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The Model for Prediction Across Scales (MPAS) is a novel set ofEarth system simulation components and consists of an atmosphericmodel, an ocean model and a land-ice model. Its distinct featuresare the use of unstructured Voronoi meshes and C-grid discretisationto address shortcomings of global models on regular grids and the use oflimited area models nested in a forcing data set, with respect toparallel scalability, numerical accuracy and physicalconsistency. This concept allows one to include the feedback ofregional land use information on weather and climate at local<i>and</i> global scales in a consistent way, which is impossible to achievewith traditional limited area modelling approaches.  Here, we present an in-depth evaluation of MPAS with regards totechnical aspects of performing model runs and scalability for threemedium-size meshes on four different high-performance computing (HPC)sites with different architectures and compilers. We uncover modellimitations and identify new aspects for the model optimisation thatare introduced by the use of unstructured Voronoi meshes. We furtherdemonstrate the model performance of MPAS in terms of its capabilityto reproduce the dynamics of the West African monsoon (WAM) and itsassociated precipitation in a pilot study.Constrained by available computational resources, we compare11-month runs for two meshes with observations and a referencesimulation from the Weather Research and Forecasting (WRF) model.We show that MPAS can reproduce the atmospheric dynamics on globaland local scales in this experiment, but identify a precipitationexcess for the West African region.  Finally, we conduct extreme scaling tests on a global 3 km meshwith more than 65 million horizontal grid cells on up to halfa million cores. We discuss necessary modifications of the modelcode to improve its parallel performance in general and specific tothe HPC environment. We confirm good scaling (70 % parallelefficiency or better) of the MPAS model and provide numbers on thecomputational requirements for experiments with the 3 km mesh. Indoing so, we show that global, convection-resolving atmosphericsimulations with MPAS are within reach of current and nextgenerations of high-end computing facilities

Towards convection-resolving, global atmospheric simulations with the Model for Prediction Across Scales (MPAS) v3.1: an extreme scaling experiment