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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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J. Ching, R. Rotunno, M. LeMone, A. Martilli, B. Kosovic, P. A. Jimenez, and J. Dudhia

Abstract

Mesoscale numerical weather prediction models using fine-grid [O(1) km] meshes for weather forecasting, environmental assessment, and other applications capture aspects of larger-than-grid-mesh size, convectively induced secondary circulations (CISCs) such as cells and rolls that occur in the convective planetary boundary layer (PBL). However, 1-km grid spacing is too large for the simulation of the interaction of CISCs with smaller-scale turbulence. The existence of CISCs also violates the neglect of horizontal gradients of turbulent quantities in current PBL schemes. Both aspects—poorly resolved CISCs and a violation of the assumptions behind PBL schemes—are examples of what occurs in Wyngaard’s “terra incognita,” where horizontal grid spacing is comparable to the scale of the simulated motions. Thus, model CISCs (M-CISCs) cannot be simulated reliably. This paper describes how the superadiabatic layer in the lower convective PBL together with increased horizontal resolution allow the critical Rayleigh number to be exceeded and thus allow generation of M-CISCs like those in nature; and how the M-CISCs eventually neutralize the virtual temperature stratification, lowering the Rayleigh number and stopping their growth. Two options for removing M-CISCs while retaining their fluxes are 1) introducing nonlocal closure schemes for more effective removal of heat from the surface and 2) restricting the effective Rayleigh number to remain subcritical. It is demonstrated that CISCs are correctly handled by large-eddy simulation (LES) and thus may provide a way to improve representation of them or their effects. For some applications, it may suffice to allow M-CISCs to develop, but account for their shortcomings during interpretation.

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Joseph B. Olson, Jaymes S. Kenyon, Irina Djalalova, Laura Bianco, David D. Turner, Yelena Pichugina, Aditya Choukulkar, Michael D. Toy, John M. Brown, Wayne M. Angevine, Elena Akish, Jian-Wen Bao, Pedro Jimenez, Branko Kosovic, Katherine A. Lundquist, Caroline Draxl, Julie K. Lundquist, Jim McCaa, Katherine McCaffrey, Kathy Lantz, Chuck Long, Jim Wilczak, Robert Banta, Melinda Marquis, Stephanie Redfern, Larry K. Berg, Will Shaw, and Joel Cline

Abstract

The primary goal of the Second Wind Forecast Improvement Project (WFIP2) is to advance the state-of-the-art of wind energy forecasting in complex terrain. To achieve this goal, a comprehensive 18-month field measurement campaign was conducted in the region of the Columbia River basin. The observations were used to diagnose and quantify systematic forecast errors in the operational High-Resolution Rapid Refresh (HRRR) model during weather events of particular concern to wind energy forecasting. Examples of such events are cold pools, gap flows, thermal troughs/marine pushes, mountain waves, and topographic wakes. WFIP2 model development has focused on the boundary layer and surface-layer schemes, cloud–radiation interaction, the representation of drag associated with subgrid-scale topography, and the representation of wind farms in the HRRR. Additionally, refinements to numerical methods have helped to improve some of the common forecast error modes, especially the high wind speed biases associated with early erosion of mountain–valley cold pools. This study describes the model development and testing undertaken during WFIP2 and demonstrates forecast improvements. Specifically, WFIP2 found that mean absolute errors in rotor-layer wind speed forecasts could be reduced by 5%–20% in winter by improving the turbulent mixing lengths, horizontal diffusion, and gravity wave drag. The model improvements made in WFIP2 are also shown to be applicable to regions outside of complex terrain. Ongoing and future challenges in model development will also be discussed.

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