AUSTIN, Texas The University of Texas at Austin Institute for Computational Engineering and Sciences (ICES) has received a $3 million National Science Foundation (NSF) grant to further advance the storm surge predictive simulations that have helped Texas emergency managers develop some of the country’s most successful hurricane evacuation plans.
Speed is essential for disaster planning, and the new simulations will be designed to take advantage of advances in supercomputing to convert large databases of weather and topographical data into storm surge predictions within an hour, half the current time for processing the continually changing data.
Clint Dawson, director of the ICES Computational Hydraulics Group, has been predicting hurricane storm surge for the past 15 years. Using computational methods that detail the location and depth of surges, Dawson and collaborators have helped Texas emergency managers develop hurricane evacuation plans and studied storm surges for every hurricane to strike the United States since the late 1990s.
The current storm surge prediction process relies on feeding hurricane data into a computational program called ADCIRC, which uses high-performance computers to generate data about potential outcomes.
With the $3 million NSF grant, Dawson, a professor of aerospace engineering and engineering mechanics, and collaborators at Louisiana State University, The University of Notre Dame, and The University of North Carolina at Chapel Hill are overhauling ADCIRC into a version 2.0 dubbed STORM that’s designed to perform more efficiently across a variety of computer hardware architectures. A goal for STORM is to work twice as fast as ADCIRC, enabling storm surge predictions to be made within an hour of receiving data inputs.
“The idea is how do we keep the program up to date and modernize it for the next generation,” Dawson said.
Since first being developed in the mid-1990s, ADCIRC has been widely used by the National Oceanic and Atmospheric Administration, U.S. Army Corp of Engineers and academic researchers to simulate and predict water flow in coastal areas of the United States. Storm surge prediction is a popular use for the program, but the governing equations describing fluid flow can be applied to investigate other research questions. During the Deep Water Horizon oil spill, for example, Dawson used ADCIRC to predict oil dispersal paths up to three days in advance.
The four-year grant pairs Dawson and ICES Research Associate Craig Michoski as co-principal investigators. They will work with research collaborators from three other universities: Hartmut Kaiser, LSU; Joannes Westerink, ND; and Richard A. Luettich, UNC-Chapel Hill.
Whatever the fluid flow problem being analyzed, the ADCIRC system works by analyzing the interaction between relatively static elements, such as coastal and undersea topography, and dynamic ones, such as how a hurricane influences water height and water velocity. ADCIRC’s computational algorithms produce a selection of potential scenarios. The most likely prediction is used by emergency response teams. In the case of storm surges, this information informs emergency response and evacuation plans and helps create maps.
The STORM program will maintain the same ADCIRC functionalities but will get a code upgrade with a completely new foundation for its algorithms, Dawson said.
The new will be written in HPX and designed to be flexible and easily integratable with other code types, and adaptable to diverse computer architectures. By rewriting the code using HPX, STORM will not only be able to run more efficiently on today’s super computing systems, but is likely well equipped to handle inevitable changes that will come.
“Where we hope to be in four years is to have a whole new code and a whole new piece of software. And it’s going to be a lot of work but it’s also necessary work if you want to keep your software useful for the next generation,” Dawson said.
At the same time, Dawson says turning ADCIRC into STORM will be an exercise in understanding the history and composition of the original code, which could help in constructing STORM, and other programs in general.
“If you don’t do these kinds of projects you lose all this memory of how you got to this point. We’re really fortunate to have this opportunity to take all the lessons that we learned and to put it into a new piece of software,” Dawson said.
