Hyperlocal Predictions are the Future of Weather Forecasting

As good as weather forecasts have become, that can happen in a world where weather forecasters make their calls for areas as wide as 20 miles across, Raytheon said in a press release.

The future may be different. The possibility of so-called hyperlocal forecasts, detailed down to areas as narrow as your neighborhood corner, or even your front door, will be one of the many future weather topics discussed at the meeting of the American Meteorological Society in Boston, Massachusetts, Jan. 12-16, 2020.

“People don’t go on a run through their town; they run through their neighborhood,” said Matt Taylor, a Raytheon meteorologist. “A weather forecast is kind of like a handshake, so if your app tells you it’s snowing outside, but it’s not, then you lack trust in it and you don’t feel inclined to use it and you don’t believe it.”

The AMS is celebrating its 100th anniversary with the theme, “The AMS Past, Present and Future: Linking Information to Knowledge to Society.” Raytheon will be there to demonstrate some of its current and future weather technologies, some of which may help realize hyperlocal forecasting. The company is investing in research on how to use machine learning, analytics and artificial intelligence to improve the accuracy of weather forecasting, the company said.

One Raytheon project is trying to use machine learning to shorten the time it takes to predict tornadoes. Using massive amounts of data, including radar data, geography and other factors, researchers believe they could help meteorologists warn the public of tornado formations much more quickly.

“An extra five minutes gives people more time to take shelter and protect their property,” said Charlie French, a Raytheon weather programs senior manager.

Raytheon is working with a company to investigate crowdsourcing data from smartphones, cell towers, cars, buildings and Internet-of-Things devices to create a very accurate, hyperlocal forecast.

According to the report, a small radar called Skyler could help bring about hyperlocal forecasting. Instead of one, massive radar installation, it consists of smaller, one-meter square Active Electronically Scanned Array, or AESA, software-defined radar units.

It gives “you highly localized information like ground fog or flash-flooding in remote or urban locations; things that today’s radars can’t do,” said Michael Dubois, Raytheon’s Skyler lead.

Another IRAD program Raytheon is investigating correlates weather warnings by the National Weather Service and broadcasters and the resulting public actions. It’s using data from social media posts and traffic cameras in the affected areas to see if and when people evacuate, take shelter or even ignore the warnings.

Raytheon already provides advanced forecasting technologies, including the Advanced Weather Interactive Processing System, or AWIPS. It helps NOAA’s National Weather Service issue forecasts, watches and warnings hours or even days before storms cross the horizon, the statement added.

Forecasters at more than 100 NWS offices and centers nationwide use AWIPS hardware and software to monitor, organize, visualize and distribute weather data from thousands of sensors and sources, view high-detail charts, graphs and maps and issue weather forecasts, watches and warnings.

“Meteorologists have a myriad of data sources to consider when making forecasts,” said Shawn Miller, Raytheon civil space and weather technical director. “Wind speed, air pressure and temperature are familiar to most people, but detailed radar data, infrared satellite images and hydrological river data can be as important.”

 

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out /  Change )

Google photo

You are commenting using your Google account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s