Abstract
Ice-dynamical processes constitute a large uncertainty in future projections of sea-level rise caused by anthropogenic climate change. Improving our understanding of these processes requires ice-sheet models that perform well at simulating both past and future ice-sheet evolution. Here, we present version 2.0 of the ice-sheet model IMAU-ICE, which uses the depth-integrated viscosity approximation (DIVA) to solve the stress balance. We evaluate its performance in a range of benchmark experiments, including simple analytical solutions and both schematic and realistic model intercomparison exercises. IMAU-ICE has adopted recent developments in the numerical treatment of englacial stress and sub-shelf melt near the grounding line, which result in good performance in experiments concerning grounding-line migration (MISMIP, MISMIP+) and buttressing (ABUMIP). This makes it a model that is robust, versatile, and user-friendly, which will provide a firm basis for (palaeo-)glaciological research in the coming years.
| Original language | English |
|---|---|
| Pages (from-to) | 5667-5688 |
| Number of pages | 22 |
| Journal | Geoscientific Model Development |
| Volume | 15 |
| Issue number | 14 |
| DOIs | |
| Publication status | Published - 21 Jul 2022 |
Bibliographical note
Funding Information:Financial support. This publication was supported by PROTECT. This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement no. 869304, PROTECT contribution number 39. The use of supercomputer facilities was sponsored by NWO Exact and Natural Sciences. Model runs were performed on the Dutch National Supercomputer Cartesius. we would like to acknowledge SurfSARA Computing and Networking Services for their support. Lennert B. Stap is funded by the Dutch Research Council (NWO) through VENI grant VI.Veni.202.031. Heiko Goelzer has received funding from the programme of the Netherlands Earth System Science Centre (NESSC), which is financially supported by the Dutch Ministry of Education, Culture and Science (OCW) under grant no. 024.002.001, and from the Research Council of Norway under projects INES (270061) and KeyClim (295046). High-performance computing and storage resources were provided by the Norwegian infrastructure for computational science through projects NN9560K, NN9252K, NS9560K, NS9252K, and NS5011K.
Publisher Copyright:
© 2022 The Author(s).
Funding
Financial support. This publication was supported by PROTECT. This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement no. 869304, PROTECT contribution number 39. The use of supercomputer facilities was sponsored by NWO Exact and Natural Sciences. Model runs were performed on the Dutch National Supercomputer Cartesius. we would like to acknowledge SurfSARA Computing and Networking Services for their support. Lennert B. Stap is funded by the Dutch Research Council (NWO) through VENI grant VI.Veni.202.031. Heiko Goelzer has received funding from the programme of the Netherlands Earth System Science Centre (NESSC), which is financially supported by the Dutch Ministry of Education, Culture and Science (OCW) under grant no. 024.002.001, and from the Research Council of Norway under projects INES (270061) and KeyClim (295046). High-performance computing and storage resources were provided by the Norwegian infrastructure for computational science through projects NN9560K, NN9252K, NS9560K, NS9252K, and NS5011K.
