For those who love weather, the wild winter has a silver lining.
Weary of this year’s extreme winter? I’d say we all are, but then I’d be missing one group — meteorologists, who find it utterly fascinating.
“This is kind of our Super Bowl — it’s almost intoxicating,” said Paul Douglas, chief meteorologist for the Star Tribune and founder of Media Logic Group.
Douglas doesn’t dismiss the long hours spent scrutinizing oceans of data, trying to get the forecast right and warn the public accordingly. “We do feel the pressure,” he said, then added: “This kind of weather makes us feel wanted and needed.”
Meteorologists across the country have been working long hours, poring over data collected by satellite and processed by computers. Their colleagues in the field have scrutinized the tiniest ice structures for clues about future storms. All of them have burned the midnight oil, then fallen into bed — exhausted, and in some cases freezing — only to wake up and start the whole thing over again the next day.
A few days ago in New York, Brian Colle woke up at 1 a.m. and headed out into the snow. Using plates of glass he’d been storing in a freezer in his garage, he collected snowflakes to analyze with a powerful microscope.
Back-to-back storms have made for a lot of night shifts this year, said Colle, a professor of marine and atmospheric science at Stony Brook University. But he’s not complaining. “We’re always looking for good data sets,” he said, “so we’ve been lucky.”
The trend over the past dozen or so years has been toward milder winters, Douglas noted. “But this is turning into an old-fashioned winter, the kind your parents complained about,” he said. “The most fascinating to me is when old-timers start to complain — older Minnesotans who’ve seen it all, who were here in the ’30s and the ’70s.”
This year’s weather patterns have left even meteorologists shaking their heads. “I’m experiencing more of these ‘Gee, we’ve never seen that’ moments,” Douglas said. “The weather appears to be getting stuck. There was a natural rhythm. Now it seems all messed up.”
He spends hours poring over warnings, models, charts and tweets — “trying to find the wisdom in the firehose of data,” he said. “I’m fascinated with what’s going on. By the end of the day, I have a headache and eyestrain from looking at multiple computers.”
That’s why Douglas finally forced himself to move his iPhone out of his bedroom in his Excelsior home. “I was getting so many alerts and advisories, it was messing with my sleep,” he said.
The science of forecasting the weather has grown much more accurate and much more complex in recent years. It begins with huge troves of data, fed through a variety of sophisticated analytic models.
Adam Sobel, a professor of Earth and environmental sciences at Columbia University, points out that this “big, automated, computationally intensive, nonhuman process that produces the raw material of the forecast” still requires human beings to evaluate the results and turn them “into an actual prediction that can be communicated to people.”
Extreme weather, like hurricanes and blizzards, increases the workload and — as the scientists say they know only too well — the stakes for the decisionmakers in the world beyond.
Dougles tries to err on the side of caution. “I’d rather be accused of hyping a storm than accused of not being emphatic enough,” he said.
David Novak, chief of the development and training branch at the National Weather Service’s Weather Prediction Center, says that in addition to pushing the predictions further into the future, meteorologists hope to make better guesses about how many inches of snow a storm will drop.
That is the challenge that brought Colle into the snow. Despite the sophistication of many analytic tools, he said, the formula to predict snow accumulation is surprisingly crude: One inch of rain is taken to equal 10 inches of snow.
But a recent storm showed how unreliable that measure was: During the first four or five hours, he said, a steady snowfall produced just an inch or so of accumulation. Then 3 or 4 inches piled up in the next hour alone. The reason may have to do with the structure of the snowflakes, and current models have no ability to predict that. The samples he gathered outside his garage may help.