IBM leverages machine learning for hyper-local weather

It's been just about six months since IBM closed its acquisition of The Weather Company, but it's not resting on its laurels. This week Big Blue moved to leverage The Weather Company's go-to-market strength to launch Deep Thunder, a machine learning-driven weather model developed by IBM Research to help industries ranging from aviation and agriculture to retail better predict the business impact of weather. "One of the greatest things about being part of IBM is having a relationship with IBM's Research arm," says Mary Glackin, head of Science & Forecast Operations for The Weather Company. The Weather Company is actually merging its existing Rapid Precision Mesoscale (RPM) model -- a numerical weather prediction system based on the Advanced Research Weather Research and Forecast System (WRF-ARW) -- with Deep Thunder. RPM generates forecasts up to 24 hours ahead, with updates every three hours in the U.S. and every six hours outside the U.S. Precipitation forecasts are calculated from half-hourly instantaneous precipitation forecasts provided by RPM.