Hurricanes are among the most devastating natural disasters, with a profound impact on both lives and economies. As climate change continues to intensify these storms, accurate forecasting becomes ever more crucial. A recent University of Houston study utilized an ACCESS allocation on Bridges-2 at the Pittsburgh Supercomputing Center to reveal significant improvements in predicting hurricane intensity and associated rainfall, potentially revolutionizing how we prepare for and respond to these powerful events.
Md Murad Hossain Khondaker and Mostafa Momen recently published their study titled Improving hurricane intensity and streamflow forecasts in coupled hydro-meteorological simulations by analyzing precipitation and boundary layer schemes in the American Meteorological Society’s Journal of Hydrometeorology about hurricanes and how the use of supercomputers can help accurately predict potential hurricane-induced damage.
At the core of this research is a novel approach to understanding how hurricanes function.
“Hurricanes operate like massive heat engines that move over the ocean and, the air friction can highly impact hurricanes’ movement, speed, and intensity” explained Momen, an assistant professor in the Department of Civil and Environmental Engineering at the University of Houston. “This friction, similar to the resistance an airplane experiences, slows down the hurricane, and our study showed how current weather models significantly overestimate this friction, leading to an underestimation of hurricane intensities.”
By reducing the assumed friction, or diffusion, in Bridges-2 generated models, the researchers made a startling discovery: They could significantly improve the accuracy of hurricane intensity forecasts. This improvement also extended to predicting hurricane-induced rainfall, a critical factor in anticipating flood risks in vulnerable areas.
“By conducting hydrological simulations, we showed that this new adjustment also improves flood forecasts in hurricane-prone regions,” Momen said. “The implications of these findings are far-reaching as recent hurricanes like Katrina, Harvey and Maria caused over $400 billion in total adjusted costs according to the NOAA (National Oceanic and Atmospheric Administration) estimates.”
Momen said that improved predictions could potentially save lives and reduce property losses.
“Enhanced hurricane predictions can potentially save millions of dollars and many lives by providing more precise forecasts of hurricane floods,” Momen said. “Our research findings using ACCESS allocations on Bridges-2 not only hold promise for better evacuation planning but also have the potential to inform emergency services with the forecasts needed to respond more effectively.”
The scale and complexity of this research required significant computational resources. The ACCESS PSC Bridges-2 system was instrumental in this project – providing over 300,000 CPU-core hours and the high-memory nodes necessary to process the vast datasets involved.
“Simulating 17 days of Hurricane Irma with eight-kilometer horizontal resolution took about 22 hours using 128 processors,” Momen said.
This research was driven by the urgent need to improve hurricane forecasts, particularly in light of the increasing frequency and intensity of these storms. The team was inspired by the shortcomings in current prediction models and the devastating impacts of recent hurricanes.
One of the most exciting aspects of this study was the dramatic improvement in forecast accuracy achieved by adjusting the turbulence parameters in the models.
“We were able to enhance hurricane intensity forecasts by up to 40% compared to default weather models,” Momen said. “Another surprising finding was that more intense hurricanes do not necessarily lead to more total rainfall but rather more localized and severe precipitation – this insight is particularly relevant for urban areas, where concentrated rainfall can lead to catastrophic flooding, as seen during Hurricane Harvey in Houston.”
Looking ahead, the research team plans to expand their focus to potentially include storm surge predictions at coastal locations and further refine their models by incorporating more sophisticated physics-based modifications. These efforts aim to enhance our ability to predict and prepare for hurricanes, ultimately reducing the risks for coastal communities.
In a world where the threat of hurricanes is growing, this research offers a beacon of hope. By improving our understanding and prediction of these powerful storms, we can better protect our communities and mitigate the catastrophic impacts they bring.
Momen and his team acknowledge financial and/or computational support from the University of Houston, the Physical and Dynamic Meteorology Program of the National Science Foundation, the National Center for Atmospheric Research and the Advanced Cyberinfrastructure Coordination Ecosystem: Services & Support program.
Resource Provider Institution(s): Pittsburgh Supercomputing Center (PSC)
Affiliations: University of Houston
Funding Agency: NSF
Grant or Allocation Number(s): EES230054
The science story featured here was enabled by the U.S. National Science Foundation’s ACCESS program, which is supported by National Science Foundation grants #2138259, #2138286, #2138307, #2137603, and #2138296.