To better understand how these twisters form, researchers have been meshing data from a number of factors that can have an impact on tornado formation. More specifically, researchers are trying to pinpoint how wind direction and height for instance can cause the updraft of storm winds to begin to spin, which is the first warning that a tornado could form.
At the heart of this research is Amy McGovern from the University of Oklahoma. McGovern has been creating models with supercomputers that are crunching vast amounts of data to understand how a number of potential storm variables interact with one another to form twisters.
At the beginning of the research endeavor, McGovern and her team used observational data from a two-decade old storm as the basis for a few hundred storm simulations. The problem was, according to the article, that these simply did not generate enough data. The team realized they needed a supercomputer and harnessed Kraken, a Teragrid machine, to revolutionize research. Under this paradigm, the team generates almost 50 terabytes for 50 simulations then turns this data to another supercomputer, Nautilus at the University of Tennessee, to sift through the data to find patterns and meaning.
As McGovern said in an interview, ”In the longer term, we would like to bring our findings and methods to the weather forecasters who actually issue the tornado warnings. We would like to develop an interface that provides them with immediate and useful information, which they can use to improve their tornado warnings.”