A collaboration, bringing together an international team of over 30 people, from six institutions on three continents, including climate and weather scientists and modelers and experts in high-performance computing (HPC), applied dedicated HPC resources to rapidly accelerate progress in addressing one of the most critical problems facing the global community, namely, global climate change. The scientific basis for undertaking this project was established in the May 2008 World Modeling Summit.

The numerical experiments were intended to determine whether increasing weather and climate model resolution to accurately resolve mesoscale phenomena in the atmosphere can improve the fidelity of the models in simulating the mean climate and the distribution of variances and covariances. Explicitly resolving cloud processes in the atmosphere without approximation by parameterization was examined as well. The effect of increasing greenhouse gas concentrations, associated with global warming, on the regional aspects of extreme temperature and precipitation, storminess, floods and droughts in key regions of the world also was evaluated in these experiments.

The two sets of numerical experiments were conducted with two different models. One was an experimental version of the European Centre for Medium-range Weather Forecasts (ECMWF) Integrated Forecast System (IFS), a global atmospheric general circulation model, which is used operationally every day to produce 10-day weather forecasts. The IFS was run at several resolutions down to 10-km grid spacing to evaluate the statistical distribution and nature of high-impact and extreme events in 20th and 21st century simulations. The other was the NICAM global atmospheric model from the Japan Agency for Marine-Earth Science and Technology (JAMSTEC), which was run at 7-km, cloud-system-resolving grid resolution to simulate the boreal summer climate, over many years, focusing on tropical cyclones, monsoon systems, and summer flood and drought situations. Both models were run in long simulations for the first time in the U.S.

These computationally-intensive experiments used the entire 18,048-core Athena Cray XT-4 supercomputer at the University of Tennessee’s National Institute for Computational Sciences (NICS) for the period October 2009 – March 2010. The project stretched the limits of CPU, disk, I/O, metadata management and tape archive resources. The data generated by this project will be made available to the communities of climate scientists interested in analyzing high-resolution climate simulations and computational scientists who can learn about operational considerations of running dedicated production at nearly petascale.

This work is in collaboration with D. Achutavarier, J. Adams, E. Altshuler, P. Andrews, B. Cash, B. Huang, E. Jin, L. Marx, J. Manganello, T. Palmer, M. Satoh, C. Stan, and H. Tomita.