The evolution of the ECMWF hybrid data assimilation system

The trend towards using flow-dependent, ensemble-based estimates of background-error covariances has been one of the main themes of atmospheric data assimilation research and development in recent years. In this work it is documented how flow-dependent ensemble information from the ECMWF ensemble of data assimilations (EDA) has gradually been incorporated into the B model which describes the background-error covariance matrix at the start of the ECMWF 4D-Var assimilation window. Starting with background-error variances for the balanced part of the control vector and observation quality control, the current article extends the flow-dependency to background-error variances for the unbalanced part of the control vector and for background-error correlation structures. The correlations are determined either online from previous days or from a hybrid of climatological and current cycle estimates. Each of these changes is shown to improve both the realism of the modelled B and the accuracy of the analysis and forecast fields produced by the 4D-Var assimilation cycle which makes use of the improved B. Finally, increasing the resolution at which the EDA 4D-Vars are run is shown to reduce the underestimation of the EDA-based error estimates.