Few areas of science are currently hotter than climate. Attempts to understand humankindÂ’s impact on our planet are occupying the front pages of countless newspapers and the minds of an increasingly informed public.

Climate change is likewise occupying a good percentage of processors on some of the worldÂ’s most powerful computing systems. Via simulation, researchers are beginning to comprehend the nuances of EarthÂ’s climate and in turn helping policymakers understand the risks and prepare for a myriad of future scenarios.

As sophisticated as todayÂ’s climate models are, however, one critical component continues to hamper their effectiveness: clouds. Turns out those white puffs of water vapor hovering overhead are computationally complex, requiring resources that even todayÂ’s most powerful supercomputers are hard pressed to furnish.

A large-scale attempt to resolve the effects of clouds, Project Athena: High Resolution Global Climate Simulations, just wrapped up a 6-months of intensive computing that consumed 70 million CPU-hours on Athena, a Cray XT4 system currently ranked the 36th fastest computer in the world; Athena is located at the National Institute for Computational Sciences, a National Science Foundation–funded research center managed by the University of Tennessee and located at Oak Ridge National Laboratory.

Besides explicitly modeling cloud systems, Project Athena featured hundreds of weather-prediction model simulations that sought to replicate the climate of the late 20th century and predict the impact of CO2 emissions on the EarthÂ’s climate in the final decades of the 21st century.

An international effort, Project Athena was the result of a partnership between climate research organizations from the United States (NICS, the Center for Ocean-Land-Atmosphere Studies), Europe (the European Center for Medium-Range Weather Forecasts), and Japan (the University of Tokyo and the Japan Agency for Marine-Earth Science and Technology).

“The ultimate goal of these simulations was to explore the possibility of revolutionizing climate and weather prediction, taking advantage of a large computing resource,” said principal investigator and COLA Director Jim Kinter.

According to Kinter, past climate models did not include clouds in the global climate system because the clouds were too computationally complex. Instead, they were treated in bulk and their behavior was largely estimated using approximations called parameterizations. These parameterizations may be the primary restraint preventing climate models from evolving from good to great, Kinter said.

The Project Athena team hypothesized that poor resolution of climate system features and approximated clouds in a climate model negatively influence the accuracy of the model, and that high resolution and explicit clouds, or clouds modeled in greater detail, will enhance it. To test this hypothesis, the scientists ran two suites of simulations; one used ECMWFÂ’s operational weather prediction code and the other used the University of TokyoÂ’s and JAMSTECÂ’s NICAM, a code that represents the global atmosphere at cloud-system-resolving scales.

Having the entire Athena system for six months allowed the team to study numerous phenomena at unprecedented scales, as low as seven kilometers in the case of the cloud-system-resolving model. In contrast, the US National Weather Service currently uses a 35-kilometer model for global weather prediction.

The hope entering the project was that if these smaller scales were successfully resolved, the more detailed simulations would lead to more realistic forecasting of atmospheric circulation and precipitation, enhancing seasonal predictions and more accurately simulating changes in the distribution and intensity of extremes of precipitation and tropical cyclones associated with changing climate.

Tropical cyclone intensity distribution, expressed as fractional frequency, as a function of maximum surface wind speed. The black bars are for the observed distribution. The colored bars are distributions from the ECMWF IFS model simulations. The inset shows an expanded view of the tail of the distribution. T1279, T511 and T159 signify the horizontal grid spacing of 16, 39 and 125 km, respectively. Image and caption courtesy NICS.

In total the cloud-system-resolving NICAM model simulations consisted of eight northern hemisphere summers (21 May–31 August). But did the use of explicit clouds rather than approximated ones improve the model? Yes and no.

The explicit cloud model produced excellent simulations of individual tropical cyclones and did very well on mean precipitation outside the tropics. However, when it came to the average precipitation in the deep tropics, the model produced “serious errors,” Kinter said, noting that tropical thunderstorms were modeled especially poorly. The problem with the tropical precipitation simulation in NICAM, said Kinter, was most likely the grid size, despite the enhanced resolution. “We probably need something like a one kilometer grid,” he said, noting that it will be some time before that is even remotely possible for global models. Why? To do the same amount of simulation with a one kilometer grid spacing, the team would need the equivalent of 512 Athenas for six months.

Needless to say it could be a while before tropical precipitation is modeled to the teamÂ’s liking. In the meantime the Project Athena team made the most of its six months, especially in the arena of simulating global atmospheric circulation, which plays a key role in weather prediction. The simulations using ECMWFÂ’s code, which included all of the major variables that describe the global atmosphere, gave the team a good idea of the strength of its model and further demonstrated and quantified the need for enhanced resolution in predictive climate models in general.

All of the simulations were run at four different resolutions: 125, 39, 16, and 10 kilometers. For each grid size, the team ran individual 13-month simulations covering a 48 year period (November 1960–December 2007) and continuous 48-year simulations. Furthermore, in an effort to gauge future climate scenarios impacted by CO2, Project Athena simulated the last 30 years of the 20th and 21st centuries, which confirmed some long-held fears.

For example, assuming CO2 levels continue to increase, the model showed definite snow cover decreases at high altitudes, which could lead to droughts in certain parts of the world. It also confirmed the need for more refined models because the outcomes of the higher resolution models (16 kilometer grid spacing) seemed to be more accurate than those at lower resolutions (125 kilometer grid spacing). As an example Kinter cited the 2003 European heat wave: was it a freak incident or something likely to happen again in the future? Such heat waves won't necessarily become the norm, according to the higher resolution model. But the high resolution model found them to be more likely than did the low resolution model, and the higher resolution model has proven to be more accurate on things that affect European climate, said Kinter.

Team members from COLA, ECMWF, and JAMSTEC/University of Tokyo met in June 2010 at a workshop at ECMWF, said Kinter, and outlined about a half dozen papers to be extracted from the research that they expect to begin appearing in 2011. Furthermore, he said, there has been a large demand for the resulting data, which the team is now working to make public.

Ultimately, Project Athena has provided the climate community with a treasure trove of data and laid the foundation for future climate experiments and simulations. The full benefits of the effort have yet to be measured, but there is little doubt that it will be seen as a huge stepping stone on the path to truly understanding the EarthÂ’s climate.

“Project Athena has succeeded in showing that increasing the spatial resolution of models of the global climate system to levels that are currently only available for short-term weather forecasting can significantly increase the fidelity of climate simulations,” Kinter said. “Many features of the climate are better represented in high-resolution simulations, including obvious things like tropical cyclones and the distribution of snowfall and not-so-obvious things like the extent, duration, and frequency of drought. The implications of this experiment for how we simulate and predict the climate in the future are very important.”

A version of this article originally appeared on the NICS website.

—Scott Jones, NICS