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This article was originally published by scientificcomputing.com and can be viewed in full here

When performing numerical weather predictions, it is important that the simulation itself be accurate, but it is also key for real-world data, based on observations, to be accurately entered into the model. Typically, weather simulations work by having the computer conduct a number of simulations based on the current state, and then entering observational data into the simulation to nudge it in a way that puts it closer to the actual state. The problem of incorporating data in the simulation — data assimilation — has become increasingly complex with the large number of types of available data, such as satellite observations and measurements taken from ground stations. Typically, supercomputers today spend an approximately equal amount of time running the simulations and incorporating the real-world data.

Now, with research that could lead to more accurate forecasts, researchers from the RIKEN Advanced Institute for Computational Science in Japan have run an enormous global weather simulation.

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