  The use of data assimilation technique to identify optimal topography is
discussed in frames of time-dependent motion governed by non-linear barotropic
ocean model. Assimilation of artificially generated data allows to measure the
influence of various error sources and to classify the impact of noise that is
present in observational data and model parameters. The choice of assimilation
window is discussed. Assimilating noisy data with longer windows provides
higher accuracy of identified topography. The topography identified once by
data assimilation can be successfully used for other model runs that start from
other initial conditions and are situated in other parts of the model's
attractor.
