Editor’s note: This is a developing story about severe weather in the Midwest. We will update it as more information becomes available.

This week brings atmospheric devastation to the Midwest: Nearly 200 tornadoes have torn through the region since last Friday, including Jefferson City, the capital of Missouri, on Wednesday night. All told, the disasters have left at least three dead and 25 injured. The damage appears to be extensive, as the flurry of storms cut a line from Texas all the way up through Maryland, with one twister touching down near Washington, DC. Officials are still taking toll.

In an ideal world, meteorologists would be able to predict when and where a tornado is going to form, as they do with rainstorms, to mobilize emergency services and give people warning. But they face a couple problems. For one, scientists know how tornadoes form, but they’re still grappling with the monumentally complex physics at play: A tornado is essentially a swirling funnel of data you can’t get anywhere near. And two, to run models that crunch all that data, you need a hell of a lot of computing power. But in this era of ever more powerful supercomputers, researchers are getting more adept at using what data they have to understand and predict tornadoes.

First, a quick primer on how tornadoes form. They begin with wind shear—that is, winds moving in different directions on top of each other. In the Midwest, this comes from two opposing layers of air: On the bottom is moist air coming off the Gulf of Mexico; on the top is dry wind associated with the jet stream, blowing in from the west.

Matt Simon covers cannabis, robots, and climate science for WIRED.

“Pretend you've got a bunch of invisible Ferris wheels in the air,” says David Gold, chief meteorologist for Global Business Services at IBM, which is rolling out a new forecasting system this year. “If the winds at the top of the Ferris wheel are blowing from the west and the winds at the bottom of the ferris wheel are calm, the Ferris wheel will spin.”

The next ingredient is a thunderstorm. This system takes the spinning Ferris wheels and tilts them on their side. Now you’ve got rotation, which consumes the thunderstorm, transforming it into a tornado.

“Because of the geography and the unique juxtaposition of all those different air masses, they readily come together very frequently during the spring,” says Gold. “That's why the Great Plains is a hot spot for tornadoes.”

To predict when and where a tornado might touch town, scientists have a range of tools at their disposal—they can measure wind speed and pressure through weather stations and watch doppler radar, for instance. Forecasters can then dispatch storm-chasing researchers to gather much-needed data should a tornado materialize. But tornadoes can be fleeting—most last for less than 10 minutes. And they’re relatively small and fast, at least compared to a slow-moving hurricane, which meteorologists can monitor over the long term using satellites. A tornado seemingly comes out of nowhere, making it difficult to alert the public of the threat.

“You're never going to do it perfectly,” says Gold. “There's always going to be measurement errors, we're always going to have gaps. So there's going to be a lot of holes, if you will, in our estimate.”

One massive gap is the fact that a tornado is a highly vertical phenomenon. “Near the surface we have pretty dense observation networks, but above the surface the density goes way down,” says Adam Clark, a research meteorologist with the NOAA National Severe Storms Laboratory. “So we launch these weather balloons, and that measures temperature and dew point and wind as you go up into the troposphere, but those are spaced at really large distances from one another.” We’re talking maybe 100 sites across the entire country.