The shrinking extent and thickness of the Arctic sea ice cover, as well as the major loss of multi-year pack ice is allowing greater access to the Arctic. In order to make use of this new accessibility efficiently and to guarantee safe operations, high-resolution sea ice forecasts are required on a variety of time scales, from hours to days, months, and seasons. Currently, shortcomings in our modeling capability preclude accurate prediction of ice characteristics on the necessary variety of temporal and spatial scales. The ability to simulate the ice edge, the space and time evolution of the pack ice, as well as ice types, thickness distribution, strength and state of deformation is crucial to accurate sea ice forecasting.
We propose to improve the representation of sea ice mechanics in general circulation models and Earth system models in order to advance the short-term (days to months), high- resolution (tens of meters to kilometers) predictive capabilities of these models. We will pursue this objective by expanding, evaluating, and applying a new sea ice model, which describes sea ice mechanics based on the elastic-decohesive rheology. In contrast to the isotropic, viscous-plastic rheology of most current sea ice models, the elastic-decohesive rheology explicitly represents the presence and direction of sea ice deformation features. The specific focus of the present proposal is on ‘understanding’ rather than ‘prediction’; that is, we aim to demonstrate that the elastic-decohesive model can better describe the underlying mechanisms responsible for regional sea ice variation and change through comparison with satellite and in-situ observations of sea ice deformation. If successful, however, this project has the potential to deliver models with much improved predictive capability of high-resolution, coupled ocean, wave, atmosphere, and sea ice processes.
The proposed work falls into three categories: model development, model evaluation, and the application of the new model. Model development focuses on the connection of an ice thickness distribution to the decohesive rheology and implementation of the rotation of the lead direction as leads are advected with the flow of the pack ice. Further, we propose a mechanism to account for the increasing strength of ice growing in leads. These developments are crucial to correctly represent the anisotropy of the ice strength, which impacts the large-scale flow of the ice cover and its local deformation. Model evaluation begins with a comparison to observations of ice concentration, thickness, and drift but focuses on the deformation rate and lead statistics. A variety of airborne and satellite derived data sets will be used. Finally, we will apply the new model in a suite of sensitivity simulations to test its dependency on spatial resolution as well as its ability to simulate break-up events of the sea ice cover in late winter and spring. Timing and spatial extent of ice beak-up are relevant to both climate processes and operational decision making.
This proposal is being submitted in response to the NOAA call, Climate Variability and Predictability (CVP) FY 2015: Understanding Arctic Sea Ice Mechanisms and Predictability. The proposed model supports NOAA’s mission to assess current and future states of the climate system in order to identify potential impacts and inform science, service, and stewardship decisions. The model specifically aims to advance the CVP program goal of understanding Pan-Arctic sea ice interactions by better describing mechanisms involved in prediction of regional sea ice variation and change.