On the effect of data assimilation on sea-ice simulations

We investigate the effects of assimilating buoy motion data and satellite SSM/I (85 Ghz) ice motion data on simulation of Arctic sea ice. The sea-ice model is a thickness and enthalpy distribution model and is coupled to an ocean model. Ice motion data are assimilated by means of optimal interpolation. Assimilating the ice motion data, particularly from drifting buoys, significantly improves the modeled ice motion with a reduced error and an increased correlation with observations. Assimilation leads to strengthened ice outflow at Fram Strait and enhanced ice deformation. The assimilation-enhanced ice deformation leads to an increase in the production of ridged ice, which changes the distribution of ice mass. The enhanced deformation results in more spatial variability of ice thickness and the modeled ice thickness agrees better with the observed thickness from four tracks of recent submarine cruises. Buoy data are most effective in reducing model errors because of their small measurement error. SSM/I data are most helpful in regions with few buoys, particularly in coastal areas, because of their better spatial coverage. Combining SSM/I data and buoy data for assimilation tends to mitigate each other's weaknesses and brings about the best overall model performance in simulating both ice motion and ice thickness.