SASIP: The Scale-Aware Sea Ice Project

The Scale-Aware Sea Ice Project aims to develop a truly innovative, scale-aware continuum sea ice model for climate research; one that faithfully represents sea ice dynamics and thermodynamics and that is physically sound, data-adaptive, highly parallelized and computationally ef cient. SASIP will use machine learning and data assimilation to exploit large datasets obtained from both simulations and remote sensing.

Through the further development of existing important state-of-the-art simulators created by some of the investigators, SASIP will build a data-constrained sea ice model that is based on solid-like physics. This model will allow improved high resolution and large scale predictions of Arctic and Antarctic sea ice, and the propagation of sea ice related climate feedback. Employing hybrid data assimilation and machine learning approaches as a native part of the model architecture will allow for objective combinations of models and data. Ultimately, SASIP will give a better understanding of the impact of amplified warming in polar regions through the development of a model that reduces uncertainties related to global earth systems.