4-D Relaxation Ensemble Kalman Filter (4D-REKF)

4-D relaxation ensemble Kalman Filter (4D-REKF) data assimilation and forecasting system. 4D-REKF integrates and leverages the cutting-edge ensemble Kalman filter (ENKF) data assimilation scheme, which is currently being studied by many leading weather institutions and universities. 4D-REKF represents a new way to extend the traditional (intermittent) EnKF data assimilation method to a 4D continuous data assimilation paradigm that avoids the dynamic shocks associated with the intermittent EnKF processes. Through this project, NCAR will collaborate with SGCC/CEPRI to apply, specialize, and advance the 4D-REKF 4-D data assimilation scheme in the development of power-grid numerical weather prediction capabilities.  The overarching goal of 4D-REKF is to build up a strong backbone technology of RTFDDA, Ensemble-RTFDDA, Climate-FDDA, and FDDA-LES modeling technologies and produce robust weather information to support electric power production, transmission, and services of SGCC.  


Please direct questions/comments about this page to:

Scott Swerdlin

Director, National Security Applications Program