In recent years, sea ice has displayed behaviour previously unseen in the satellite record. This fast-changing sea-ice cover calls for adapting and improving our modelling approaches and mathematical techniques to simulate its behaviour and its interaction with the atmosphere and the ocean, both in terms of dynamics and thermodynamics.
Sea ice is governed by a variety of small-scale processes that affect its large-scale evolution. Modelling this nonlinear coupled multidimensional system remains a major challenge, because (1) we still lack the understanding of the physics governing sea-ice dynamics and thermodynamics, (2) observations to conduct model evaluation are scarce and (3) the numerical approximation and the simulation become more difficult and computationally expensive at higher resolution.
Recently, several new modelling approaches have been developed and refined to address these issues. These include but are not limited to new rheologies, discrete element models, advanced subgrid parameterizations, the representation of wave-ice interactions, sophisticated data assimilation schemes, often with the integration of machine learning techniques. Moreover, novel in-situ observations and the growing availability and quality of sea-ice remote-sensing data bring new opportunities for improving sea-ice models.
This session aims to bring together researchers working on the development of sea-ice models, from small to large scales and for a wide range of applications such as idealised experiments, operational predictions, or climate simulations, to discuss current advances and challenges ahead.
Sea ice is governed by a variety of small-scale processes that affect its large-scale evolution. Modelling this nonlinear coupled multidimensional system remains a major challenge, because (1) we still lack the understanding of the physics governing sea-ice dynamics and thermodynamics, (2) observations to conduct model evaluation are scarce and (3) the numerical approximation and the simulation become more difficult and computationally expensive at higher resolution.
Recently, several new modelling approaches have been developed and refined to address these issues. These include but are not limited to new rheologies, discrete element models, advanced subgrid parameterizations, the representation of wave-ice interactions, sophisticated data assimilation schemes, often with the integration of machine learning techniques. Moreover, novel in-situ observations and the growing availability and quality of sea-ice remote-sensing data bring new opportunities for improving sea-ice models.
This session aims to bring together researchers working on the development of sea-ice models, from small to large scales and for a wide range of applications such as idealised experiments, operational predictions, or climate simulations, to discuss current advances and challenges ahead.