Research conducted by a team led by a Brown University physicist has revealed a statistical technique that can include small-scale dynamics in computer weather simulations of large-scale phenomena.
These small-scale dynamics include atmospheric air circulation and ocean currents.
Models produced by computers are designed to capture the big picture and quite often ignore small-scale goings on. Examples of this can be found in models of a planet’s atmosphere capturing jets and airflows, which are large-scale dynamics, and missing out on clouds and localized turbulence, the small-scale dynamics, even though these dynamics can potentially have an impact on the larger scale.
According to Brown physicist Brad Marston, the abundance of numbers involved in such a simulation are too many for a computer to process at a practical speed. Marston said that the simulation of a day of the atmosphere could take up to a year, which is far too long.
Marston and his colleagues have presented a way to average out small-scale dynamics that would allow the dynamics to be included in the simulation while capturing their effects. The small-scale degrees of freedom remain intact, but are treated in a different way.