| Summary: | Motivated by abundant sources of data and the need to improve weather prediction capabilities, data assimilation has a long history in atmospheric modeling. Data assimilation applied to sea-ice models, on the other hand, is in its infancy. Most of the investigations over the past twenty years falls into one of three categories: (1) the statistical interpolation of data into gridded fields (Thorndike and Colony, 1983), (2) advanced assimilation methods applied to simplified “box” style sea-ice models (Thomas and Rothrock, 1989), and (3) the non-statistical assimilation of ice data (Maslanik and Maybee, 1994). While the work of Maslanik and Maybee comes closest, no one had tackled the problem of statistically assimilating data into a full-featured sea-ice model. This situation changed with the work of Meier et al. (2000). They assimilated ice motions derived from passive microwave imagery into a fully dynamic-thermodynamic sea-ice model using optimal interpolation, a statistical interpolation technique. Their success motivated this project.
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