Hurricanes are America’s most destructive natural hazards, causing more deaths and property damage than any other type of disaster. Since 1980, these powerful tropical storms have done more than US$1.5 trillion in damage and killed more than 7,000 people.
Hurricanes are America’s most destructive natural hazards, causing more deaths and property damage than any other type of disaster. Since 1980, these powerful tropical storms have done more than US$1.5 trillion in damage and killed more than 7,000 people.
The No. 1 cause of the damages and deaths from hurricanes is storm surge.
Storm surge is the rise in the ocean’s water level, caused by a combination of powerful winds pushing water toward the coastline and reduced air pressure within the hurricane compared to the pressure outside of it. In addition to these factors, waves breaking close to the coast causes sea level to increase near the coastline, a phenomenon we call wave setup, which can be an important component of storm surge.
Accurate storm surge predictions are critical for giving coastal residents time to evacuate and giving emergency responders time to prepare. But storm surge forecasts at high resolution can be slow.
As a coastal engineer, I study how storm surge and waves interact with natural and human-made features on the ocean floor and coast and ways to mitigate their impact. I have used physics-based models for coastal flooding and have recently been exploring ways that artificial intelligence can improve the speed of storm surge forecasting.
Today, operational storm surge forecasts rely on hydrodynamic models, which are based on the physics of water flow.
These models use current environmental conditions—such as how fast the storm is moving toward shore, its wind speed and direction, the timing of the tide, and the shape of the seafloor and the landscape—to compute the projected surge height and determine which locations are most at risk.
