P10  Enhancements to the Real-Time Operational NCAR-ATEC Ensemble-RTFDDA (E-4DWX) Forecasting System with NCAR DART-EnKF, WRF-NMM and SKEB

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.