Superfloe parameterization with physics constraints for data assimilation and uncertainty quantification of sea ice floes ...
<!--!introduction!--> The discrete element method (DEM) provides a new modeling approach for describing sea ice dynamics. It exploits particle-based methods to characterize the physical quantities of each sea ice floe along its trajectory under Lagrangian coordinates. One major challenge in ap...
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| Format: | Conference Object |
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GFZ German Research Centre for Geosciences
2023
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| Online Access: | https://dx.doi.org/10.57757/iugg23-2035 https://gfzpublic.gfz-potsdam.de/pubman/item/item_5018801 |
| Summary: | <!--!introduction!--> The discrete element method (DEM) provides a new modeling approach for describing sea ice dynamics. It exploits particle-based methods to characterize the physical quantities of each sea ice floe along its trajectory under Lagrangian coordinates. One major challenge in applying DEM models is the heavy computational cost when the number of floes becomes large. In this paper, an efficient Lagrangian parameterization algorithm is developed, which aims at reducing the computational cost of simulating the DEM models while preserving the key features of the sea ice. The new parameterization takes advantage of a small number of artificial ice floes, called the superfloes, to effectively approximate a considerable number of the floes, where the parameterization scheme satisfies several important physics constraints. The physics constraints guarantee the superfloe parameterized system will have short-term dynamical behavior similar to that of the full system. These constraints also allow ... : The 28th IUGG General Assembly (IUGG2023) (Berlin 2023) ... |
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