the world.
Researchers reviewed 94 studies on cyclone risk and found that current methods may not fully capture the dangers that communities face.
The study, titled A Critical Review of Hurricane Risk Assessment Models and Predictive Frameworks, was published in the journal Geoscience Frontiers. It is the first comprehensive review of how cyclone risks are assessed.
Every year, more than 80 cyclones, typhoons, and hurricanes form globally, with Australia experiencing some of the strongest and most destructive storms.
These powerful weather events threaten lives, damage buildings, and disrupt economies.
What’s Missing in Current Risk Assessments?
The research identified six key factors that affect cyclone risk: land use, slope, rainfall, elevation, population density, and soil quality.
Including these factors in risk models could improve predictions and help create better policies to protect communities.
Distinguished Professor Biswajeet Pradhan from the University of Technology Sydney (UTS), who led the study, warns that outdated risk assessments leave communities vulnerable.
“Our review shows that cyclone risk models often focus only on specific threats, like storm surges or flooding, rather than how these dangers combine,” Professor Pradhan said. “This can leave communities unprepared for the full scale of destruction.”
Another issue is that current models focus more on how often cyclones occur rather than the actual damage they cause. However, damage data is more useful for policymakers. The study found that only 5% of cyclone risk studies examined the effectiveness of mitigation measures, revealing a major gap in disaster planning.
The Need for Better Preparation
Mitigation measures—such as stronger building codes, coastal defenses, early warning systems, and land use planning—are essential for reducing cyclone damage. However, current risk models do not always consider how well these measures work.
The study also found that economic losses from cyclones are often underestimated. Many assessments overlook indirect effects, such as business disruptions, which can have long-term financial consequences.
The Role of AI in Risk Assessment
Professor Pradhan’s previous research explored how artificial intelligence (AI) and machine learning can improve cyclone risk assessments. He believes AI could make predictions more accurate and help with disaster planning.
“Some researchers have started using AI models like neural networks, but there is more potential to explore advanced techniques,” he said. “Better models could help cyclone-prone regions like Australia prepare for extreme weather as the climate changes.”
This research highlights the urgent need for better cyclone risk assessments, using modern technology and a broader approach to ensure communities are well-prepared for future storms.
Source: KSR.
