with speed-ups improving rapidly with increased mesh resolution. We provide a set of recommendations for users in search of efficient solvers to use for transient ice flow simulations, enabling higher-resolution meshes and faster turnaround time. The end result will be improved transient simulations for short-term, highly resolved forward projections (10-100 year time scale) and also improved long-term paleo-reconstructions using higher-order representation of stresses in the ice. This analysis will also enable a new generation of comprehensive uncertainty quantification assessments of forward sea-level rise projections, which rely heavily on ensemble or sampling approaches that are inherently expensive. [ABSTRACT FROM AUTHOR]