On the possibility of correction of the forecasting of the Lorenz attractor dynamic characteristics using experimental data and data assimilation

In this paper the application of the Data Assimilation method based on Ensemble Kalman Filter to forecasting the Lorenz attractor dynamic characteristics is described. In the article the EnKF algorithm is described as applied to forecasting of the Lorenz attractor coordinates. The assessment of influence of the filter parameters on the quality of correction of the forecast is carried out. The importance of using before obtained forecast results in the filter window is noted. Primary principles of correction of forecast of dynamic characteristics in nonlinear systems based on EnKF are formulated. The obtained results allow the conclusion about the necessity of applying the Data Assimilation method to carrying out forecasts of various dynamic characteristics in nonlinear systems using the EnKF as a tool to be drawn. © Published under licence by IOP Publishing Ltd