MCore: A High-Order Finite-Volume Dynamical Core for Atmospheric General Circulation Models
Abstract
The desire for increasingly accurate predictions of the atmosphere has driven numerical models to smaller and smaller resolutions, while simultaneously exponentially driving up the cost of existing numerical models. Even with the modern rapid advancement of computational performance, it is estimated that it will take more than twenty years before existing models approach the scales needed to resolve atmospheric convection. However, smarter numerical methods may allow us to glimpse the types of results we would expect from these fine-scale simulations while only requiring a fraction of the computational cost. The next generation of atmospheric models will likely need to rely on both high-order accuracy and adaptive mesh refinement in order to properly capture features of interest. We present our ongoing research on developing a set of ``smart'' numerical methods for simulating the global non-hydrostatic fluid equations which govern atmospheric motions. We have harnessed a high-order finite-volume based approach in developing an atmospheric dynamical core on the cubed-sphere. This type of method is desirable for applications involving adaptive grids, since it has been shown that spuriously reflected wave modes are intrinsically damped out under this approach. The model further makes use of an implicit-explicit Runge-Kutta-Rosenbrock (IMEX-RKR) time integrator for accurate and efficient coupling of the horizontal and vertical model components. We survey the algorithmic development of the model and present results from idealized dynamical core test cases, as well as give a glimpse at future work with our model.
- Publication:
-
AGU Fall Meeting Abstracts
- Pub Date:
- December 2011
- Bibcode:
- 2011AGUFM.A11J..07U
- Keywords:
-
- 0545 COMPUTATIONAL GEOPHYSICS / Modeling;
- 0550 COMPUTATIONAL GEOPHYSICS / Model verification and validation;
- 3337 ATMOSPHERIC PROCESSES / Global climate models;
- 3367 ATMOSPHERIC PROCESSES / Theoretical modeling