Articles | Volume 15, issue 9
https://doi.org/10.5194/gmd-15-3721-2022
© Author(s) 2022. 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-15-3721-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
10 May 2022
Model description paper |
| 10 May 2022
| 10 May 2022
MPAS-Seaice (v1.0.0): sea-ice dynamics on unstructured Voronoi meshes
Theoretical Division, Los Alamos National Laboratory, Los Alamos, NM, USA
William H. Lipscomb
Climate and Global Dynamics Laboratory, National Center for Atmospheric Research, Boulder, CO, USA
Elizabeth C. Hunke
Theoretical Division, Los Alamos National Laboratory, Los Alamos, NM, USA
Douglas W. Jacobsen
Theoretical Division, Los Alamos National Laboratory, Los Alamos, NM, USA
Nicole Jeffery
Computer, Computational, and Statistical Sciences Division, Los Alamos National Laboratory, Los Alamos, NM, USA
Darren Engwirda
Theoretical Division, Los Alamos National Laboratory, Los Alamos, NM, USA
Todd D. Ringler
Science Technology Policy Institute, Washington, DC 20006, USA
Jonathan D. Wolfe
Theoretical Division, Los Alamos National Laboratory, Los Alamos, NM, USA
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- Global Sensitivity Analysis Using the Ultra‐Low Resolution Energy Exascale Earth System Model I. Tezaur et al. 10.1029/2021MS002831
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- Comparing heterogeneity of sea-ice models with viscous-plastic and Maxwell elasto-brittle rheology M. Bourgett et al. 10.1017/aog.2024.40
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- Development of a total variation diminishing (TVD) sea ice transport scheme and its application in an ocean (SCHISM v5.11) and sea ice (Icepack v1.3.4) coupled model on unstructured grids Q. Wang et al. 10.5194/gmd-17-7067-2024
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- The DOE E3SM Model Version 2: Overview of the Physical Model and Initial Model Evaluation J. Golaz et al. 10.1029/2022MS003156
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11 citations as recorded by crossref.
- Uncovering the interannual predictability of the 2003 European summer heatwave linked to the Tibetan Plateau P. Shi et al. 10.1038/s41612-024-00782-3
- Global Sensitivity Analysis Using the Ultra‐Low Resolution Energy Exascale Earth System Model I. Tezaur et al. 10.1029/2021MS002831
- Estimating Arctic Ocean Acoustic Travel Times Using an Earth System Model S. Niklasson et al. 10.1029/2022GL102216
- Development and evaluation of a new 4DEnVar-based weakly coupled ocean data assimilation system in E3SMv2 P. Shi et al. 10.5194/gmd-18-2443-2025
- Southern Ocean polynyas and dense water formation in a high-resolution, coupled Earth system model H. Jeong et al. 10.5194/tc-17-2681-2023
- Comparing heterogeneity of sea-ice models with viscous-plastic and Maxwell elasto-brittle rheology M. Bourgett et al. 10.1017/aog.2024.40
- Ice-shelf freshwater triggers for the Filchner–Ronne Ice Shelf melt tipping point in a global ocean–sea-ice model M. Hoffman et al. 10.5194/tc-18-2917-2024
- LIGHT-bgcArgo-1.0: using synthetic float capabilities in E3SMv2 to assess spatiotemporal variability in ocean physics and biogeochemistry C. Nissen et al. 10.5194/gmd-17-6415-2024
- Accuracy and stability analysis of horizontal discretizations used in unstructured grid ocean models F. Rodrigues Lapolli et al. 10.1016/j.ocemod.2024.102335
- Development of a total variation diminishing (TVD) sea ice transport scheme and its application in an ocean (SCHISM v5.11) and sea ice (Icepack v1.3.4) coupled model on unstructured grids Q. Wang et al. 10.5194/gmd-17-7067-2024
- CD-type discretization for sea ice dynamics in FESOM version 2 S. Danilov et al. 10.5194/gmd-17-2287-2024
3 citations as recorded by crossref.
- An evaluation of the E3SMv1 Arctic ocean and sea-ice regionally refined model M. Veneziani et al. 10.5194/gmd-15-3133-2022
- The DOE E3SM Model Version 2: Overview of the Physical Model and Initial Model Evaluation J. Golaz et al. 10.1029/2022MS003156
- Simulating Sea‐Ice Deformation in Viscous‐Plastic Sea‐Ice Models With CD‐Grids C. Mehlmann et al. 10.1029/2023MS003696
Latest update: 03 Jul 2025
Short summary
We present the dynamical core of the MPAS-Seaice model, which uses a mesh consisting of a Voronoi tessellation with polygonal cells. Such a mesh allows variable mesh resolution in different parts of the domain and the focusing of computational resources in regions of interest. We describe the velocity solver and tracer transport schemes used and examine errors generated by the model in both idealized and realistic test cases and examine the computational efficiency of the model.
We present the dynamical core of the MPAS-Seaice model, which uses a mesh consisting of a...
