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A multivariate data assimilation experiment was conducted in order to improve the global representation of both the ocean and sea ice fields through the inclusion of sea ice concentration (SIC) data. Our method corrects the surface forcing and ocean temperature fields (as well as the SIC field) through the use of three-dimensional variational analysis. The adjustments to surface air temperatures resulting from the SIC assimilation are estimated on the basis of two constraints. First, we assume that the interfacial temperature difference between the surface air and the average value at the 'top' of the grid (which represents a weighted mean according to the relative coverage of sea ice to open water within the grid) is maintained at the pre-assimilation value. Similarly, the vertical temperature structure for each of the five sea ice categories considered here remains unchanged throughout the assimilation. In making the necessary adjustments to upper-layer ocean temperatures, we again adopt a weighting procedure based on the condition that ice-free water temperature must remain the same. Thus, areas containing sea ice are allotted the freezing-point temperature such that the weighted mean value across the grid can be derived. The reproduction of the SIC field in both hemispheres is improved by incorporating the resulting corrections to the surface forcing and ocean temperature values, indicating that these boundary conditions produce results that are more consistent with the corrected SIC field in the sea ice model. The enhanced ocean-sea ice fields provide initial conditions that are better suited for coupled atmosphere-ocean-sea ice prediction experiments. [ABSTRACT FROM AUTHOR]