A Weather Tracking Black Hole Is Helping Uncover the Mysteries of Tornadoes

"The reality is we probably truly underestimate the number of tornadoes."

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Sep 14 2015, 1:00pm

Image: Flickr/Mike McCune

Tornados are incredibly destructive weather events, so you'd think that we have a pretty good handle on tracking them across this massive, sparsely populated country of ours. In reality, we have no idea how many potentially tornadoes strike Canada in a given year, particularly in the north.

Humans still make up our most reliable tornado sensor network, and in the north, that network is especially weak because of how few people live there, compared to the more urban and densely populated south. Even if Canada's radar system—which is localized to the south—catches some intense weather activity, the only way to be sure a tornado is really occurring is via on-the-ground reports.

"There are huge gaps in the areas or territories of Canada where you don't find anybody. The reality is we probably truly underestimate the number of tornadoes," David Phillips, a senior climatologist for Environment Canada, told me over the phone. "Who knows what's going on in northern Ontario?"

Environment Canada's radar network. Screengrab: Environment Canada

According to Phillips, the number of tornadoes that occur annually in Canada could be much higher than 200, a far cry from the 60 to 80 figure that's often repeated, although it is impossible to say for certain. Researchers such as Vincent Cheng at the University of Toronto are trying to identify which climatological factors are most likely to cause a tornado and build computer models that can predict tornado frequency in a given area, seasons in advance.

The goal, Cheng told me, is to give developers in the north an idea of the harsh conditions their buildings will eventually face. "When anyone develops a new subdivision of building, they take into account this type of severe wind," Cheng told me in a phone interview. "Is it a one in 1,000 years return period, or one in 100? They want to know what the tornado occurrences and risks are in any particular area."

In a paper published last week in Nature Communications, Cheng and his colleagues described a computer model they built using tornado sighting data from the past 30 years. After establishing which climate conditions were most tightly correlated with tornado occurrences, the model extrapolated this information to sparsely populated areas in order to infer how many tornadoes are likely to have occurred there in the same period.

The model's predictions. A) through I) are the months of the year, beginning with December. Screengrab: Cheng, et al.

For example, Cheng and his colleagues found that their model predicted tornado frequencies that were much higher than what has actually been recorded in the northern prairies. With enough data, Cheng said, this same model could predict tornado frequency in the future.

"Right now, we understand the dynamics and the conditions under which some of the strongest tornadoes occur, but we usually in some respect only know that after the fact," Gregory Carbin, a meteorologist at the US National Oceanic and Atmospheric Administration's storm prediction centre, told me over the phone.

The US has a denser radar network than Canada, and a more evenly distributed population—and hence a better detection system—but it's still difficult to predict when tornadoes will strike. The storm prediction center at NOAA is dedicated to investigating the variables that determine how a tornado forms, but blind spots in sparsely populated areas such as mountainous regions pose a problem for research. The situation in Canada, Carbin said, is much worse.

In terms of investigating and predicting tornadoes, Phillips said, people—even people assisted by drones—are likely to be our main source of data for years to come. This means that the entire northern half of Canada will remain a blind spot for meteorologists for years to come as well, although researchers like Cheng, with the help of some advanced computer models, are slowly pulling back the veil of mystery.