The project team will develop a cloud-resolving Earth system model with throughput necessary for multi-decade, coupled high resolution climate simulations. This next-generation model has the potential to substantially reduce major systematic errors in precipitation found in current models because of its more realistic and explicit treatment of convective storms. Consequently, it will improve our ability to assess regional impacts of climate change on the water cycle that directly affect multiple sectors of the US and global economies, especially agriculture and energy production. We will integrate a cloud-resolving convective parameterization (superparameterization) into the DOE ACME Earth System model using the Multiscale Modeling Framework (MMF), and explore its full potential to scientifically and computationally advance climate simulation and prediction. The superparameterization will be designed to make full use of GPU accelerated systems and we will also refactor and port other key components of the ACME model for GPU systems. In the first 4 years, we will target the OLCF Summit 100PF system, using performance portable approaches that prepare us for exascale and can also be extended to support multicore systems with additional resources. Most of our effort is devoted to making the MMF configuration of ACME exascale ready and performance portable: GPU optimization work and adopting new programming models for the performance-critical atmosphere, ocean and ice components. The close integration of scientific and computational development under this project to incorporate the cloud-resolving MMF capability will improve the simulation quality and accuracy of the weather-resolving ACME atmospheric model.
One of the DOE Exascale Computing Project Applications