Toward Optimization of Rheology in Sea Ice Models through Data Assimilation

Sea ice models that allow for deformation are primarily based on rheological formulations originally developed in the 1970s. In both the original viscoplastic (VP) and elastic-VP schemes, the internal pressure term is modeled as a function of variable sea ice thickness and concentration with spatially and temporally constant empirical parameters for ice strength. This work considers a spatially variable extension of the rheology parameters as well as wind stress in a one-dimensional VP sea ice data assimilation system. In regions of total ice cover, experiments that assimilate synthetic ice-state observations using variable rheological parameters show larger improvements than equivalent experiments using homogeneous parameters. For partially ice-covered regions where internal ice stresses are relatively unimportant, experiments assimilating synthetic sea ice velocity observations demonstrate reasonable reconstruction of spatially variable wind stresses. These results suggest practical benefits for sea ice–state reconstruction and forecasts by using sea ice velocity, thickness, and concentration observations to optimize spatially varying rheological parameters and to improve wind stress forcing.