The
use of the data assimilation technique to identify optimal topography is
discussed in frames of time-dependent motion governed by nonlinear 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 length of the
assimilation window in 4DVar is discussed. It is shown that using longer window
lengths would provide more accurate ocean topography. The topography defined
using this technique can be further used in other model runs that start from
other initial conditions and are situated in other parts of the model’s
attractor.
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