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UMR 5672

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You are here: Home / Seminars / Colloquium / Modelling rheological transitions in a solid/fluid/granular and cold material: sea ice

Modelling rheological transitions in a solid/fluid/granular and cold material: sea ice

Véronique Dansereau (ISTerre, Univ. Grenoble Alpes)
When Dec 18, 2023
from 11:00 to 12:00
Where Salle Condorcet
Attendees Véronique Dansereau
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The thin ice that covers the polar oceans is a very complex geomaterial that exhibits various mechanical behaviors, depending on its local state and on the time and space scales at which it is observed. Where it is very dense, it behaves like a brittle solid that breaks under the stress imposed by the winds and ocean currents. Once broken and loosened, it can also flow like a fluid under the action of the same winds and currents. In the so-called Marginal Ice Zone, where it is intensively fractured by ocean waves, it behaves like a frictional granular media. Between these three different regimes (solid, fluid and granular), the intensity of energy, gas and momentum exchanges between the ice, the atmosphere and the ocean are widely different, hence the importance of capturing their essence in climate models. Equally important is the capability to simulate the transitions between the three regimes, as these strongly control both the local, seasonal and the large-scale, long-term evolution of the sea ice cover. 
This talk will present past and ongoing efforts to develop numerical models for the dynamics of sea ice, destined to operational and climate-type simulations. It will discuss associated challenges, for instance, formulating rheologies that can capture the very complex and multi-scale behavior of this material while keeping a continuum framework that incorporates a minimum number of observationally-relevant state variables. It will also discuss similarities between the deformation mechanisms present in sea ice and in other geophysical systems - the Earth crust in particular - and how these similarities can be exploited to develop transversal and numerically-efficient models. 

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