Oklahoma has been ravaged by a massive, mile-wide tornado, with more predicted to come. We talked about the megastorms with atmospheric scientist Karen Kosiba, whose work is showcased in documentary Tornado Alley.


Kosiba is a researcher at the Center for Severe Weather Research in Colorado, where she studies ground-level conditions during tornadoes. She has also spent the past several years working with VORTEX2, a team of scientists who follow these deadly wind storms in trucks fitted out with sensors and radar, gathering reams of data on how tornadoes start, and how you can expect them to behave once they do.

She's been on the TV series Storm Chasers, and in Tornado Alley we see her in the command center of one of the mobile storm chasing labs - a truck that carries its own Doppler radar setup.


io9: You've been following tornadoes for years now. Is there something different or unusual happening this year that's caused so many tornadoes at once?

KK: Not really - these things fluctuate year to year. It's not part of a pattern. You can find other years that this has happened - there's a particularly strong system out of the Pacific, and we're getting good moisture up there. It just kind of happens. These are fast-moving systems so our research team isn't trying to get in front of them and study them. Once they get into southeast, there are lots of trees and rough terrain that blocks our radar observations. But part of what we're trying to learn is how to predict these kinds of storms better.

Is there any way to predict which storms will turn into tornadoes?

We know that supercell storms are big producers of these tornadoes, but we can't predict whether a particular storm will make a tornado.

That's the big objective of VORTEX2 - a lot of it is getting information from the field. We're trying to figure out these details as well as how to relay it to the weather service and the public. Just because we learn stuff doesn't mean it can translate into better weather prediction. People may not have the observational tech required to measure whether a storm will create a tornado. Most places have radar, which measures 30 meters up into the air and higher. But what if it turns out that [for accurate predictions] you need lower level observation, or soundings closer to the storm, or temperature and wind speed? You need other equipment to get those measurements.



We want to know what winds are doing at the ground level, because that's where it affects people the most. We're trying to correlate radar readings with ground level wind speed. So maybe our data, at some point, would allow people to use radar observation to predict what the winds at the ground will be like.

What's the most interesting thing you've discovered about tornadoes since you started observing them?

We have data on almost 200 tornadoes - a lot of them aren't alike. They have very different vortices and structures - you can be surprised by a dataset. You can see a lot of new structures - that's the cool thing.

If you'll allow me to have a scifi moment let's talk about something far future: Tornado prevention. What if you were the storm stoppers instead of the storm chasers? We know hot air and moisure are required to make tornadoes. What would we need to prevent them? Imagine you had futuristic technology - whatever you needed. How would you stop a tornado before it starts?

Well . . . [laughs]. You wouldn't want your thunderstorms to rotate. You might want to switch the wind direction somehow, though you might get in trouble by creating something entirely different. Basically the mesocyclone [the high-level rotating storm that eventually touches down as a tornado] is what you want to stop. So you'd want something airborne that could change the wind directions as the weather pattern comes through. Maybe something that would deflect the wind, prevent the rotation. You wouldn't want to change the rain or anything like that - you need the rain. I'm not sure what this airborne device would look like, but that's what you'd want to do.

This io9 flashback originally appeared in 2011.