Numerical simulations of a convective boundary layer (CBL) are performed to investigate model behavior in the terra incognita, also known as the gray zone. The terra incognita of the CBL refers to a range of model grid spacing that is comparable to the size of the most energetic convective eddies, which are on the order of the boundary layer depth. Using the Rayleigh–Bénard thermal instability as reference, a set of idealized simulations is used to show that gray zone modeling is not only a numerical challenge, but also poses dynamical difficulties. When the grid spacing falls within the CBL gray zone, grid-dependent convection can occur. The size of the initial instability structures is set by the grid spacing rather than the natural state of the flow. This changes higher-order flow statistics and poses fundamental difficulties for gray zone modeling applications.
A critical challenge in characterizing land-atmosphere interactions across scales in Earth system models (ESMs) is the non-linearity that emerges as a result of spatial heterogeneities over land (
As model grid resolutions move from the mesoscale to the microscale, turbulent structures represented in atmospheric boundary layer simulations change dramatically. At intermediate resolutions, the so-called gray zone, turbulent motions are not resolved accurately, posing a challenge to numerical simulations. The representation of turbulence is also highly sensitive to the choice of closure model. Here, we examine explicit filtering and reconstruction in the gray zone as a technique to better represent atmospheric turbulence. The convective boundary layer is simulated using the Weather Research and Forecasting (WRF) Model with horizontal resolutions ranging from 25 m to 1 km. Four large-eddy simulation (LES) turbulence models are considered: the Smagorinsky model, the TKE-1.5 model, and two versions of the dynamic reconstruction model (DRM). The models are evaluated by their ability to produce consistent mean potential temperature profiles, heat and momentum fluxes, velocity fields, and turbulent kinetic energy spectra as the grids become coarser. The DRM, a mixed model that uses an explicit filtering and reconstruction technique to account for resolvable subfilter-scale (RSFS) stresses, performs very well at resolutions of 500 m and 1 km without any special tuning, whereas the Smagorinsky and TKE-1.5 models produce heavily grid-dependent results.
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