SciDAC: Climate Change Prediction Program

Accurate prediction of climate change on decadal and longer time scales remains a major scientific objective of the Environmental Sciences Division of DOE. The Climate Change Prediction Program (CCPP) is the current phase in the evolution of DOE's long-standing climate modeling and simulation research agenda. CCPP is focused on developing, testing and applying climate simulation and prediction models that stay at the leading edge of scientific knowledge and computational technology. CCPP will continue the development of models based on more definitive theoretical foundations and improved computational methods that will run efficiently on current and future generations of high-performance scientific supercomputers. The intent is to increase dramatically both the accuracy and throughput of computer model-based predictions of future climate system response to the increased atmospheric concentrations of greenhouse gases.

Concurrently, to meet the challenge posed by the new generation of terascale computers with peak speeds of 10 to 100 trillion Operations Per Second (teraOPS), SC will fund a set of coordinated investments in scientific computing, through its Scientific Discovery through Advanced Computing (SciDAC) Program. SciDAC will create a scientific computing software infrastructure that bridges the gap between the advanced computing technologies being developed by the computer industry and the scientific research programs sponsored by the Office of Science. The CCPP portion of SciDAC has been labeled the Accelerated Climate Prediction Initiative.

SciDAC Climate will develop the next generation of climate prediction models. Over the next two to five years, these models will be used to predict climate variability and climate change decades to centuries in the future under a variety of forcing scenarios. This will complement the CCPP's basic research component that is looking to develop the knowledge to build succeeding generations of models beyond the five-year time horizon. Multi-disciplinary research teams will address both climate science and computational science challenges facing the development of production-quality climate GCMs in the two to five year time frame. These challenges include, but are not limited to, improving component model performance and accuracy, implementing efficient coupling strategies, and maximizing throughput on high-end computers that are anticipated to have theoretical peak speeds of 10 - 50 TeraOPS.