Method of dynamic model results correction by observational data and its application in oceanography

New method of data assimilation for the correction of model computations is developed and applied. The method is based on the path of least resistance principle and uses the theory of diffusion stochastic processes and stochastic differential equations. Derived from this principle the system of linear equations is needed to be solved to apply this method. This system may be considered as a generalization of the known Kalman scheme when dynamics of the model is taken into account.
The method is applied to numerical experiments in conjunction with model circulation HYCOM and satellite sea level observational data from archive AVISO for Atlantic. The skill of the method is assessed using the results of the experiments. The model output is compared with twin experiments, namely the model calculation without assimilation and one comes to the conclusion that the proposed method is consistent and robust.