New weather system promises 'vastly improved' global forecasting

January 10, 2019 // By Rich Pell
IBM (Armonk, NY) and its subsidiary The Weather Company (Atlanta, GA) have unveiled a new global weather forecasting system that they say will provide the most accurate local weather forecasts ever seen worldwide.

The new IBM Global High-Resolution Atmospheric Forecasting System (GRAF), say the companies, will be the first hourly-updating commercial weather system that is able to predict something as small as thunderstorms globally. Compared to existing models, it will provide a nearly 200% improvement in forecasting resolution (from 12 to 3 sq km) for much of the globe.

GRAF uses IBM POWER9-based supercomputers, crowd-sourced data from millions of sensors worldwide, and in-flight data to create more localized, more accurate views of weather globally.

"Today, weather forecasts around the world are not created equal, so we are changing that," says Cameron Clayton, general manager of Watson Media and Weather for IBM. "Weather influences what people do day-to-day and is arguably the most important external swing factor in business performance. As extreme weather becomes more common, our new weather system will ensure every person and organization around the world has access to more accurate, more finely-tuned weather forecasts."

Currently, much of the world relies on forecasts for predictions that cover 12- to 15-kilometer swaths of land - too wide to capture many weather phenomena. In addition, leading weather models traditionally update only every 6 to 12 hours. In contrast, GRAF will provide 3-kilometer resolution that updates hourly.

The new system, say the companies, will be the first to draw on untapped data, such as sensor readings from aircraft, overcoming the lack of specialized weather equipment in many parts of the world. It will also give smartphone users the opportunity to contribute to helping improve 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 to sharing that information.

In addition, hundreds of thousands of weather stations - many run by amateur weather enthusiasts - can also contribute data to the model. While the resulting volume of data would be too much for most supercomputers, says IBM, this new model analyzes


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