We derive an implicit-explicit (IMEX) formalism for the three-dimensional (3D) Euler equations that allow a unified representation of various nonhydrostatic flow regimes, including cloud resolving and mesoscale (flow in a 3D Cartesian domain) as well as global regimes (flow in spherical geometries). This general IMEX formalism admits numerous types of methods including single-stage multistep methods (e.g., Adams methods and backward difference formulas) and multistage singlestep methods (e.g., additive Runge-Kutta methods). The significance of this result is that it allows a numerical model to reuse the same machinery for all classes of time-integration methods described in this work. We also derive two classes of IMEX methods, one-dimensional and 3D, and show that they achieve their expected theoretical rates of convergence regardless of the geometry (e.g., 3D box or sphere) and introduce a new second-order IMEX Runge-Kutta method that performs better than the other second-order methods considered. We then compare all the IMEX methods in terms of accuracy and efficiency for two types of geophysical fluid dynamics problems: buoyant convection and inertia-gravity waves. These results show that the high-order time-integration methods yield better efficiency particularly when high levels of accuracy are desired.
Introduction.In a previous article [20] we introduced the nonhydrostatic unified model of the atmosphere (NUMA) for use in limited-area modeling (i.e., mesoscale or regional flow), namely, applications in which the flows are in large, three-dimensional (3D) Cartesian domains (imagine flow in a 3D box where the grid resolutions are below 10 km); the emphasis of that paper was on the performance of the model on distributed-memory computers with a large number of processors. In that paper we showed that the explicit RK35 time integrator (also used in this paper) was able to achieve strong linear scaling for processor counts on the order of 10 5 . The emphasis of the present article is on the mathematical framework of the model dynamics (i.e., we are not considering the subgrid-scale parameterization at this point;