Weather and Climate Forecasting

In the pantheon of HPC grand challenges, weather forecasting and long-term climate simulation rank right up there with the most complex and computationally demanding problems in astrophysics, aeronautics, fusion power, exotic materials,and earthquake prediction, to name just a few.

Modern weather forecasting requires cooperation in the collection of observed data and sharing of forecasts output among all nations, a collaboration that has been ongoing for decades. This data is used to simulate effects on a range of scales — from events, such as the path of tornadoes, that change from minute to minute and move over distances measured in meters, to turnover of water layers in the ocean, a process that is measured in decades or even hundreds of years, and spans thousands of miles.

The amount of data collected is staggering. Hundreds of thousands of surface stations, including airborne radiosondes, ships and buoys, aircraft, and dozens of weather satellites, are streaming terabytes of information every day. This data is interpolated to fit the three-dimensional grid that approximates the globe and over which the simulation is run to produce a forecast. The importance of this information cannot be understated, especially when it comes to anticipating, understanding and coping with weather and climate disasters. For example, according the National Centers for Environmental Informatics, there were eight U.S. weather and climate events in 2014 with losses exceeding $1 billion each, including droughts, tornadoes, flooding and severe storms such as a major winter storm event.

Because of the complexity involved, the length of the simulation period and the amounts of data generated, weather prediction and climate modeling on a global basis require some of the most powerful computers in the world. The models incorporate topography, winds, temperatures, radiation, gas emission, cloud forming, land and sea ice, vegetation and more. However, although weather prediction and climate modeling make use of common numerical methods, the items they compute differ.