A Double Fourier Series (DFS) Dynamical Core in a Global Atmospheric Model with Full Physics

Abstract

Abstract This study describes an application of the double Fourier series (DFS) spectral method developed by Cheong as an alternative dynamical option in a model system that was ported into the Global/Regional Integrated Model System (GRIMs). A message passing interface (MPI) for a massive parallel-processor cluster computer devised for the DFS dynamical core is also presented. The new dynamical core with full physics was evaluated against a conventional spherical harmonics (SPH) dynamical core in terms of short-range forecast capability for a heavy rainfall event and seasonal simulation framework. Comparison of the two dynamical cores demonstrates that the new DFS dynamical core exhibits performance comparable to the SPH in terms of simulated climatology accuracy and the forecast of a heavy rainfall event. Most importantly, the DFS algorithm guarantees improved computational efficiency in the cluster computer as the model resolution increases, which is consistent with theoretical values computed from a dry primitive equation model framework. The current study shows that, at higher resolutions, the DFS approach can be a competitive dynamical core because the DFS algorithm provides the advantages of both the spectral method for high numerical accuracy and the gridpoint method for high performance computing in the aspect of computational cost.