Ice-Ocean Simulations using an Elastic-Decohesive Model

University Of New Mexico, Albuquerque NM

Investigators

Abstract

With prior NSF support, an elastic-decohesive ice model was developed based on the observed discontinuous and anisotropic behavior of ice. The emphasis of that work was development of a model to predict lead opening and orientation, as well as efficient numerical techniques to solve the model equations. The model was tested on basin-scale (e.g., Beaufort Sea) calculations over a period of about one winter month. The simulations were evaluated against ice deformation derived from satellite observations of ice motion using new metrics developed to account adequately for the presence of discontinuities. Building on this prior work, the PIs propose to further refine the models in order to conduct large-scale simulations. Specifically, they propose to add elements to the sea-ice model that allow realistic runs over long time scales. First, the model currently does not refreeze leads in the sense of resetting the ice strength over time if the lead closes and/or sufficient new ice is formed to heal the fracture. Second, the current model was developed and tested on winter conditions and does not adequately model freeze-up in the fall or melting in the spring. The model has been tested so far with prescribed ocean and wind currents. They propose to couple the sea-ice model to the Massachusetts Institute of Technology general circulation model (MITgcm) and test the combined code on basin-scale and eventually global simulations. They propose a direct comparison of the elastic-decohesive model with the viscous-plastic model currently used in the MITcgm code. The comparisons will be based on ice deformations inferred from satellite observations. This novel approach to sea ice modeling is designed to model the small scale features whose effects are averaged in the traditional sea ice models now in use in global climate models and most operational models. If proven successful through sufficient model-data comparison, this new approach could prove highly beneficial as Arctic operations, such as ship routing, require detailed predictions of anticipated conditions.