Implementation of a brittle sea-ice rheology in an Eulerian, finite-difference, C-grid modeling framework: Impact on the simulated deformation of sea-ice in the Arctic

We have implemented the Brittle Bingham-Maxwell sea-ice rheology (BBM) into SI3, the sea-ice component of NEMO. We describe how we achieved this numerical implementation. Specifically, we detail how we introduced a new spatial discretization framework, well adapted to solve the equations of sea-ice d...

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Bibliographic Details
Main Authors: Brodeau, Laurent, Rampal, Pierre, Òlason, Einar, Dansereau, Véronique
Format: Text
Language:English
Published: 2024
Subjects:
Online Access:https://doi.org/10.5194/gmd-2023-231
https://gmd.copernicus.org/preprints/gmd-2023-231/
Description
Summary:We have implemented the Brittle Bingham-Maxwell sea-ice rheology (BBM) into SI3, the sea-ice component of NEMO. We describe how we achieved this numerical implementation. Specifically, we detail how we introduced a new spatial discretization framework, well adapted to solve the equations of sea-ice dynamics, in order to overcome the numerical issues posed by the use of the staggered C-grid. As a validation step, a twin hindcast experiment performed with the coupled ocean/sea-ice setup of the NEMO system, run at a 1/4° spatial resolution, serves as a basis to evaluate the simulated sea-ice deformation rates against satellite observations; when using the newly-implemented BBM rheology and when using the default viscous-plastic rheology of SI3. The results show the added value of using a brittle-type of rheology, such as BBM, to accurately simulate the highly-localized deformation patterns of sea-ice. Thus, our results highlight the relevance of the use of this newly-implemented rheology for future modeling studies that utilize a classical Eulerian sea-ice modeling framework, i.e. based on the finite-difference discretization method over a quadrilateral, staggered, computational grid. This includes, in particular, coupled climate simulations performed with CMIP-class Earth System Models at coarse to moderate spatial resolution.