A close collaboration between NCSA visualization experts and atmospheric researchers sheds new light on the formation of the most powerful, dangerous tornadoes

by Trish Barker

In a typical year, 1,200 tornadoes cause 70 fatalities and 1,500 injuries nationwide. Most of the damage, deaths, and injury are due to a very small percentage of these tornadoes, the so-called “supertwisters” whose winds of more than 200 miles per hour put them at the extreme end of the Fujita Scale of Tornado Intensity (the so-called F4 and F5 tornadoes). On average, there are 12 or 13 of these tornadoes in the United States each year.

Ideally, forecasters would be able to provide enough warning that people could protect themselves from these killer storms. While they have successfully identified atmospheric conditions that are favorable for supercell formation, accurately predicting which storms will produce tornadoes and at what time is a feat that continues to challenge forecasters. Researchers from the University of Illinois at Urbana-Champaign collaborated with visualization experts at NCSA in an effort to shed light on how the most violent tornadoes form and to create animations that reveal the inner behavior of tornado producing storms.

Their work was showcased this March in an episode of the PBS TV series NOVA called "Hunt for the Supertwister."

A storm is born

Scientists know that the strongest tornadoes are generated by a particular type of rotating thunderstorm called a supercell. The swirling winds of a supercell can produce tornadoes. But not all supercells lead to tornadoes, and not all tornadoes become supertwisters. In fact, only about 20 percent to 25 percent of supercells produce tornadoes. Why some storms spawn tornadoes while others don't -- and why some tornadoes become extraordinarily strong supertwisters -- is not yet well understood.

Supercells form in an unstable and adequately deep atmospheric layer that has sufficient moisture and significant change in the horizontal wind speed. An environment that favors the formation of tornadoes also requires high relative surface humidity, considerable low-level horizontal wind, and steep low-level lapse rates (meaning the temperature drops rapidly at greater atmospheric heights).

In an effort to pinpoint what triggers tornadoes, researchers -- including NCSA research scientist Robert Wilhelmson -- create computer simulations of evolving storms. Just as physicians use X-rays and CAT scans to diagnose disease, these storm researchers use simulations and visualization to analyze tornado formation.

"The big problem in storm science is that with the instrumentation we have we can't sense all the things that we need to know," explains Lou Wicker, a scientist at the National Severe Storms Laboratory who frequently collaborates with Wilhelmson. "From the field, we can't figure out completely what's going on, but we think the computer model is a reasonable approximation of what's going on, and with the model we can capture the entire story."

Wicker developed a model called NCOMMAS (NSSL Collaborative Model for Multiscale Atmospheric Simulation) to computationally simulate thunderstorms and their associated tornadoes. NCOMMAS is based upon an earlier model developed by Wilhelmson.

The simulation begins with data describing the pre-tornado weather conditions -- wind speed, atmospheric pressure, humidity, etc. -- at discrete points separated by distances ranging from 20 meters to three kilometers. Starting with these initial variables, partial differential equations that describe changes in the atmospheric flow are solved. The numerical solution of these equations proceeds in small time intervals for two to three storm hours as the supercell forms and produces a tornado. A virtual storm is born.

Go to Page 2


Access Online | Posted 11-8-2004








Converting static data to a high-resolution dynamic visualization can help researchers zero in on fresh insights. In this visualization, orange spheres are rising; blue spheres are falling. Similarly colored streamtubes represent a 100-second history of selected weightless tracer particles. Swaying cones are used to symbolize the speed and direction of the wind at ground level. Click here to view a movie of this visualization.