Accurately representing flow across the mesoscale to the microscale is a persistent roadblock for completing realistic microscale simulations. The science challenges that must be addressed to coupling at these scales include the following: 1) What is necessary to capture the variability of the mesoscale flow, and how do we avoid generating spurious rolls within the terra incognita between the scales? 2) Which methods effectively couple the mesoscale to the microscale and capture the correct nonstationary features at the microscale? 3) What are the best methods to initialize turbulence at the microscale? 4) What is the best way to handle the surface-layer parameterizations consistently at the mesoscale and the microscale? 5) How do we assess the impact of improvements in each of these aspects and quantify the uncertainty in the simulations? The U.S. Department of Energy Mesoscale-to-Microscale-Coupling project seeks to develop, verify, and validate physical models and modeling techniques that bridge the most important atmospheric scales determining wind plant performance and reliability, which impacts many meteorological applications. The approach begins with choosing case days that are interesting for wind energy for which there are observational data for validation. The team has focused on modeling nonstationary conditions for both flat and complex terrain. This paper describes the approaches taken to answer the science challenges, culminating in recommendations for best approaches for coupled modeling.
Coupled mesoscale–microscale simulations are required to provide time-varying weather-dependent inflow and forcing for large-eddy simulations under general flow conditions. Such coupling necessarily spans a wide range of spatial scales (i.e., ~10 m to ~10 km). Herein, we use simulations that involve multiple nested domains with horizontal grid spacings in the terra incognita (i.e., km) that may affect simulated conditions in both the outer and inner domains. We examine the impact on simulated wind speed and turbulence associated with forcing provided by a terrain with grid spacing in the terra incognita. We perform a suite of simulations that use combinations of varying horizontal grid spacings and turbulence parameterization/modeling using the Weather Research and Forecasting (WRF) Model using a combination of planetary boundary layer (PBL) and large-eddy simulation subgrid-scale (LES-SGS) models. The results are analyzed in terms of spectral energy, turbulence kinetic energy, and proper orthogonal decomposition (POD) energy. The results show that the output from the microscale domain depends on the type of turbulence model (e.g., PBL or LES-SGS model) used for a given horizontal grid spacing but is independent of the horizontal grid spacing and turbulence modeling of the parent domain. Simulation using a single domain produced less POD energy in the first few modes compared to a coupled simulation (one-way nesting) for similar horizontal grid spacing, which highlights that coupled simulations are required to accurately pass the mesoscale features into the microscale domain.
Abstract. The sensitivities of idealized large-eddy simulations (LESs) to variations of
model configuration and forcing parameters on quantities of interest to wind
power applications are examined. Simulated wind speed, turbulent fluxes,
spectra and cospectra are assessed in relation to variations in two physical
factors, geostrophic wind speed and surface roughness length, and several
model configuration choices, including mesh size and grid aspect ratio,
turbulence model, and numerical discretization schemes, in three different
code bases. Two case studies representing nearly steady neutral and
convective atmospheric boundary layer (ABL) flow conditions over nearly flat
and homogeneous terrain were used to force and assess idealized LESs, using
periodic lateral boundary conditions. Comparison with fast-response velocity
measurements at 10 heights within the lowest 100 m indicates that most model
configurations performed similarly overall, with differences between observed
and predicted wind speed generally smaller than measurement variability.
Simulations of convective conditions produced turbulence quantities and
spectra that matched the observations well, while those of neutral
simulations produced good predictions of stress, but smaller than observed
magnitudes of turbulence kinetic energy, likely due to tower wakes
influencing the measurements. While sensitivities to model configuration
choices and variability in forcing can be considerable, idealized LESs are
shown to reliably reproduce quantities of interest to wind energy
applications within the lower ABL during quasi-ideal, nearly steady neutral
and convective conditions over nearly flat and homogeneous terrain.
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