Sign In

Communications of the ACM

ACM TechNews


View as: Print Mobile App Share:
A tornado-watcher captures data on a funnel cloud.

A researcher at the University of Oklahoma is generating high-resolution simulations of supercell storms in order to try to identify precursors of tornadoes.

Credit: Tornado Channel

University of Oklahoma researcher Amy McGovern is using computational thinking to identify precursors of tornadoes by generating high-resolution simulations of supercell storms, using the Extreme Science and Engineering Discovery Environment's high-performance computing system.

McGovern wants to generate as many as 100 different supercell simulations during the project. She also plans to use a combination of data mining and visualization techniques as she explores the formation of tornadoes, what causes tornadoes, and why some storms generate tornadoes and other storms do not.

Early research that began with a U.S. National Science Foundation Career Grant resulted in developing data-mining software and initial techniques on lower-resolution simulations.

McGovern, who is working with visualization experts at the Texas Advanced Computing Center, has identified six weather features, including hook echoes, bounded weak echo regions, updrafts, cold pools, helicity with regions of strong vorticity, and vertical pressure perturbation gradients. The results came from the researchers investigating variables by experimenting with different values and various models, and looking for consistent patterns and interesting structures over the life of the simulated storm.

The aim is to compare these simulated storms with real storms.

From Texas Advanced Computing Center
View Full Article


Abstracts Copyright © 2016 Information Inc., Bethesda, Maryland, USA


No entries found