IBM and its subsidiary The Weather Company unveiled a powerful new global weather forecasting system that will provide several-fold more accurate local weather forecasts than current solutions.
"The new IBM Global High-Resolution Atmospheric Forecasting System (GRAF) will be the first hourly-updating commercial weather system that is able to predict something as small as thunderstorms globally," said the company. Compared to existing models, it will provide a nearly 200 per cent improvement in forecasting resolution for much of the globe from 12 to 3 square kilometer.
Predictions from the new system will be made available globally later in 2019, helping airlines to better minimise disruption from turbulence; insurers to better prepare for storm recovery operations; utility companies to better position repair crews for outages; farmers to better anticipate and prepare for dramatic shifts in weather and more.
GRAF uses advanced IBM POWER9-based supercomputers, crowdsourced data from millions of sensors worldwide, and in-flight data to create more localised, more accurate views of weather globally.
"Accurate and timely communication of weather forecasts combined with AI, analytics, IoT etc. can have a domino effect in helping consumers and businesses in India make faster, smarter decisions. With IBM's powerful new global weather forecasting system we have a highly advanced and differentiated solution that will address longstanding issues of data gaps, specificity and confidence in weather prediction for businesses and agriculture ecosystem." Himanshu Goyal, India Business Leader, The Weather Company.
The new system will be the first to draw on untapped data such as sensor readings from aircraft, overcoming the lack of specialised weather equipment. It will also give people the opportunity to contribute to improving weather forecasts globally, as it will be able to make use of pressure sensor readings sent from barometers found within smartphones if people opt-in. "Additionally, hundreds of thousands of weather stations, many run by amateur weather enthusiasts, can also contribute data to the model," added the company.
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