THE ENSEMBLE KALMAN FILTER THEORY AND METHOD DEVELOPMENT

Nowadays,data assimilation has played an important role in research of atmosphere and ocean.Four dimension variation may be considered a better data assimilation method.But with data assimilation method developing,a new data assimilation method— ensemble Kalman filter is becoming popular.As a sequential data assimilation method,ensemble Kalman filter is similar to Kalman filter that has been presented by Kalman in 1960 but hard to apply to atmospheric data assimilation in operation for large calculating cost.Ensemble method makes Kalman filter available and has made a great progress in past ten years.After review development of data assimilation and ensemble Kalman filter,the virtue of ensemble Kalman filter is discussed.Getting a flow-dependent background error covariance may be a most attractive character of ensemble Kalman filter.Also,the problem of ensemble Kalman filter applied is discussed in this paper.Since we can just use finite ensemble in ensemble Kalman filter,simple error is unavoidable and will bring some severe problems,for instance,filter divergence.At the end,the future of ensemble Kalman filter is expected.Although no operational center has yet implemented ensemble Kalman filter,Canada has plan to do so.Besides,hybrid variation and four dimension variation may be mainstream of numeric weather prediction.