Scaling and Performance Improvements in Elmer/Ice

• Main Author: Thomas Zwinger
• Other Authors: Mika Malinen, Juha Ruokolainen, Peter Råback
• Format: Report
• Language: unknown
• Published: 2013
• Subjects: IPCC; HPC; Antarctic; The Antarctic; Greenland; Antarc*
• Online Access: https://zenodo.org/record/822189; https://doi.org/10.5281/zenodo.822189

By gaining and losing mass, glaciers and ice-sheets play a key role in sea level evolution. This is obvious when considering the past 20000 years, during which the collapse of the large northern hemisphere ice-sheets after the Last Glacial Maximum contributed to a 120m rise in sea level. This is particularly worrying when the future is considered. Indeed, recent observations clearly indicate that important changes in the velocity structure of both the Antarctic and Greenland ice-sheets are occurring, suggesting that large and irreversible changes may already have been initiated. This was clearly emphasised in the last report published by the Intergovernmental Panel on Climate Change (IPCC) [7]. The IPCC also asserted that current knowledge of key processes causing the observed accelerations was poor, and concluded that reliable projections obtained with process-based models for sea-level rise (SLR) are currently unavailable. Most of these uncertain key processes have in common that their physical/numerical characteristics, such as shallow ice approximation (SIA), are not accordingly reflected or even completely missing in the established simplified models that have been in use since decades. Whereas those simplified models run on common PC systems, the new approaches require higher resolution and larger computational models, which demand High Performance Computing (HPC) methods to be applied. In other words, numerical glaciology, like climatology and oceanography decades ago, needs to be updated for HPC with scalable codes, in order to deliver the prognostic simulations demanded by the IPCC. The DECI project ElmerIce, and enabling work associated with it, improved simulations of key processes that lead to continental ice loss. The project also developed new data assimilation methods. This was intended to decrease the degree of uncertainty affecting future SLR scenarios and consequently contribute to on-going international debates surrounding coastal adaptation and sea-defence planning. These results directly ...