Error analysis and assimilation of remotely sensed ice motion within an Arctic sea ice model

New sea ice motion fields available from remotely sensed data are potential ly useful for assessing and improving models of the polar ice pack. Here we investigate the error characteristics of the observed ice motions relative to drifting buoys and a dynamic-thermodynamic ice model. A data assimilati on approach is then used to assess the potential of the motion data for red ucing model biases, as well as the potential of the model to serve as an in terpolation tool to generate improved ice motion data sets. Special Sensor Microwave/Imager (SSM/I) derived and model simulated ice motions for the ye ars 1988 through 1993 are compared with ice displacement observations from drifting buoys. Variability and biases are summarized for seasonal and regi onal means. SSM/I motions are assimilated into the model using an optimal i nterpolation method that accounts for the modeled and SSM/I motion error va riances and the number and distribution of the SSM/I motions. Modeled and S SM/I-derived motions are found to have comparable mean errors, With some no table regional and seasonal differences. Assimilation substantially reduces the error standard deviation and improves the correlation of the simulated motions relative to the buoy observations, but some biases remain. In the model framework used here, assimilation of the SSM/I data substantially alt ers average ice thickness in some regions of the Arctic and affects ice mas s outflow through the Fram Strait but has a small effect on mean ice concen tration. The assimilation yields an increase in the spatial and temporal va riability in ice deformation. The observations are particularly suited for improving the simulation of specific synoptic events, where substantial dif ferences can occur between simulated and observed ice transport.