We present the massively parallel performance of a $h$-adaptive solver for atmosphere dynamics that allows for non-conforming mesh refinement. The numerical method is based on a Discontinuous Galerkin (DG) spatial discretization, highly scalable thanks to its data locality properties, and on a second order Implicit-Explicit Runge-Kutta (IMEX-RK) method for time discretization, particularly well suited for low Mach number flows. Simulations with non-conforming meshes for flows over orography can increase the accuracy of the local flow description without affecting the larger scales, which can be solved on coarser meshes. We show that the local refining procedure has no significant impact on the parallel performance and, therefore, both efficiency and scalability can be achieved in this framework.

翻译：本文展示了一种支持非一致网格细化的大气动力学$h$自适应求解器的大规模并行性能。该数值方法基于间断伽辽金空间离散格式（因其数据局部性而具有高度可扩展性）以及二阶隐式-显式龙格-库塔时间离散格式（特别适用于低马赫数流动）。针对地形上空流动采用非一致网格的模拟，可在不影响大尺度流动（可在较粗网格上求解）的前提下，提升局部流动描述的精度。研究表明，局部细化过程对并行性能无显著影响，因此在该框架下可同时实现高效性与可扩展性。