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  • Author or Editor: Meelis J. Zidikheri x
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Meelis J. Zidikheri and Jorgen S. Frederiksen

Abstract

Inverse methods for determining the anomalous mean forcing functions responsible for climate change are investigated. First, an iterative method is considered, and it is shown to successfully reproduce forcing functions for various idealized and observed climate states using quasigeostrophic simulations. Second, a new inverse method that is more computationally efficient is presented. This method closes the mean-field equations by representing the second-order statistical moments, the transient eddy heat and momentum (or potential vorticity) fluxes, as linear functions of the mean field. The coefficients of the linear parameterization are determined by least squares regression. It is shown that the new method also successfully reproduces the anomalous forcing functions responsible for climatic changes in quasigeostrophic simulations.

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Meelis J. Zidikheri and Jorgen S. Frederiksen

Abstract

A stochastic subgrid modeling method is used to parameterize horizontal and vertical subgrid-scale transfers in large-eddy simulations (LESs) of baroclinic flows with large-scale jets and energy spectra typical of the atmosphere. The approach represents the subgrid-scale eddies for LES (at resolutions of T63 and T31) by a stochastic model that takes into account the memory effects of turbulent eddies. The statistics of the model are determined from a higher-resolution (T126) direct numerical simulation (DNS). The simulations use a quasigeostrophic two-level model and the subgrid terms are inhomogeneous in the vertical and anisotropic in the horizontal and are represented by 2 × 2 matrices at each wavenumber. The parameterizations have the largest magnitudes at a cusp near the largest total wavenumbers of the truncations. At T63 the off-diagonal elements of the matrices are negligible (corresponding to effectively decoupled levels) and the diagonal elements are almost isotropic. At the lower resolution of T31 the off-diagonal elements are more important and even the diagonal elements are more anisotropic. At both resolutions, and for anisotropic or isotropized subgrid terms, LESs are in excellent agreement with higher-resolution DNS.

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Vassili Kitsios, Jorgen S. Frederiksen, and Meelis J. Zidikheri

Abstract

Subgrid-scale parameterizations with self-similar scaling laws are developed for large-eddy simulations (LESs) of atmospheric flows. The key new contribution is the development of scaling laws that govern how these parameterizations depend on the LES resolution and flow strength. Both stochastic and deterministic representations of the effects of subgrid-scale eddies on the retained scales are considered. The stochastic subgrid model consists of a backscatter noise term and a drain eddy viscosity, while in the deterministic subgrid model the net effect of these two terms is represented by a net eddy viscosity. In both cases the subgrid transfers are calculated self-consistently from the statistics of higher-resolution-reference direct numerical simulations (DNSs). The dependence of the subgrid parameterizations on the resolution of the LESs is determined for DNSs having resolutions up to triangular 504 wavenumber truncations. The subgrid parameterizations are developed for typical large-scale atmospheric flows and for different strengths and spectra of kinetic energy within a quasigeostrophic spectral model. LESs using the stochastic and deterministic subgrid parameterizations are shown to replicate the kinetic energy spectra of the reference DNS at the scales of the LESs. It is found that the maximum strengths of the drain, net, and backscatter viscosities satisfy scaling laws dependent on the LES truncation wavenumber and that the dependence of these eddy viscosities on total wavenumber can also be written as essentially universal functions that depend on flow strength and resolution. The scaling laws make the subgrid-scale parameterizations more generally applicable in LESs and remove the need to generate them from reference DNSs.

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