AulignŽ, Thomas, National Center for Atmospheric
Research, and Luke Peffers, Air Force Technical Applications Center
Ensemble/variational
hybrid data assimilation systems are currently under a lot of scrutiny. They
are very attractive because they show the potential to leverage the robustness
and efficiency of variational systems with the flow dependency and uncertainty estimation
from Ensemble Kalman Filters (EnKFs). The drawback is that it requires to
develop, interface and maintain
two separate data assimilation systems. We propose a new approach for updating
the ensemble perturbations within the variational system and without the need
for an extra EnKF system. We will explain the implementation and show results
for the WRF model in full ensemble data assimilation mode. The evolution of the
analysis and the ensemble spread will be studied and compared to a state-of-the-art
EnKF system. This new approach is much simpler to implement and can be used in
hybrid mode.