IBM GRAF Builds on The Weather Companys AI and Cloud Capabilities – Forbes

When it recently launched a new weather model called IBM GRAF, The Weather Company took a big supercomputing step forward.

IBM GRAF, with its ability to process weather data from a variety of sources worldwide, enables The Weather Company, an IBM Business, to deliver high-resolution, hourly-updated forecasts around the globeparticularly to regions that have never had them before.

But the full power of IBM GRAF to generate local forecasts for the entire world depends on technology that The Weather Company already had in place and is continually refining: artificial intelligence (AI) and cloud computing.

When a series of winter storms recently lashed much of the United States, millions of people used The Weather Channel mobile app and weather.com website to help plan their travel.

Sophisticated AI algorithms from The Weather Company turn troves of current and historic weather data into recommendations, for example, that can tell an electric utility company where to trim trees to prevent blackouts before the next storm hits. Or that can compute a two-week flu-risk forecast for a given locale.

And it is the mix of IBM Cloud and hybrid cloud networks that can deliver The Weather Companys forecasts anywhere in the worldto business customers computer systems and for free to millions of users via smartphones and web apps.

You have to know whats happening everywhere in the atmosphere, right now, said Cameron Clayton, general manager of IBM Watson Media and Weather. Supercomputing and AI have had a profound impact on our ability to map the atmosphere and predict the future. The cloud helps us share those forecasts any time, anywhere.

IBM GRAFshorthand for Global High-Resolution Atmospheric Forecasting systemruns on a purpose-built IBM POWER9 supercomputer known as Dyeus. It maps conditions at billions of points in the atmosphere to produce hyperlocal pictures of what the weather will look like up to 12 hours in advance. It also produces a fresh set of predictions every hour, rather than every 6 or 12, as with many weather models in other parts of the world.

But thats just the beginning. Those predictions feed into the multi-model forecasting engine that The Weather Company, part of IBM, has been refining for more than two decades. Using complex machine learning algorithms, that engine combines the IBM GRAF results with those of about 100 other weather forecasts from around the world, including the American modelthe Global Forecast System used by the National Weather Serviceand the European model, ECMWF.

All these other models have different opinions about what the forecast is, said Peter Neilley, an IBM distinguished engineer and director of weather forecasting sciences and technologies for The Weather Company. The AI or machine learning is the thing that binds them all together and figures out the right way to combine them to produce an optimized forecast.

To do that, the engine compares factors like temperature or precipitation from each model based on geography, time, weather type and recent forecast accuracy and assigns them relative weights and correction factors. The system then blends those weighted contributions to arrive at the final forecast. The calculations involve some 400 terabytes of data collected daily to provide forecasts for two billion locations around the world, according to Mr. Clayton, and can result in 25 billion forecasts every day.

Those end up, in one form or another, with consumers, whether delivered by a broadcaster as part of the local morning weather report; on an IBM website such as weather.com or wunderground.com or its familiar The Weather Channel app; or, for business customers, through a product tailored for specific markets and uses. But increasingly, in an approach Mr. Clayton calls cognitive computing, the company is using artificial intelligence and machine learning to combine meteorological observations with a variety of other types of data, and go beyond predicting the weather to enable specific responses.

This is often accomplished through IBMs Watsona suite of AI tools and apps named for the companys founder that famously beat two returning champions on Jeopardy! in 2011and in the IBM Cloud. The idea is to deliver specific insights to help people make better decisions, from whether to take along the umbrella for the day to whether to evacuate in advance of a storm.

For example, the company is working with Oncor, based in Texas and among the nations largest utilities, to help predict where vegetative growth is most likely to interfere with power lines which can cause blackouts and wildfiresallowing managers to better plan for preventative maintenance.

The Weather Company uses AI to analyze weather phenomena, location, season and time of day and other actors to provide 15-day local flu forecasts.

At Knight Transportation, a leading trucking company, a Watson-enabled service allows drivers to receive real-time audio alerts through their in-cab communication systems about how weather conditions will affect their planned routes. That means truckers, whose safety, delivery deadlines and cargo are regularly threatened by the effects of bad weather, can better avoid roads made dangerous by ice, fog or high winds, or seek shelter before hitting a storm.

The Weather Company is applying AI-powered predictive platforms to other industries as well, including agribusiness, insurance, aviation, retail and energy trading.

The Weather Company's flu tracker can help people take precautions during a local outbreak of illnesses.

On the consumer side, The Weather Company websites and apps can provide personalized information beyond, say, a prediction of a 75 percent chance of rain at 2 p.m. in a particular zip code. The Weather Channel app, for instance, is able to glean users interests from the alerts and services they opt into and determine what information they most want to see each day, like the best hours to go for a run or whether an allergy sufferer will have to contend with a high pollen count.

There is also a new tracker that analyses weather phenomena, location, season and time of day along with other factors to determine the likelihood that people are at risk for getting the flu. It then provides a 15-day flu forecast on the theory that people can take precautions like avoiding events or washing their hands more frequently during an outbreak.

It becomes a platform that you could use for pretty much any data type, any type of a health-type situationallergies, flu, arthritis flare-ups, said Chris Hill, chief information and technology officer for IBM Watson Media and Weather. Theres a lot of interesting dynamics of health and weather and weve built a generic engine that enables us to gain insights from different types of weather using data science.

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IBM GRAF Builds on The Weather Companys AI and Cloud Capabilities - Forbes