Monday, August 4, 2014

U.S. Weather Computers Are a Little More Super Today Than Yesterday


IDL TIFF file


If it seems, over the course of the next few weeks, that weather predictions are a little more accurate, then it's probably not your imagination. It's just that the computers that the U.S. Federal Government uses to predict the weather have gotten a lot smarter.



The National Oceanic and Atmospheric Administration, the parent agency of the National Weather Service, switched over to using two new IBM-made supercomputers, according to an interesting story from IDG's Computerworld.



The new machines are capable of 213 teraflops, or 213 trillion floating point operations per second. That's almost three times the power of the prior systems, which were capable of 74 teraflops. One will be in Reston, Va., and one will be in Orlando, Fla. The systems were "turned on" during a press event in College Park, Md..



While that's definitely some serious computing horsepower, it's well shy of the world's current supercomputing champ, China's Tianhe-2, which boasts a scorching 33.86 petaflops, or 33.86 quadrillion floating point operations per second.



How will you notice the difference? Since these computers will be the source of pretty much every weather forecast you're likely to see, including those found on all the weather apps on your smartphone, you may start noticing temperature predictions that are more accurate, especially in the extended forecasts.



Another - and probably more important - change should come in the accuracy of hurricane modeling. Last year, during Hurricane Sandy (pictured), there were criticisms that European forecasters used more accurate computer models to predict where the storm was heading.



As it turns out, there is a bit of a friendly competition going on between NOAA and the European Centre for Medium-Range Weather Forecasts, which had those better computer models. It's not sitting still, either. It just purchased a set of new Cray supercomputers, but hasn't yet disclosed their performance.


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