Meteorologists have invented a mathematical system for scoring Northeast snowstorms on a five-step scale -- like hurricanes.
The system threatens to end generations of barstool debates over which half-remembered storms really were the worst. Someday, it might even give forecasters a way to telegraph the severity of storms before the snow flies.
The new rankings -- Categories 1 through 5 -- could appear in post-storm assessments as early as this winter, according to Tom Karl, director of the National Climatic Data Center in Asheville, N.C. That's the nation's repository for weather statistics.
"We're ready to go operational once we've had a significant enough storm," he said. There was no immediate word on whether last Friday's storm -- which dumped a few inches here but close to a foot of snow across parts of New England and the Midwest -- will make the cut.
Called the Northeast Snowfall Impact Scale (NESIS), the system is the invention of meteorologists Paul J. Kocin, a winter weather expert at the Weather Channel, and Louis W. Uccellini, director of the National Centers for Environmental Prediction in Camp Springs.
The two scientists wanted something that would be as understandable as the well-known Saffir-Simpson Scale for hurricanes. That rates intensity by a single variable: top sustained wind speeds. For example, Katrina, the most destructive hurricane in modern history, was a terrifying Category 5 storm at sea before it struck the Gulf Coast as a Category 4.
Tornadoes, too, are ranked -- after the fact -- by their highest winds. The colorful Fujita Scale rises from the F-0 Gale Tornado, through Severe, Devastating and Incredible until it reaches the ultimate F-6, the Inconceivable Tornado, with winds above 319 mph.
But big, complex snowstorms can't be fairly measured by their winds alone. Their whiteouts, deep drifts, low temperatures and sprawl have long defied simple comparisons. And how do you weigh their impact as they clog streets, bury runways and disrupt life for tens of millions?
"We struggled with how to go about doing it," Uccellini said. At first, no strategy seemed to work consistently, much less capture a storm's impact on daily life and the economy. For example, a big, windy storm with low barometric pressures and deep snow might miss the biggest urban populations entirely.
Given the variables they had to consider, it took the pair 10 years to develop NESIS. Eventually, Uccellilni said, "We struck upon the idea that if you could map the snowfall on the population density, you could get a measure."
They decided on five storm categories -- Notable, Significant, Major, Crippling and Extreme -- based on the geographic distribution of the snow and the population that's buried beneath it. That was important.
"If there were snows in the mountains, who cared?" Uccellini explained.
The categories are based on a mathematical index that captures the geographical distribution of the snowfall in square miles (with greater mathematical weight applied to greater snow depths), as well as the number of people affected -- all assembled with digital mapping technologies.
"It allowed us to quantify the impact of snowfall on population density," Uccellini said. "After all, that's the essence of what people remember about a big snowfall."
Storms falling within given ranges are assigned to one of the scale's five broad categories. So, just as a hurricane with top sustained winds of 111-130 mph is classified as a Category 3 storm, a Northeast snowstorm with a NESIS index between 4 and 5.99 will be ranked as a Category 3 snowstorm. A Category 5 snowstorm must have a NESIS index of 10 or higher.
To calibrate the scale, the inventors used the formula to analyze the 30 biggest Northeastern snowstorms between 1950 and 2000, using population from 1999 for consistency. Future storms will be ranked using the most recent population data.
Using a larger sample of 70 storms, they found the average was a strong Category 2. Only two storms reached Category 5 -- both monsters with deep snows blanketing large areas with dense populations.
The worst of the worst was the March 12-14 "Superstorm" of 1993, which pummeled residents from Alabama to Maine with record cold and 1 to 4 feet of snow. It killed 250 people, caused $3 billion in property damage and paralyzed the eastern third of the nation, affecting 60 million people. Its NESIS index was 12.52.
The second-worst was the Jan. 6-8 "Blizzard of '96," with a NESIS index of 11.54. Also known as "the Great Furlough Storm," its 21 inches of snow delayed the return of federal workers furloughed during a budget dispute between Congress and the Clinton White House. Up to 3 feet fell in Frederick and Washington counties.