Googling turns up some hits, but not much. The basic issue is that weather prediction is one of those problems that can always use more computational power. It

Googling turns up some hits, but not much. The basic issue is that weather prediction is one of those problems that can always use more computational power. It is even a known problem that the models used by the National Weather Service are inferior to the models used by agencies in Europe, and one of the things holding us back is raw computational power. From "Why Isn't the U.S. Better at Prediction Extreme Weather?" (http://www.nytimes.com/2016/10/23/magazine/why-isnt-the-us-better-at-predicting-extreme-weather.html?_r=0 http://www.nytimes.com/2016/10/23/magazine/why-isnt-the-us-b...): While Mass is the most outspoken on the subject, many experts insist that if the Weather Service wants to meaningfully improve its predictions, it must employ a technique called ensemble forecasting. The basic premise is either to tweak the physics equations or to make repeated changes to a model’s variables: You might bump up the temperature slightly, for example, and then run the model again. After a half-dozen or so reruns, you get a set, or “ensemble,” of forecasts that can be compared with one another. When all the forecasts in an ensemble agree, it’s a reasonably sure bet that the predictions will pan out. Nobody I’ve spoken to doubts the superiority of ensembles. Yet they haven’t been widely adopted in the United States at the resolution required to forecast localized, or “mesoscale,” events — specifically, thunderstorms, flash floods and tornadoes — because high-resolution ensembles require more computing power than the National Weather Service can currently provide. Higher-resolution ensembles translate to greater accuracy in the same way that HDTVs are clearer than analog sets. I met with a scientist at the National Center for Atmospheric Research in Boulder who showed me a prototype mesoscale ensemble for the United States. But at the moment, he can’t exploit its full potential because the supercomputing cluster at the Weather Service simply couldn’t handle the load. HPC systems are essentially designed for this type of computational problem, and we still want more powerful versions of it. For this reason, I find it unlikely that commodity cloud infrastructure - which was not explicitly designed for this type of problem, and it almost assuredly going to perform worse - will have much success in this area. At least in the near future.