How AI can improve storm surge forecasts to help save lives
storm surge forecasts: Hurricanes cause significant damage due to storm surge, which is influenced by wind and pressure. AI can enhance storm surge predictions, providing faster, more accurate information to aid evacuations and preparedness for coastal communities at risk.
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.An aerial photo of Fort Myers Beach, Fla., in the aftermath of Hurricane Ian in September 2022 shows the damage storm surge can do. Ricardo Arduengo/AFP via Getty Images
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.
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.
Hydrodynamic models have substantially improved in recent decades, and computers have become significantly more powerful, such that rapid low-resolution simulations are possible over very large areas. However, high-resolution simulation that provide neighborhood-level detail can take several hours to run.
Those hours can be critical for communities at risk to evacuate safely and for emergency responders to prepare adequately.The National Hurricane Center’s storm surge forecast for Hurricane Ian two days before it made landfall near Fort Myers, Fla., on Sept. 28, 2022. NOAA
To forecast storm surge across a wide area, modelers break up the target area into many small pieces that together form a computational grid or mesh. Picture pixels in an image. The smaller the grid pieces, or cells, the higher the resolution and the more accurate the forecast. However, creating many small cells across a large area requires greater computing power, so forecasting storm surge takes longer as a result.
Forecasters can use low-resolution computer grids to speed up the process, but that reduces accuracy, leaving communities with more uncertainty about their flood risk.
AI can help speed that up.
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How AI can create better forecasts
There are two main sources of uncertainty in storm surge predictions.
One involves the data fed into the computer model. A hurricane’s storm track and wind field, which determine where it will make landfall and how intense the surge will be, are still hard to forecast accurately more than a few days in advance. Changes to the coast and sea floor, such as from channel dredging or loss of salt marshes, mangroves or sand dunes, can affect the resistance that storm surge will face.
The second uncertainty involves the resolution of the computational grid, over which the mathematical equations of the surge and wave motion are solved. The resolution determines how well the model sees changes in landscape elevation and land cover and accounts for them, and at how much granularity the physics of hurricane surge and waves is solved.Detailed storm surge models can provide more specific information about expected flood height. These two modeled examples show the difference in expected flooding from a fast-moving storm, above, and a slow-moving storm, below. NOAASlower-moving storms tend to have higher and broader storm surge inland, including into bays and estuaries. NOAA
AI models can produce detailed predictions faster. For example, engineers and scientists have developed AI models based on deep neural networks that can predict water levels along the coastline quickly and accurately by using data about the wind field. In some cases, these models have been more accurate than traditional hydrodynamic models.
AI can also develop forecasts for areas with little historic data, or be used to understand extreme conditions that may not have occurred there before.
For these forecasts, physics-based models can be used to generate synthetic data to train the AI on scenarios that might be possible but haven’t actually happened. Once an AI model is trained on both the historic and synthetic data, it can quickly generate surge forecasts using details about the wind and atmospheric pressure.
Training the AI on data from hydrodynamic models can also improve its ability to quickly generate inundation risk maps showing which streets or houses are likely to flood in extreme events that may not have a historical precedent but could happen in the future.
The future of AI for hurricane forecasting
AI is already being used in operational storm surge forecasts in a limited way, mainly to augment the commonly used physics-based models.
As artificial intelligence models rapidly spread through every aspect of our lives and more data becomes available for training them, the technology offers potential to improve hurricane and storm surge forecasting in the future, giving coastal communities faster and more detailed warnings about the risks on the way.
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DoorDash Driver Arrested After Claiming Sexual Assault: What Really Happened?
A DoorDash driver who claimed she was sexually assaulted during a delivery is now facing felony charges after police say her viral video showed an unconscious, partially nude customer without consent. Here’s what investigators found and why the case is sparking national debate.
DoorDash delivery driver involved in a viral video controversy after claiming sexual assault; police say no assault occurred, and the driver now faces felony charges.
DoorDash Driver Arrested After Claiming Sexual Assault: What Really Happened?
A Viral Accusation Turns Into a Criminal Case
A routine food drop-off turned into a national controversy this month after a DoorDash delivery driver claimed she was sexually assaulted during a delivery — only to later be arrested herself following a police investigation. The incident, which quickly spread across TikTok and other platforms, has generated fierce debate over privacy, personal safety, and the power of viral video culture.
The driver, identified as Livie Rose Henderson, posted a video on social media in mid-October claiming that when she arrived at a customer’s home in Oswego, New York, she found the front door open and discovered a man “half-naked and unconscious” on his couch. She publicly described the moment as a sexual assault, saying she felt endangered and traumatized.
Her posts went viral almost immediately, drawing attention from millions of viewers and sparking outrage over the safety risks faced by gig workers — particularly women — who make deliveries to unfamiliar homes.
But the narrative took a dramatic turn.
Police: No Sexual Assault Occurred
According to the Oswego Police Department, an investigation found no evidence that Henderson was sexually assaulted. Instead, authorities say that she:
Entered the home without consent
Recorded the unconscious customer, who was partially nude
Posted the footage online, identifying him
Made claims police say were “false and misleading”
Investigators concluded the man was intoxicated and unconscious, not acting with intent or awareness. As a result, Henderson was arrested and charged with:
Second-degree unlawful surveillance (felony)
First-degree dissemination of unlawful surveillance images (felony)
Police emphasized that recording a person who is nude or partially nude inside their home — regardless of context — constitutes a violation of New York’s surveillance and privacy laws if done without permission.
DoorDash Drops the Driver
Henderson also claimed that DoorDash deactivated her account, something she described as retaliation for “exposing her assaulter.” But following her arrest, DoorDash stated that recording customers inside their homes violates company policy and local laws.
DoorDash said it cooperated with investigators but declined to comment further on personnel matters.
A Complicated Public Reaction
Social media reaction has been sharply divided:
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Sympathy for the driver
Many viewers initially supported Henderson, arguing that gig workers often deal with unsafe conditions and should not be forced to decide between finishing a delivery or backing away from a potentially threatening situation.
Backlash over privacy violations
Others argue that Henderson crossed legal and ethical boundaries by:
Entering a private residence
Recording a vulnerable, unconscious person
Posting it publicly
Accusing the individual of a crime without evidence
These actions, critics say, show the dangerous consequences of rushing to social media before police or professional investigators evaluate the facts.
The Larger Issue: Safety vs. Responsibility
This case highlights a broader tension in the era of app-based work and viral content:
Gig workers do indeed face unpredictable and sometimes unsafe situations.
Customers have a right to privacy in their homes.
Social media, meanwhile, rewards the fastest and most dramatic version of a story — even before the truth is known.
As the criminal process continues, Henderson’s case may set a new precedent for how privacy laws interact with the realities of delivery work and the instant visibility of online platforms.
Focuses on the legal perspective, privacy violations, and the potential consequences of posting sensitive content online.
STM Daily News is a vibrant news blog dedicated to sharing the brighter side of human experiences. Emphasizing positive, uplifting stories, the site focuses on delivering inspiring, informative, and well-researched content. With a commitment to accurate, fair, and responsible journalism, STM Daily News aims to foster a community of readers passionate about positive change and engaged in meaningful conversations. Join the movement and explore stories that celebrate the positive impacts shaping our world.
How China cleaned up its air pollution – and what that meant for the climate
How China cleaned up its air pollution: Beijing’s air quality went from hazardous to good while Delhi and Lahore still struggle. Discover how China dramatically reduced pollution since 2013—and why cleaner air may have unintended consequences for global warming and climate change.
Delhi: 442. Lahore: 334. Beijing: 16. These are the levels of PM 2.5, one of the principle measures for air pollution, on November 19. As Pakistanis and Indians struggle with hazardous air quality, in Beijing – a city once notorious for its smog – the air quality is currently rated as good. Ahead of the 2008 Beijing Olympics, the Chinese government was so concerned about pollution that it introduced temporary restrictions on cars, shut down factories and stopped work on some construction sites. The measures worked and one study later found that levels of air pollution were down 30% during the period when the temporary Olympic restrictions were in place. It would take a few more years before the Chinese government implemented a clean air action plan in 2013. Since then, China has achieved a dramatic improvement in its air quality. In this episode of The Conversation Weekly podcast, we speak to Laura Wilcox, a professor at the National Centre for Atmospheric Science at the University of Reading in the UK, to understand how China managed to clean up its air pollution. But Wilcox’s recent research uncovered some unintended consequences from this cleaner air for the global climate: the pollution was actually helping to cool the atmosphere and by taking it away, it may have accelerated global warming. Wilcox explains:
What we’re seeing is a removing of cooling that’s revealing warming that’s already there. So the air pollution isn’t the cause of the warming. It’s just letting us see stuff that we’ve already done.
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The Hong Kong high-rise fire shows how difficult it is to evacuate in an emergency
Hong Kong High-Rise Fire: The deadly Hong Kong fire exposes critical challenges in evacuating tall buildings. Learn why stair descent is slower than expected, how human behavior causes delays, and what modern safety features can save lives.
Evacuations of high-rises don’t happen every day, but occur often enough. And when they do, the consequences are almost always severe. The stakes are highest in the buildings that are full at predictable times: residential towers at night, office towers in the day. We’ve seen this in the biggest modern examples, from the World Trade Center in the United States to Grenfell Tower in the United Kingdom. The patterns repeat: once a fire takes hold, getting thousands of people safely down dozens of storeys becomes a race against time. But what actually makes evacuating a high-rise building so challenging? It isn’t just a matter of “getting people out”. It’s a collision between the physical limits of the building and the realities of human behaviour under stress.
It’s a long way down to safety
The biggest barrier is simply vertical distance. Stairwells are the only reliable escape route in most buildings. Stair descent in real evacuations is far slower than most people expect. Under controlled or drill conditions people move down at around 0.4–0.7 metres per second. But in an actual emergency, especially in high-rise fires, this can drop sharply. During 9/11, documented speeds at which survivors went down stairs were often slower than 0.3 m/s. These slow-downs accumulate dramatically over long vertical distances. Fatigue is a major factor. Prolonged walking significantly reduces the speed of descent. Surveys conducted after incidents confirm that a large majority of high-rise evacuees stop at least once. During the 2010 fire of a high-rise in Shanghai, nearly half of older survivors reported slowing down significantly. Long stairwells, landings, and the geometry of high-rise stairs all contribute to congestion, especially when flows from multiple floors merge into a single shaft. Slower movers include older adults, people with physical or mobility issues and groups evacuating together. These reduce the overall pace of descent compared with the speeds typically assumed for able-bodied individuals. This can create bottlenecks. Slow movers are especially relevant in residential buildings, where diverse occupants mean movement speeds vary widely. Visibility matters too. Experimental studies show that reduced lighting significantly slows down people going down stairs. This suggests that when smoke reduces visibility in real events, movement can slow even further as people hesitate, misjudge steps, or adjust their speed.
Human behaviour can lead to delays
Human behaviour is one of the biggest sources of delay in high-rise evacuations. People rarely act immediately when an alarm sounds. They pause, look for confirmation, check conditions, gather belongings, or coordinate with family members. These early minutes are consistently some of the costliest when evacuating from tall buildings. Studies of the World Trade Center evacuations show the more cues people saw – smoke, shaking, noise – the more they sought extra information before moving. That search for meaning adds delay. People talk to colleagues, look outside windows, phone family, or wait for an announcement. Ambiguous cues slow them even further. In residential towers, families, neighbours and friend-groups naturally try to evacuate together. Groups tend to form wider steps, or group together in shapes that reduce overall flow. But our research shows when a group moves in a “snake” formation – one behind the other – they travel faster, occupy less space, and allow others to pass more easily. These patterns matter in high-rise housing, where varied household types and mixed abilities make moving in groups the norm.
Why stairs aren’t enough
As high-rises grow taller and populations age, the old assumption that “everyone can take the stairs” simply no longer holds. A full building evacuation can take too long, and for many residents (older adults, people with mobility limitations, families evacuating together) long stair descents are sometimes impossible. This is why many countries have turned to refuge floors: fire- and smoke-protected levels built into towers as safe staging points. These can reduce bottlenecks and prevent long queues. They give people somewhere safe to rest, transfer across to a clearer stair, or wait for firefighters. Essentially, they make vertical movement more manageable in buildings where continuous descent isn’t realistic. Alongside them are evacuation elevators. These are lifts engineered to operate during a fire with pressurised shafts, protected lobbies and backup power. The most efficient evacuations use a mix of stairs and elevators, with ratios adjusted to the building height, density and demographics. The lesson is clear: high-rise evacuation cannot rely on one tool. Stairs, refuge floors and protected elevators should all be made part of ensuring vertical living is safer.Milad Haghani, Associate Professor and Principal Fellow in Urban Risk and Resilience, The University of Melbourne; Erica Kuligowski, Principal Research Fellow, School of Engineering, RMIT University, and Ruggiero Lovreglio, Professor in Digital Construction and Fire Engineering, Te Kunenga ki Pūrehuroa – Massey University This article is republished from The Conversation under a Creative Commons license. Read the original article.
STM Daily News is a vibrant news blog dedicated to sharing the brighter side of human experiences. Emphasizing positive, uplifting stories, the site focuses on delivering inspiring, informative, and well-researched content. With a commitment to accurate, fair, and responsible journalism, STM Daily News aims to foster a community of readers passionate about positive change and engaged in meaningful conversations. Join the movement and explore stories that celebrate the positive impacts shaping our world.
Gemma Ware, Host, The Conversation Weekly Podcast, The Conversation This article is republished from The Conversation under a Creative Commons license. Read the original article.
