Enabling large eddy simulations with the Weather Research and Forecasting model via improved subfilter-scale turbulence models

The Weather Research and Forecasting model (WRF) is a state of the art atmospheric modeling system that can be employed to simulate an array of atmospheric flows, from the global scale circulation to turbulence-resolving applications (Skamarock, et. al, 2005). Historically WRF and other numerical weather prediction models have been used primarily to simulate flow down to the mesoscale. However, with the recent expansion of computational resources and increasing flexibility of atmospheric modeling systems, such models are increasingly being used to model flow at smaller and smaller scales, including large eddy simulations (LES).

To enhance WRF's applicability to LES, we have implemented three improved subfilter-scale stress (SFS) models into the ARW core. These include two improved subgrid models, the Nonlinear Backscatter and Anisotropy (NBA) Model of Kosovic (1997), and they Dynamic Eddy Viscosity model of Wong and Lilly (1994), as well as a model for the Resolvable Subfilter-Scale Stresses (RSFS), which models the effects of stresses arising from scales of the flow that are attenuated by numerical discretization errors (following Chow et al, 2005).

In this presentation, we demonstrate the improvements afforded by the new SFS models using data from idealized flow simulations. In particular we show that the new models improve both agreement with the logarithmic wind profile in neutral flow over flat terrain, and the representation of recirculation in the lee of a gently-sloping, two-dimensional hill. A companion paper (J. K. Lundquist et al.) demonstrates the applicability of this tool for wind energy forecasting applications.

This work is performed under the auspices of the U.S. Department of Energy by

Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344

UCRL# LLNL-PROC-400486