A PARTICLE-IN-CELL SEA-ICE MODEL

Fronts or discontinuities in geophysical flows are often smoothed in numerical models owing to artificial diffusion and dispersion introduced by the advection algorithm. This is a particular problem in operational sea-ice forecasting where the position of the ice edge must be accurately predicted. The particle-in-cell (PIC) scheme avoids artificial smoothing by partitioning the ice volume into individual particles whose motion is integrated in a Lagrangian sense. The velocity field is obtained by solving the momentum equation on an underlying fixed Eulerian grid. Comparisons between the PIC scheme and more conventional advection algorithms are presented using both idealized and observed forcing fields. An advantage of the PIC model is that the resolution of the underlying Eulerian grid (on which the computationally expensive momentum equation is solved) can be chosen to represent the spatial variability of the forcing fields (winds and currents) rather than to minimize advection errors. A large number of particles per unit area can be used to resolve features of interest while maintaining only a sparse particle distribution elsewhere. The model is readily extended to include additional particles representing, for example, an oil spill.