Articles | Volume 16, issue 9
https://doi.org/10.5194/gmd-16-2607-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-16-2607-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
15 May 2023
Model description paper |
| 15 May 2023
| 15 May 2023
The CryoGrid community model (version 1.0) – a multi-physics toolbox for climate-driven simulations in the terrestrial cryosphere
Sebastian Westermann
CORRESPONDING AUTHOR
Department of Geosciences, University of Oslo, Oslo, Norway
Center for Biogeochemistry of the Anthropocene, University of Oslo, Oslo, Norway
Thomas Ingeman-Nielsen
DTU Sustain, Technical University of Denmark, Kgs. Lyngby, Denmark
Johanna Scheer
DTU Sustain, Technical University of Denmark, Kgs. Lyngby, Denmark
Kristoffer Aalstad
Department of Geosciences, University of Oslo, Oslo, Norway
Juditha Aga
Department of Geosciences, University of Oslo, Oslo, Norway
Center for Biogeochemistry of the Anthropocene, University of Oslo, Oslo, Norway
Nitin Chaudhary
Department of Geosciences, University of Oslo, Oslo, Norway
Department of Physical Geography and Ecosystem Science, Lund University, Lund, Sweden
Bernd Etzelmüller
Department of Geosciences, University of Oslo, Oslo, Norway
Simon Filhol
Department of Geosciences, University of Oslo, Oslo, Norway
Andreas Kääb
Department of Geosciences, University of Oslo, Oslo, Norway
Cas Renette
Department of Geosciences, University of Oslo, Oslo, Norway
Louise Steffensen Schmidt
Department of Geosciences, University of Oslo, Oslo, Norway
Thomas Vikhamar Schuler
Department of Geosciences, University of Oslo, Oslo, Norway
Robin B. Zweigel
Department of Geosciences, University of Oslo, Oslo, Norway
Center for Biogeochemistry of the Anthropocene, University of Oslo, Oslo, Norway
Léo Martin
Faculty of Geosciences, Utrecht University, Utrecht, the Netherlands
Sarah Morard
Department of Geosciences, University of Fribourg, Fribourg, Switzerland
Matan Ben-Asher
EDYTEM Lab, Université Savoie Mont Blanc, CNRS, Le Bourget-du-Lac, France
Michael Angelopoulos
Permafrost Research Section, Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research, Potsdam, Germany
Julia Boike
Permafrost Research Section, Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research, Potsdam, Germany
Brian Groenke
Permafrost Research Section, Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research, Potsdam, Germany
Department of Electrical Engineering and Computer Science, Technical University of Berlin, Berlin, Germany
Frederieke Miesner
Permafrost Research Section, Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research, Potsdam, Germany
Jan Nitzbon
Permafrost Research Section, Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research, Potsdam, Germany
Paul Overduin
Permafrost Research Section, Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research, Potsdam, Germany
Simone M. Stuenzi
Permafrost Research Section, Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research, Potsdam, Germany
Moritz Langer
Permafrost Research Section, Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research, Potsdam, Germany
Department of Earth Sciences, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
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Cited
12 citations as recorded by crossref.
- The evolution of Arctic permafrost over the last 3 centuries from ensemble simulations with the CryoGridLite permafrost model M. Langer et al. 10.5194/tc-18-363-2024
- Climate change is rapidly deteriorating the climatic signal in Svalbard glaciers A. Spolaor et al. 10.5194/tc-18-307-2024
- Recent ground thermo-hydrological changes in a southern Tibetan endorheic catchment and implications for lake level changes L. Martin et al. 10.5194/hess-27-4409-2023
- TopoPyScale: A Python Package for Hillslope Climate Downscaling S. Filhol et al. 10.21105/joss.05059
- A novel numerical implementation for the surface energy budget of melting snowpacks and glaciers K. Fourteau et al. 10.5194/gmd-17-1903-2024
- Investigating the thermal state of permafrost with Bayesian inverse modeling of heat transfer B. Groenke et al. 10.5194/tc-17-3505-2023
- Meltwater runoff and glacier mass balance in the high Arctic: 1991–2022 simulations for Svalbard L. Schmidt et al. 10.5194/tc-17-2941-2023
- Estimating surface water availability in high mountain rock slopes using a numerical energy balance model M. Ben-Asher et al. 10.5194/esurf-11-899-2023
- Simulating ice segregation and thaw consolidation in permafrost environments with the CryoGrid community model J. Aga et al. 10.5194/tc-17-4179-2023
- Glacial isostatic adjustment reduces past and future Arctic subsea permafrost R. Creel et al. 10.1038/s41467-024-45906-8
- Simulating the effect of subsurface drainage on the thermal regime and ground ice in blocky terrain in Norway C. Renette et al. 10.5194/esurf-11-33-2023
- The Multiple Snow Data Assimilation System (MuSA v1.0) E. Alonso-González et al. 10.5194/gmd-15-9127-2022
10 citations as recorded by crossref.
- The evolution of Arctic permafrost over the last 3 centuries from ensemble simulations with the CryoGridLite permafrost model M. Langer et al. 10.5194/tc-18-363-2024
- Climate change is rapidly deteriorating the climatic signal in Svalbard glaciers A. Spolaor et al. 10.5194/tc-18-307-2024
- Recent ground thermo-hydrological changes in a southern Tibetan endorheic catchment and implications for lake level changes L. Martin et al. 10.5194/hess-27-4409-2023
- TopoPyScale: A Python Package for Hillslope Climate Downscaling S. Filhol et al. 10.21105/joss.05059
- A novel numerical implementation for the surface energy budget of melting snowpacks and glaciers K. Fourteau et al. 10.5194/gmd-17-1903-2024
- Investigating the thermal state of permafrost with Bayesian inverse modeling of heat transfer B. Groenke et al. 10.5194/tc-17-3505-2023
- Meltwater runoff and glacier mass balance in the high Arctic: 1991–2022 simulations for Svalbard L. Schmidt et al. 10.5194/tc-17-2941-2023
- Estimating surface water availability in high mountain rock slopes using a numerical energy balance model M. Ben-Asher et al. 10.5194/esurf-11-899-2023
- Simulating ice segregation and thaw consolidation in permafrost environments with the CryoGrid community model J. Aga et al. 10.5194/tc-17-4179-2023
- Glacial isostatic adjustment reduces past and future Arctic subsea permafrost R. Creel et al. 10.1038/s41467-024-45906-8
Latest update: 24 Apr 2024
Short summary
The CryoGrid community model is a new tool for simulating ground temperatures and the water and ice balance in cold regions. It is a modular design, which makes it possible to test different schemes to simulate, for example, permafrost ground in an efficient way. The model contains tools to simulate frozen and unfrozen ground, snow, glaciers, and other massive ice bodies, as well as water bodies.
The CryoGrid community model is a new tool for simulating ground temperatures and the water and...
