P66  Development and Evaluation of a WRF-Based Real-Time Very-Large-Eddy Simulation Scale NWP System

Wu, Wanli, Yubao Liu, Linlin Pan, Yuewei Liu, Jason Knievel, Rong-Shyang Sheu, National Center for Atmospheric Research/RAL, and John Pace, Scott Halvorson, Frank Gallagher Jr., U.S. Army Test and Evaluation Command, Dugway, Utah

Advances in scientific understanding of weather processes, rapid increases in computing power, and demands on precision fine-scale severe storms forecasting have promoted numerical weather prediction (NWP) developments toward to cloud-resolving and large-eddy simulation (LES) scales. Such ultra high resolution NWP possesses great potential for many weather-critical applications such as prediction of hazardous releases, wind power, military operations. Liu et al (2011) has developed a WRF-based multi-scale simultaneous-nestdown data assimilation and forecasting system, which employs a three-dimensional LES turbulence model at 100s meters grid spacing, and uses an improved nudging scheme in fine scale data assimilation. The across scale prediction system has been evaluated in simulating fine scale weather including tornado-like severe storms and topographic flows in regions with complex terrain. It has demonstrated robustness and additional skill at LES scales. The system has recently been adopted for operational wind power forecasting for an offshore wind farm in South Korea, with nested model grids spacing from 24.3km to 300 meters; has also been implemented for real-time experimental forecast at the Army Dugway Proving Ground, UT.  In this talk, we will review the configuration and the special model settings of the DPG VLES scale NWP system and its skills based on semi-operational forecasting outputs with intensive observational data for data assimilation and verification.  We will also study the impact of the LES model forecasting on transport and dispersion modeling at DPG.