Data assimilation using a hybrid variational-ensemble approach:  methodology and recent applications in numerical weather prediction

Xuguang Wang
University of Oklahoma


A hybrid variational and ensemble transform Kalman filter (ETKF) analysis method has been implemented for regional NWP using the WRF model. In the hybrid method, the variational framework is used to calculate the analysis increment using ensemble-based flow-dependent background-error covariances. To accommodate flow-dependent ensemble-based covariances within existing variational systems, an “extended control variable method” that includes covariance localization to account for sampling error was implemented. The ensemble transform Kalman filter was used to generate ensemble forecasts.

Recent studies have suggested that the hybrid systems may yield the “best of both worlds” by combining the best aspects of variational and ensemble Kalman filter (EnKF) systems. The advantages of the hybrid method will be discussed. Applications of the hybrid VAR-ETKF using WRF for various scales and data types will be discussed in the seminar. These include synoptic scale month-long experiments over North America domain, hurricane forecasts and radar assimilation for continental precipitation.