a high-order finite-volume scheme for the dynamical core of weather and climate models christiane...

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A High-Order Finite-Volume Scheme for the Dynamical Core of Weather and Climate Models Christiane Jablonowski and Paul A. Ullrich, University of Michigan, Ann Arbor Overview Cubed-Sphere Grids Tests of the Nonhydrostatic Model at all Scales Idealized tests in Cartesian geometry that assess the model performance at the microscale (2D bubble resembling convection), mesoscale (2D mountain waves) and 3D global scale: The cubed- sphere grid consists of 6 faces (in red) that are subdivided (in blue). The grid point distribution is almost uniform. We use a non- ortho-gonal equiangular cubed-sphere grid. We collaborate with Phillip Colella (Lawrence Berkeley National Laboratory) and will soon introduce an Adaptive Mesh Refinement (AMR) Technique via the Chombo library. The future generation of atmospheric models used for weather and climate predictions will likely rely on both high-order accuracy and Adaptive Mesh Refinement (AMR) techniques in order to properly capture the atmospheric features of interest. We present our ongoing research on developing a set of conservative and highly accurate numerical methods for simulating the atmospheric fluid flow (the so-called dynamical core). In particular, we have developed a fourth-order finite-volume scheme for a nonhydrostatic dynamical core on a cubed-sphere grid (Ullrich and Jablonowki 2010, 2011a,b) that makes use of an implicit-explicit Runge-Kutta-Rosenbrock (IMEX-RKR) time integrator and Riemann solvers. We survey the algorithmic steps, present results from idealized dynamical core test cases and outline the inclusion of AMR into the model design. Algorithmic Design High-Order Sub-Grid Reconstructions and Source Terms High-order accuracy can be achieved in finite-volume methods using high-degree polynomials to locally reconstruct the prognostic variables in each cell. We make use of cubic polynomials to ensure our schemes achieve fourth-order accuracy. We utilize the convolution / deconvolution method by Barad and Colella (2005) to compute source terms and fluxes with fourth-order accuracy. Low-Speed Riemann Solver Numerical fluxes obtained from a reconstruction-based approach are computed using a Riemann solver. We have adapted a version of the low-diffusion AUSM + -up Riemann solver (Liou 2006), which was designed for aerospace applications at low Mach numbers. Implicit-Explicit Runge-Kutta-Rosenbrock Time Integrator 3D atmospheric models have a large horizontal grid spacing (10-400 km) compared to a relatively short vertical grid spacing (10-1000 m). Explicit numerical integration relies on time steps which are proportional to the grid size, so the maximum time step is determined by the highly restrictive vertical grid spacing. Our scheme couples a 2 nd -order implicit method in the vertical with a 4 th -order explicit RK Barad, M. and P. Colella, 2005: A fourth-order accurate local refinement method for Poisson’s equation. J. Comput. Phys., 209, 1-18 Colella, P., D. T. Graves, N. D. Keen, T. J. Ligocki, D. F. Martin, P. W. McCorquodale, D. Modiano, P. O. Schwartz, T. D. Sternberg, and B. V. Straalen, 2009: Chombo Software Package for AMR Applications Design Document Jablonowski and Williamson, 2006: A baroclinic instabilitiy test case for atmospheric model dynamical cores. Quart. J. Roy. Meteor. Soc., 132 (621C), 2943-2975 Liou, M.-S., 2006: A sequel to AUSM, Part II: AUSM+-up for all speeds. J. Comput. Phys., 214, 137-170 Reed, K. A. and C. Jablonowski, 2011: An analytic vortex initialization technique for idealized tropical cyclone studies in AGCMs, Mon. Wea. Rev.,139, 689-710 Ullrich, P. and C. Jablonowski, 2011a: Operator-split Runge-Kutta-Rosenbrock (RKR) methods for non- hydrostatic atmospheric models. Mon. Wea. Rev., in revision Ullrich, P. and C. Jablonowski, 2011b: MCore: A non-hydrostatic atmospheric dynamical core utilizing high- order finite-volume methods, J. Comput. Phys., in prep. for submission in May 2011 Ullrich, P. A., C. J. Jablonowski, and B. L. van Leer, 2010: High-order finite-volume models for the shallow-water equations on the sphere. J. Comput. Phys., 229, 6104-6134 References Tests of the Nonhydrostatic Model (MCORE) on the Cubed- Sphere Model MCORE: Surface pressure in hPa at day 9. The grid spacing is approx. 1x1 deg, with 26 levels. Intercomparison to the dynamical cores FV, FVcubed, Eulerian and HOMME that are part of NCAR’s Community Atmosphere Model We test our nonhydrostatic dynamical core on the cubed- sphere grid (MCORE, left) with the baroclinic wave test by Jablonowski and Williamson (2006). The right figure shows intercomparison plots from four NCAR dynamical cores. The high- order accuracy of MCORE suppresses the grid imprinting seen in 2 nd -order cubed-sphere models like FVcubed. The finite- volume scheme also prevents artifacts like spectral ringing (noise) seen in EUL and HOMME. MCORE Future Aqua-Planet Tests with Physics Parameterizations We have developed a tropical cyclone test case (Reed and Jablonowski, 2011) and will test MCORE with moist physics parameterizations. Idealized tropical cyclone simulations with NCAR’s dynamical cores. The wind speeds at day 10 differ significantly. Grid spacing: 1x1 deg, with 26 levels

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Page 1: A High-Order Finite-Volume Scheme for the Dynamical Core of Weather and Climate Models Christiane Jablonowski and Paul A. Ullrich, University of Michigan,

A High-Order Finite-Volume Scheme for the Dynamical Core of Weather and Climate ModelsChristiane Jablonowski and Paul A. Ullrich, University of Michigan, Ann Arbor

Overview Cubed-Sphere Grids Tests of the Nonhydrostatic Model at all Scales

Idealized tests in Cartesian geometry that assess the model performance at the microscale(2D bubble resembling convection), mesoscale (2D mountain waves) and 3D global scale:

The cubed-spheregrid consists of 6 faces (in red) that are subdivided (in blue). The grid point distribution is almost uniform. We use a non-ortho-gonal equiangularcubed-sphere grid.

We collaborate with Phillip Colella (Lawrence Berkeley National Laboratory) and will soon introduce an Adaptive Mesh Refinement (AMR) Technique via the Chombo library.

The future generation of atmospheric models used for weather and climate predictions will likely rely on both high-order accuracy and Adaptive Mesh Refinement (AMR) techniques in order to properly capture the atmospheric features of interest. We present our ongoing research on developing a set of conservative and highly accurate numerical methods for simulating the atmospheric fluid flow (the so-called dynamical core).

In particular, we have developed a fourth-order finite-volume scheme for a nonhydrostatic dynamical core on a cubed-sphere grid (Ullrich and Jablonowki 2010, 2011a,b) that makes use of an implicit-explicit Runge-Kutta-Rosenbrock (IMEX-RKR) time integrator and Riemann solvers. We survey the algorithmic steps, present results from idealized dynamical core test cases and outline the inclusion of AMR into the model design.

Algorithmic Design

High-Order Sub-Grid Reconstructions and Source TermsHigh-order accuracy can be achieved in finite-volume methods using high-degree polynomials to locally reconstruct the prognostic variables in each cell. We make use of cubic polynomials to ensure our schemes achieve fourth-order accuracy. We utilize the convolution / deconvolution method by Barad and Colella (2005) to compute source terms and fluxes with fourth-order accuracy.

Low-Speed Riemann SolverNumerical fluxes obtained from a reconstruction-based approach are computed using a Riemann solver. We have adapted a version of the low-diffusion AUSM+-up Riemann solver (Liou 2006), which was designed for aerospace applications at low Mach numbers.

Implicit-Explicit Runge-Kutta-Rosenbrock Time Integrator3D atmospheric models have a large horizontal grid spacing (10-400 km) compared to a relatively short vertical grid spacing (10-1000 m). Explicit numerical integration relies on time steps which are proportional to the grid size, so the maximum time step is determined by the highly restrictive vertical grid spacing. Our scheme couples a 2nd-order implicit method in the vertical with a 4th-order explicit RK method in the horizontal to relax the CFL restriction in the vertical, lengthen the time step and improve the computational performance.

Barad, M. and P. Colella, 2005: A fourth-order accurate local refinement method for Poisson’s equation. J. Comput. Phys., 209, 1-18

Colella, P., D. T. Graves, N. D. Keen, T. J. Ligocki, D. F. Martin, P. W. McCorquodale, D. Modiano, P. O. Schwartz, T. D. Sternberg, and B. V. Straalen, 2009: Chombo Software Package for AMR Applications Design Document

Jablonowski and Williamson, 2006: A baroclinic instabilitiy test case for atmospheric model dynamical cores. Quart. J. Roy. Meteor. Soc., 132 (621C), 2943-2975

Liou, M.-S., 2006: A sequel to AUSM, Part II: AUSM+-up for all speeds. J. Comput. Phys., 214, 137-170

Reed, K. A. and C. Jablonowski, 2011: An analytic vortex initialization technique for idealized tropical cyclone studies in AGCMs, Mon. Wea. Rev.,139, 689-710

Ullrich, P. and C. Jablonowski, 2011a: Operator-split Runge-Kutta-Rosenbrock (RKR) methods for non-hydrostatic atmospheric models. Mon. Wea. Rev., in revision

Ullrich, P. and C. Jablonowski, 2011b: MCore: A non-hydrostatic atmospheric dynamical core utilizing high-order finite-volume methods, J. Comput. Phys., in prep. for submission in May 2011

Ullrich, P. A., C. J. Jablonowski, and B. L. van Leer, 2010: High-order finite-volume models for the shallow-water equations on the sphere. J. Comput. Phys., 229, 6104-6134

References

Tests of the Nonhydrostatic Model (MCORE) on the Cubed-Sphere

Model MCORE: Surface pressure in hPa at day 9. The grid spacing is approx. 1x1 deg, with 26 levels.

Intercomparison to the dynamical cores FV, FVcubed, Eulerian and HOMME that are part of NCAR’s Community Atmosphere Model

We test our nonhydrostatic dynamical core on the cubed-sphere grid (MCORE, left) with the baroclinic wave test by Jablonowski and Williamson (2006). The right figure shows intercomparison plots from four NCAR dynamical cores. The high-order accuracy of MCORE suppresses the grid imprinting seen in 2nd-order cubed-sphere models like FVcubed. The finite-volume scheme also prevents artifacts like spectral ringing (noise) seen in EUL and HOMME.

MCORE

Future Aqua-Planet Tests with Physics Parameterizations

We have developed a tropical cyclone test case (Reed and Jablonowski, 2011) and will test MCORE with moist physics parameterizations.

Idealized tropical cyclone simulations with NCAR’s dynamical cores. The wind speeds at day 10 differ significantly.

Grid spacing: 1x1 deg, with 26 levels