Title: Implementation Plans of Hybrid 4D EnVar for the NCEP GFS and Future Directions

The inclusion of flow-dependent, ensemble-based estimates of the background error covariances has been very successful as seen from the implementation of hybrid 3D EnVar into NCEP operations for the Global Forecast System (GFS) and Global Data Assimilation System (GDAS). Since then significant progress has been made toward the 4D extension of the algorithm, by including temporally evolving error estimates of the background. The hybrid 4D EnVar algorithm has a few attractive qualities for an operational center relative to traditional 4DVAR, most notably the lack of need for developing and maintaining a tangent linear and adjoint of the forward model as well as reduced computational cost. NCEP is planning to implement the hybrid 4D EnVar into operations for the GDAS/GFS in Q2FY16.

Results at reduced resolution have been extremely encouraging. The results from various sensitivity experiments will be presented. Results from an evolving near-real time full resolution parallel experiment will also be presented. Results from retrospective parallels are also expected to be available.

Beyond the initial implementation of hybrid 4D EnVar, various enhancements are still in their early phase of development such as improved data selection, the role of the static error covariance, incremental analysis update (IAU) and outer loop configuration. IAU will be explored as a means of gently forcing in the 4D increment into the model and will serve as a replacement for the full field digital filter for initialization. Using the IAU will hopefully allow the gradual spinup of moisture related quantities as well as retaining the increment. The IAU will also be used to initialize the ensemble.