The project 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 U.S. and global economies, especially agriculture and energy production.

The project will involve integrating a cloud-resolving convective parameterization (superparameterization) into the DOE Energy Exascale Earth System Model (E3SM), by using the Multiscale Modeling Framework (MMF), and exploring 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.

Argonne’s work will focus on the Parallel I/O library PIO. We will evaluate and provide improved support of existing asynchronous I/O features in PIO, enhance it to support dynamic reconfiguration of PIO tuning parameters, and implement the basic framework for the asynchronous work queue in PIO. We will also evaluate or demonstrate the use of burst buffers with asynchronous I/O in the PIO library.