Coupled High-Resolution Modeling of the Earth System
Code: CM2
Allocation: 20 million hours
Advances in computing power are enabling climate simulations of unprecedented resolution, opening the door for researchers to analyze climate change at the regional level. Leading climate researchers to date have simulated cells of 100 kilometers—about 60 miles—for both atmosphere and ocean. As they take the next step, to cells of about 25 kilometers, they face the challenge of understanding natural and forced climate variability and a range of new physical processes. Researchers distinguish between natural or internal variations in climate, which might cause an increase in global temperature on a decade or longer time scale, from forced variations, those which are human or solar induced. At a resolution of 25 km, researchers begin to see the influence of both ocean eddies and organized atmospheric storm systems. An enhanced understanding of ocean dynamics may even allow them to predict climate changes a decade into the future.
The Coupled High-Resolution Modeling of the Earth System (CHiMES) project will use Oak Ridge National Laboratory’s petascale Jaguar supercomputer to conduct a series of long-term climate integrations using a coupled model of unprecedented resolution. A team led by Venkatramani Balaji of the National Oceanic and Atmospheric Administration (NOAA) and Princeton University’s Geophysical Fluid Dynamics Laboratory (GFDL) will use 20 million processor hours to conduct a first-of-its-kind, high-resolution, multicentury suite of climate simulations to parse and predict both natural and forced variability in the coupled climate system. The team will use CM2.5, one of an evolving family of atmospheric/ocean general circulation models that allow independent groups of scientists and algorithm developers to assemble components of the system independently. Underpinning this framework is a highly-scalable parallel communication fabric. The results will help us understand what we can expect from regional climate change in the near future and may inform the design of international modeling campaigns aimed at addressing these questions
