RII Track-4:NSF: Continental-scale, high-order, high-spatial-resolution, ice flow modeling based on graphics processing units (GPUs)

University Of North Dakota Main Campus, Grand Forks ND

Investigators

Abstract

The global mean sea level is rising at an average rate of 3.7 mm yr−1, posing a significant threat to coastal communities and global ecosystems. The increase in ice discharge from the Antarctic ice sheet contributes significantly to the rising sea levels. However, its dynamic response to climate change remains a fundamental uncertainty in sea level rise projections. Conventional central processing units (CPUs) limit the time needed to run simulation ensembles of continental-scale Antarctica forward in time to assess better its sea-level contribution sensitivity to uncertainties in climate forcing parameterization. Ice flow predictions are the most computationally expensive part of ice sheet simulations in terms of computer memory and execution time. Leveraging graphics processing units (GPUs) to alleviate the high computational costs associated with ice flow simulations can provide an enhanced balance between speed and predictive performance. With the support of this fellowship, the PI and a graduate student will investigate those mentioned above to run three-dimensional (3-D) high-spatial-resolution higher-order simulation ensembles of continental-scale Antarctica forward in time to assess better its sea-level contribution sensitivity to uncertainties in climate forcing parameterization, which has been previously impossible. This Research Infrastructure Improvement Track-4 EPSCoR Research Fellows (RII Track-4) project will provide a fellowship to a Senior Lecturer and training for a graduate student at the University of North Dakota. This work would be conducted in collaboration with researchers at Dartmouth College. Several recent studies have used stress balance models with complexities lower than the 3-D Blatter-Pattyn higher-order model and spatial resolutions equal to or greater than 1 km near grounding lines to keep computational resources manageable when running simulation ensembles forward in time at the continental scale. These studies partially assess the Antarctic sea-level contribution sensitivity to uncertainties in climate forcing parameterization. The study will explicitly test an accelerated and matrix-free method in conjunction with the GPU’s ability to run 3-D high-spatial-resolution higher-order simulation ensembles of continental-scale Antarctica forward in time to assess better its sea level contribution sensitivity to uncertainties in climate forcing parameterization, which has been previously impossible. These findings have not been available due to computational costs; however, they are urgently needed as the Antarctic Ice Sheet loses mass at an increasing rate and will significantly benefit process-oriented and sea-level-projection studies over the coming decades. The methods developed will enable the ice sheet community to quantify the uncertainty bounds in projections with increased confidence, better identify the sources most responsible for the uncertainties in projections, and determine the types of satellite measurements that must be made to reduce uncertainty in projections. Furthermore, the methods and software developed can be extended to accelerate other large-scale Navier-Stokes or incompressible fluid flow applications. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.