SCIENCE

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 Earth’s climate in the final decades of the 21st century.

The Project Athena effort, which represented one of the most intensive and ambitious climate simulation projects in history, was funded by NSF and was the result of a partnership of climate research organizations from the United States (NICS, the Center for Ocean-Land-Atmosphere Studies [COLA]), Europe (the European Centre for Medium-Range Weather Forecasts [ECMWF]), and Japan (the University of Tokyo and the Japan Agency for Marine-Earth Science and Technology [JAMSTEC]).

“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 clouds are too computationally complex to have been accurately included as a part of the global climate system in past climate models. 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, said Kinter.

Two suites of simulations, one using ECMWF’s operational weather prediction code and the other using the University of Tokyo’s and JAMSTEC’s NICAM, a code that represents the global atmosphere at cloud-system-resolving scales, were run to test one hypothesis: poor resolution of climate system features and approximated clouds in a climate model negatively influence the accuracy of the model; high resolution and explicit clouds, or clouds modeled in greater detail, will enhance it.

Having the entire Athena system for 6 months allowed the team to study numerous phenomena at unprecedented scales, as low as 7 kilometers in the case of the cloud-system-resolving model. For comparison, the 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.

In total the cloud-system-resolving NICAM model simulations consisted of eight northern hemisphere summers (May 21–August 31). 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,” said Kinter, 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 1-kilometer grid,” he said, noting that it will be some time before that is even remotely possible for global models, considering that given the geometry of the grid and numerical stability factors, the team would need the equivalent of 512 Athenas for 6 months to do the same amount of simulation at 1-kilometer grid spacing.

Needless to say it could be a while before tropical precipitation is modeled to the team’s liking. In the meantime the Project Athena team made the most of its 6 months, especially in the arena of simulating global atmospheric circulation, which plays a key role in weather prediction. The simulations using ECMWF’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.