Cheap and noisy chips could improve climate predictions

New Scientist: As scientists start to fill out the picture of a future globe dramatically changed by catastrophic global warming, the use of climate models is increasingly important when forecasting the risks faced by various regions. Tim Palmer and researchers at the European Centre for Medium-Range Weather Forecasts say that running simulations on cheap computer chips that produce results tainted with random noise could improve those models.

Many climate processes – such as cloud formation or the movement of air currents – are too complex to simulate exactly. Models approximate these processes over a particular region of the planet, dividing it into grids typically around 100 kilometres across. Different models, however, often fail to precisely match up because they vary in how their approximations are built. While researchers are striving to make the models more realistic, they are limited by the processing power of the supercomputers that run climate models, Palmer says. "That determines how fine of a grid we can solve the equations on, because of the computing cost," he says.

Adding a degree of randomness to a particular model and running it multiple times could provide a cheaper way to increase realism, Palmer and colleagues argue, as it could be a "poor man's surrogate for high-resolution models". If multiple, slightly different runs of a model come up with the same answer, it provides a hint of the strength of a prediction, according to the team. The technique has already been shown to work for weather forecasting over periods of a few weeks. "The time is now right to integrate this into climate models," Palmer says….

A supercell thunderstorm over Chaparall, New Mexico, in 2004, courtesy of NOAA