Parameter Optimization in Sea Ice Models with Elastic-Viscoplastic Rheology

Ice rheology formulation is the key component of the modern sea ice modeling. In the CICE6 community model, rheology and landfast grounding/arching effects are simulated by functions of the sea ice thickness and concentration with a set of fixed parameters empirically adjusted to optimize the model performance. In this study we consider a spatially variable extension of representing these parameters in the two-dimensional EVP sea ice model with a formulation similar to CICE6. Feasibility of optimization of the rheological and landfast sea ice parameters is assessed by applying variational data assimilation to the synthetic observations of ice concentration, thickness and velocity. It is found that the tangent linear and adjoint models featuring EVP rheology are unstable, but can be stabilized by adding Newtonian damping term into the adjoint equation. The set of the observation system simulation experiments shows that landfast parameter distributions can be reconstructed after 5–10 iterations of the minimization procedure. Optimization of the sea ice initial conditions and spatially varying parameters in the equation for the stress tensor requires more computation, but provides a better hindcast of the sea ice state and the internal stress tensor. Analysis of the inaccuracy in the wind forcing and errors in the sea ice thickness observations have shown reasonable robustness of the variational DA approach and feasibility of its application to the available and incoming observations.