The quality of an ice forecast depends on a good initial condition, good boundary conditions, and a good physical model to integrate relevant equations forward in time. The aim of this project is to implement a variational method to reduce errors in ice initial conditions, a process usually referred to as data assimilation. This will be accomplished in several steps, involving (1) implementation of missing components in the variational ice data assimilation system, and (2) testing the system in a forecast environment applied to the Baltic Sea. The expected outcome of the project is improved Baltic Sea ice forecasts. The purpose of this document is to report on the progress made during the first year, roughly covering part (1) above, whereas the remaining part (2) has been reported at the end of 2011.