A compatible and conservative spectral element method on unstructured grids

Taylor, Mark A.; Fournier, A.

doi:10.1016/j.jcp.2010.04.008

Cited by 189 publications

(162 citation statements)

References 37 publications

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“…The Accelerated Climate Model for Energy-Atmosphere (ACME-A) has much in common with the Community Atmosphere Spectral Element Model (CAM-SE) (Dennis et al, 2012) as both share a common origin in the High Order Method Modeling Environment (HOMME) (Taylor and Fournier, 2010). ACME-A employs both a hydrostatic model and an experimental non-hydrostatic compressible shallowatmosphere model.…”

Section: Accelerated Climate Model For Energy-atmosphere (Acme-a)mentioning

confidence: 99%

DCMIP2016: a review of non-hydrostatic dynamical core design and intercomparison of participating models

et al. 2017

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Abstract. Atmospheric dynamical cores are a fundamental component of global atmospheric modeling systems and are responsible for capturing the dynamical behavior of the Earth's atmosphere via numerical integration of the NavierStokes equations. These systems have existed in one form or another for over half of a century, with the earliest discretizations having now evolved into a complex ecosystem of algorithms and computational strategies. In essence, no two dynamical cores are alike, and their individual successes suggest that no perfect model exists. To better understand modern dynamical cores, this paper aims to provide a comprehensive review of 11 non-hydrostatic dynamical cores, drawn from modeling centers and groups that participated in the 2016 Dynamical Core Model Intercomparison Project (DCMIP) workshop and summer school. This review includes a choice of model grid, variable placement, vertical coordinate, prognostic equations, temporal discretization, and the diffusion, stabilization, filters, and fixers employed by each system.

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Section: Accelerated Climate Model For Energy-atmosphere (Acme-a)mentioning

confidence: 99%

DCMIP2016: a review of non-hydrostatic dynamical core design and intercomparison of participating models

et al. 2017

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“…The global climate model used in this study is CAM5 with the spectral element dynamical core [Taylor and Fournier, 2010;Dennis et al, 2012] on a cubed sphere grid at NE30 resolution (about 110 km grid spacing) with 30 vertical layers. Deep convection is treated with the mass flux parameterization of Zhang and McFarlane [1995], with further modifications by Richter and Rasch [2008], Neale et al [2008], and Suhas and Zhang [2014].…”

Section: Model Description and Simulation Setupmentioning

confidence: 99%

Can nudging be used to quantify model sensitivities in precipitation and cloud forcing?

Lin

Wan

Zhang

et al. 2016

J Adv Model Earth Syst

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Efficient simulation strategies are crucial for the development and evaluation of high‐resolution climate models. This paper evaluates simulations with constrained meteorology for the quantification of parametric sensitivities in the Community Atmosphere Model version 5 (CAM5). Two parameters are perturbed as illustrating examples: the convection relaxation time scale (TAU), and the threshold relative humidity for the formation of low‐level stratiform clouds (rhminl). Results suggest that the fidelity of the constrained simulations depends on the detailed implementation of nudging and the mechanism through which the perturbed parameter affects precipitation and cloud. The relative computational costs of nudged and free‐running simulations are determined by the magnitude of internal variability in the physical quantities of interest, as well as the magnitude of the parameter perturbation. In the case of a strong perturbation in convection, temperature, and/or wind nudging with a 6 h relaxation time scale leads to nonnegligible side effects due to the distorted interactions between resolved dynamics and parameterized convection, while 1 year free‐running simulations can satisfactorily capture the annual mean precipitation and cloud forcing sensitivities. In the case of a relatively weak perturbation in the large‐scale condensation scheme, results from 1 year free‐running simulations are strongly affected by natural noise, while nudging winds effectively reduces the noise, and reasonably reproduces the sensitivities. These results indicate that caution is needed when using nudged simulations to assess precipitation and cloud forcing sensitivities to parameter changes in general circulation models. We also demonstrate that ensembles of short simulations are useful for understanding the evolution of model sensitivities.

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“…The antisymmetry of {F, H } µ , {F, H } is equivalent to the discrete integrationby-parts formula (4), itself equivalent to the discretization of the horizontal div and grad operators being compatible (see e.g. Taylor and Fournier, 2010). The antisymmetry of {F, H } v results from w ee = −w ee and q ee = q e e (Ringler et al, 2010).…”

Section: Lagrangian Vertical Coordinatementioning

confidence: 99%

DYNAMICO-1.0, an icosahedral hydrostatic dynamical core designed for consistency and versatility

Dubos¹,

Dubey

Tort³

et al. 2015

Geosci. Model Dev.

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Abstract. The design of the icosahedral dynamical core DY-NAMICO is presented. DYNAMICO solves the multi-layer rotating shallow-water equations, a compressible variant of the same equivalent to a discretization of the hydrostatic primitive equations in a Lagrangian vertical coordinate, and the primitive equations in a hybrid mass-based vertical coordinate. The common Hamiltonian structure of these sets of equations is exploited to formulate energy-conserving spatial discretizations in a unified way.The horizontal mesh is a quasi-uniform icosahedral C-grid obtained by subdivision of a regular icosahedron. Control volumes for mass, tracers and entropy/potential temperature are the hexagonal cells of the Voronoi mesh to avoid the fast numerical modes of the triangular C-grid. The horizontal discretization is that of Ringler et al. (2010), whose discrete quasi-Hamiltonian structure is identified. The prognostic variables are arranged vertically on a Lorenz grid with all thermodynamical variables collocated with mass. The vertical discretization is obtained from the three-dimensional Hamiltonian formulation. Tracers are transported using a second-order finite-volume scheme with slope limiting for positivity. Explicit Runge-Kutta time integration is used for dynamics, and forward-in-time integration with horizontal/vertical splitting is used for tracers. Most of the model code is common to the three sets of equations solved, making it easier to develop and validate each piece of the model separately.Representative three-dimensional test cases are run and analyzed, showing correctness of the model. The design permits to consider several extensions in the near future, from higher-order transport to more general dynamics, especially deep-atmosphere and non-hydrostatic equations.

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A compatible and conservative spectral element method on unstructured grids

Cited by 189 publications

References 37 publications

DCMIP2016: a review of non-hydrostatic dynamical core design and intercomparison of participating models

DCMIP2016: a review of non-hydrostatic dynamical core design and intercomparison of participating models

Can nudging be used to quantify model sensitivities in precipitation and cloud forcing?

DYNAMICO-1.0, an icosahedral hydrostatic dynamical core designed for consistency and versatility

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