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Tu-Uyen Tran, Published February 16 2014

Weather science's swift advance

GRAND FORKS – A few taps on a keyboard or the click of a mouse is all it takes.

Because of technological advancements, Grand Forks meteorologist Mark Ewens has access to a world of weather data collected by thousands of sensors around the country and even the world.

“All of this information is new,” he said, gesturing to the four computer screens in front of him. “All of the stuff we’re seeing on the satellite is new from 40 years ago, just the sheer amount of weather data.”

Though there are the occasional woefully wrong forecasts, which Ewens admits readily, the science of weather has advanced by leaps and bounds in the past several decades thanks to the abundance of data and computing power.

Even in the space of a decade, the weather service has reported major improvements. Between 2001 and 2011, the lead time for winter storm warnings increased, on average, from 13 hours to 20 hours.

In that same time, tornado warning lead times increased from 10 minutes to 15 minutes. Ewens said before Doppler radars were introduced in the 1990s, meteorologists had a hard time even detecting tornadoes.

Day-to-day forecasts such as rain and snow have improved, too, with a threat score increasing from 26 percent to 34 percent. The score measures how close the weather service came to a perfect forecast, where it gets the amount of precipitation and location exactly right for the next day.

Quite a change

To appreciate how much weather science has changed, consider what it was like in 1974 when Ewens began his career as a weather forecaster in the Air Force.

There were really no automated weather sensors then. Meteorologists had to gather the information from the instruments themselves, checking thermometers and rain gauges. They’d go outside every hour to look at the sky, identify the clouds and estimate cloud height.

In North Dakota, there were eight observation stations, Ewens said. Today, there are 30 such stations in the state and almost 1,000 more around the nation.

To gather data higher in the atmosphere, the meteorologists of 1974 relied on balloons released twice a day and satellites, as meteorologists do now. But there wasn’t as much data then.

Twice a day, an extra-large fax machine would print out the latest satellite images, and Ewens and his colleagues would use pens to plot their data on top of it.

Today, computers gather images from many weather satellites, stitch them into time-lapse videos, layer the images with data and send them over the Internet – the images and videos are even available to the general public.

Data from the upper atmosphere are also available from sensors mounted on commercial aircraft, providing information around the clock.

Weather forecasters in 1974 were assisted by computers as they are today, but the small amount of data available and the relatively low computing power meant forecasts were not as fine-grained as now, according to Ewens and Mark Frazier, the meteorologist in charge at the Grand Forks weather service office.

Today, the weather service’s supercomputers can create models that simulate many layers of atmosphere within grid-squares of 2.5 square miles.

“The accuracy we have today, for example, at Day 7 is closer to what we used to have 25 years ago for Days 1 to 3,” said Frazier.

Besides its own simulations, the weather service gets simulations from other weather agencies, such as Canada’s and Japan’s.

And all of this is available free to the public and private forecasters, ranging from the local TV weatherman to the Weather Channel.

Skill still important

But while the availability of data and supercomputing power have increased dramatically, the skill of the meteorologist still matters.

“The computers are really good, but they’re not perfect,” Ewens said.

Grid-squares they look at are still not small enough and, hidden within the squares, may be small storms that the computers would dismiss as noise from bad instruments, he said. During severe weather, he said, a meteorologist is always keeping an eye on things to catch what the computers miss.

The simulations don’t always account for local factors either, Ewens and Frazier said.

For example, the Red River Valley might not seem like much of a valley, but it is deep enough to act as a funnel, so when the wind roars down from the north at the right angle, that funnel causes an increase in wind speed, Ewens said.

As sophisticated as supercomputers are today, weather data collection is expected to get even better. But meteorologists will probably remain humble even then, because they know they’ll never get it 100 percent right.