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  • Author or Editor: J. D. Mirocha x
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J. D. Mirocha, J. K. Lundquist, and B. Kosović

Abstract

Two formulations of a nonlinear turbulence subfilter-scale (SFS) stress model were implemented into the Advanced Research Weather Research and Forecasting model (ARW-WRF) version 3.0 for improved large-eddy simulation performance. The new models were evaluated against the WRF model’s standard Smagorinsky and 1.5-order turbulence kinetic energy (TKE) linear eddy-viscosity SFS stress models in simulations of geostrophically forced, neutral boundary layer flow over both flat terrain and a shallow, symmetric transverse ridge. Comparisons of simulation results with similarity profiles indicate that the nonlinear models significantly improve agreement with the expected profiles near the surface, reducing the overprediction of near-surface stress characteristic of linear eddy-viscosity models with no near-wall damping. Comparisons of simulations conducted using different mesh sizes indicate that the nonlinear model simulations at coarser resolutions agree more closely with the higher-resolution results than corresponding lower-resolution simulations using the standard WRF SFS stress models. The nonlinear models produced flows featuring a broader range of eddy sizes, with less spectral power at lower frequencies and more spectral power at higher frequencies. In simulated flow over the transverse ridge, distributions of flow separation and reversal near the surface simulated at higher resolution were likewise better depicted in coarser-resolution simulations using the nonlinear models.

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Megan H. Daniels, Katherine A. Lundquist, Jeffrey D. Mirocha, David J. Wiersema, and Fotini K. Chow

Abstract

Mesoscale atmospheric models are increasingly used for high-resolution (<3 km) simulations to better resolve smaller-scale flow details. Increased resolution is achieved using mesh refinement via grid nesting, a procedure where multiple computational domains are integrated either concurrently or in series. A constraint in the concurrent nesting framework offered by the Weather Research and Forecasting (WRF) Model is that mesh refinement is restricted to the horizontal dimensions. This limitation prevents control of the grid aspect ratio, leading to numerical errors due to poor grid quality and preventing grid optimization. Herein, a procedure permitting vertical nesting for one-way concurrent simulation is developed and validated through idealized cases. The benefits of vertical nesting are demonstrated using both mesoscale and large-eddy simulations (LES). Mesoscale simulations of the Terrain-Induced Rotor Experiment (T-REX) show that vertical grid nesting can alleviate numerical errors due to large aspect ratios on coarse grids, while allowing for higher vertical resolution on fine grids. Furthermore, the coarsening of the parent domain does not result in a significant loss of accuracy on the nested domain. LES of neutral boundary layer flow shows that, by permitting optimal grid aspect ratios on both parent and nested domains, use of vertical nesting yields improved agreement with the theoretical logarithmic velocity profile on both domains. Vertical grid nesting in WRF opens the path forward for multiscale simulations, allowing more accurate simulations spanning a wider range of scales than previously possible.

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