Eyeing The Damage and Reasons Of Hurricane Season
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Eyeing The Damage Of Hurricane SeasonTropical cyclones, known as hurricanes and typhoons in other parts of the world, have caused huge damage in many places recently. The United States has just been hit by Hurricane Milton, within two weeks of Hurricane Helene. Climate change likely made their impacts worse.
[...] The bureau's forecast is consistent with scientific evidence suggesting climate change is likely to result in fewer but more severe tropical cyclones. They are now more likely to bring stronger winds and more intense rain and flooding.
Our knowledge of tropical cyclones and climate change is based on multiple lines of evidence globally and for the Australian region. This work includes our studies based on observations and modeling.
[...] Many ocean heat records have been set recently. This means we have been in "uncharted waters" from a temperature perspective. It adds further uncertainty if relying on what occurred in the past when making predictions for the current climate.
The science makes it clear we need to plan for tropical cyclone impacts in a different way from what might have worked in the past. This includes being prepared for potentially fewer tropical cyclones overall, but with those that do occur being more likely to cause more damage. This means there are higher risks of damaging winds, flooding and coastal erosion.
Arthur T Knackerbracket has processed the following story:
In the aftermath of hurricanes like Helene and Milton, the damaging effects of these natural disasters are the center of national conversations, including questions about the long-term impact to infrastructure. However, current methods for damage assessment don't offer clear and timely answers to these questions.
That's where AI and engineering can help. Researchers from Texas A&M University are pioneering the use of AI and machine learning to create faster methods to assess damages caused by hurricanes.
[...] Using this dataset, Manzini and fellow graduate student Priya Perali trained an AI system to recognize building and road damage caused by disasters. Learning these models took hours of high-performance computing but have resulted in a damage assessment system that can sort through the building and road damages of a large neighborhood after a disaster in only four minutes using a laptop.
"AI offers tremendous value for rural counties which do not have the budget or workforce to conduct physical damage assessments but do have inexpensive drones," said Murphy, a Raytheon Professor in the Department of Computer Science and Engineering.
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