Pan, Linlin, National Center for Atmospheric Research,
Yubao Liu, Jason Knievel, Gregory Roux, Wanli Wu, Yonghui Wu, John Pace, Scott
Halvorson, Frank Gallagher, Dougway Proving Ground, US Army
WRF based E-RTFDDA
(ensemble real time four dimensional data assimilation) is an innovative
mesoscale real-time ensemble data analysis and forecasting system, which
contains multi-model, multi-physics and multi-perturbation approaches, and is
the core of ATEC (US Army Test and
Evaluation Command) four-dimensional weather system (E-4DWX). A 30-member
E-RTFDDA system with three nested domains with grid sizes of 30, 10 and 3.33 km
has been running on a Department of Defense high-performance computing platform
for years. The system has also been applied for supporting the Xcel Energy wind
energy prediction.
This paper reports
several new enhancements to the E-RTFDDA system. The NCAR DART-EnKF (Data
assimilation research testbed-ensemble Kalman filter) system has been
integrated into E-RTFDDA to enhance the E-RTFDDA member perturbation and data
assimilation. The enhancement allows DART EnKF to take the advantages of
E-RTFDDA by deriving error covariance using the multiple perturbation E-RTFDDA
forecasts; and meanwhile, updated EnKF means and a subset of EnKF members are used
to perturb initial conditions. Also integrated are the WRF-NMM (non-hydrostatic
mesoscale model system) and the WRF SKEB (stochastic kinetic-energy backscatter
scheme) ensemble perturbations. The results of the system performance and
sensitivity studies will be presented.