AI Enhances Flood Warnings but Cannot Erase Risk of Disaster

A view shows a flooded schoolyard in Bamako, Mali, September 23, 2024. (Reuters)
A view shows a flooded schoolyard in Bamako, Mali, September 23, 2024. (Reuters)
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AI Enhances Flood Warnings but Cannot Erase Risk of Disaster

A view shows a flooded schoolyard in Bamako, Mali, September 23, 2024. (Reuters)
A view shows a flooded schoolyard in Bamako, Mali, September 23, 2024. (Reuters)

When floods ripped through parts of Europe in September, the scale of the destruction took people by surprise. The intense rains should not have, because those had been predicted by sophisticated forecasting systems enhanced with artificial intelligence.

But forewarned did not mean forearmed. Though the rains were accurately predicted, the effects in the deluged areas were not - a fact that highlights the difficulties of dealing with ever more common extreme weather.

AI has supercharged weather forecasting, using a range of statistical tools to analyze years of historical data and predict patterns, and at a lower cost than traditional numerical weather predictions.

AI technology can create more specific predictions ahead of events such as urban flooding or in complex terrain such as mountainous areas.

For example, Google-funded GraphCast, a machine learning–based method trained directly from reanalysis data, was found to outperform traditional models. Reanalysis data relies on past forecasts rerun with modern forecasting models to provide the most complete picture of past weather and climate.

But there are still gaps in knowledge, in how the information is used and in investment to strengthen data gathering models, experts say.

"In some cases and for some variables, AI models can beat physics-based models, but in other cases vice versa," said Andrew Charlton-Perez, professor of meteorology at the University of Reading in the UK.

One issue is that the effectiveness of an AI model is only as good as the information it is fed. If there is little input data, or extreme events happen more frequently at different times of the year or in different regions, weather disasters become more challenging to predict.

"A good use of the AI-based weather forecasts would be to complement and enhance our forecasting toolbox, perhaps by allowing us to produce larger ensembles of forecasts that enable accurate assessment and interpretation of the likelihood of extreme events," Charlton-Perez added.

COMMUNICATION IS KEY

Since January, the European Center for Medium-Range Weather Forecasts (ECMWF), an independent organization that provides predictions four times per day to European countries, has been using the Artificial Intelligence/Integrated Forecasting System (AIFS).

This data-driven forecasting model makes multiple predictions rapidly and delivers long-term forecasts of weather events like cyclones and heatwaves.

The ECMWF readings ahead of the September floods were accurate, experts say.

Thomas Wostal, press officer for meteorological observatory GeoSphere Austria, told Context/the Thomson Reuters Foundation that their numerical models - including the ECMWF's predictions - foresaw 300-400 millimeters (11.8-15.7 inches) of rain locally, which came to pass.

But even with accurate forecasts, scientists say communication is key, especially in an era when climate change means extreme weather is becoming more frequent.

"I think what happened with (the recent floods) ... is that it's so rare - a one in 150- to 200-year event - that even if the weather models capture it, there's a reasonable degree of uncertainty," said Shruti Nath, a postdoctoral research assistant in predicting weather and climate at Oxford University.

"You have to produce the warning in a way that is communicative, in the degree of severity it could possibly have on people, then people could see the cost of inaction versus the cost of action is actually much greater. So then they would actually put (in) more resources," she said.

EUROPE BEHIND THE CURVE?

Europe faces urgent climate risks that are outpacing policies and adaptation actions, a report from the European Environment Agency has warned.

Extreme heat, drought, wildfires and flooding will worsen in Europe even under optimistic global warming scenarios and affect living conditions throughout the continent, the EEA says.

After the floods, the European commissioner for crisis management, Janez Lenarčič, said the disaster was not an anomaly.

"These extreme weather events that used to be once in a lifetime are now an almost annual occurrence. The global reality of climate breakdown has moved into the everyday lives of Europeans," he said.

Some tech entrepreneurs say Europe is not ready.

Jonas Torland, co-founder of Norway-based 7Analytics, which develops models for predicting floods and landslides, said governments and businesses in the United States had risk managers who were more accustomed to assessing environmental hazards, while in Europe, authorities lacked readiness.

"We often see substantial expenditures with minimal data support for informed decision-making", Torland, whose models are used in the cities of Oslo, Bergen and Kristiansand, told the Thomson Reuters Foundation.

"While AI is a crucial component of these models, unfortunately, governments are not investing in or purchasing these advanced AI solutions," he said adding that he believed governments "stick to their old data providers and consultants.”

Data processing is also a challenge because these complex AI models need to run updates every hour as forecasts change.

That requires both a lot of computing power, and a lot of time - especially at more minute scales.

A 1-by-1 meter grid, which 7Analytics uses for its predictions, is 100 times more detailed than a 10-by-10 meter grid, but requires more than 100 times as long to process.

High computing power also means huge amounts of energy and water are needed, which makes AI models part of the problem because they are adding to the planet-heating emissions driving the climate emergency.

Some big technology companies, like Microsoft and Google, are exploring the use of nuclear power to run their huge data storage centers.

Other scientists stress that beyond refining their forecasting abilities, authorities need to invest in physical solutions, like developing areas where floodwater can safely be stored, and early warning systems.

They also need to minimize development in flood-prone areas, given the likelihood of more intense climate change-driven floods, and meet their commitments to limit emissions.

"It's not a question of data or technology or knowledge. It's a question of implementation, political will," Friederike Otto, a senior lecturer at Imperial College in London, said in an email response to questions.

"As long as the world burns fossil fuels, the root cause of climate change, extreme weather events will continue to intensify, killing people and destroying homes. To curb this trend, we need to replace oil, gas and coal with renewable energy."



KAUST Scientists Develop AI-Generated Data to Improve Environmental Disaster Tracking

King Abdullah University of Science and Technology (KAUST) logo
King Abdullah University of Science and Technology (KAUST) logo
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KAUST Scientists Develop AI-Generated Data to Improve Environmental Disaster Tracking

King Abdullah University of Science and Technology (KAUST) logo
King Abdullah University of Science and Technology (KAUST) logo

King Abdullah University of Science and Technology (KAUST) and SARsatX, a Saudi company specializing in Earth observation technologies, have developed computer-generated data to train deep learning models to predict oil spills.

According to KAUST, validating the use of synthetic data is crucial for monitoring environmental disasters, as early detection and rapid response can significantly reduce the risks of environmental damage.

Dean of the Biological and Environmental Science and Engineering Division at KAUST Dr. Matthew McCabe noted that one of the biggest challenges in environmental applications of artificial intelligence is the shortage of high-quality training data.

He explained that this challenge can be addressed by using deep learning to generate synthetic data from a very small sample of real data and then training predictive AI models on it.

This approach can significantly enhance efforts to protect the marine environment by enabling faster and more reliable monitoring of oil spills while reducing the logistical and environmental challenges associated with data collection.


Uber, Lyft to Test Baidu Robotaxis in UK from Next Year 

A sign of Baidu is pictured at the company's headquarters in Beijing, China March 16, 2023. (Reuters)
A sign of Baidu is pictured at the company's headquarters in Beijing, China March 16, 2023. (Reuters)
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Uber, Lyft to Test Baidu Robotaxis in UK from Next Year 

A sign of Baidu is pictured at the company's headquarters in Beijing, China March 16, 2023. (Reuters)
A sign of Baidu is pictured at the company's headquarters in Beijing, China March 16, 2023. (Reuters)

Uber Technologies and Lyft are teaming up with Chinese tech giant Baidu to try out driverless taxis in the UK next year, marking a major step in the global race to commercialize robotaxis.

It highlights how ride-hailing platforms are accelerating autonomous rollout through partnerships, positioning London as an early proving ground for large-scale robotaxi services ‌in Europe.

Lyft, meanwhile, plans ‌to deploy Baidu's ‌autonomous ⁠vehicles in Germany ‌and the UK under its platform, pending regulatory approval. Both companies have abandoned in-house development of autonomous vehicles and now rely on alliances to accelerate adoption.

The partnerships underscore how global robotaxi rollouts are gaining momentum. ⁠Alphabet's Waymo said in October it would start ‌tests in London this ‍month, while Baidu ‍and WeRide have launched operations in the ‍Middle East and Switzerland.

Robotaxis promise safer, greener and more cost-efficient rides, but profitability remains uncertain. Public companies like Pony.ai and WeRide are still loss-making, and analysts warn the economics of expensive fleets could pressure margins ⁠for platforms such as Uber and Lyft.

Analysts have said hybrid networks, mixing robotaxis with human drivers, may be the most viable model to manage demand peaks and pricing.

Lyft completed its $200 million acquisition of European taxi app FreeNow from BMW and Mercedes-Benz in July, marking its first major expansion beyond North America and ‌giving the US ride-hailing firm access to nine countries across Europe.


Italy Fines Apple Nearly 100m Euros over App Privacy Feature

An Apple logo hangs above the entrance to the Apple store on 5th Avenue in the Manhattan borough of New York City, July 21, 2015. REUTERS/Mike Segar/File Photo Purchase Licensing Rights
An Apple logo hangs above the entrance to the Apple store on 5th Avenue in the Manhattan borough of New York City, July 21, 2015. REUTERS/Mike Segar/File Photo Purchase Licensing Rights
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Italy Fines Apple Nearly 100m Euros over App Privacy Feature

An Apple logo hangs above the entrance to the Apple store on 5th Avenue in the Manhattan borough of New York City, July 21, 2015. REUTERS/Mike Segar/File Photo Purchase Licensing Rights
An Apple logo hangs above the entrance to the Apple store on 5th Avenue in the Manhattan borough of New York City, July 21, 2015. REUTERS/Mike Segar/File Photo Purchase Licensing Rights

Italy's competition authority said Monday it had fined US tech giant Apple 98 million euros ($115 million) for allegedly abusing its dominant position in the mobile app market.

According to AFP, the AGCM said in a statement that Apple had violated privacy regulations for third-party developers in a market where it "holds a super-dominant position through its App Store".

The body said its investigation had established the "restrictive nature" of the "privacy rules imposed by Apple... on third-party developers of apps distributed through the App Store".

The rules of Apple's App Tracking Transparency (ATT) "are imposed unilaterally and harm the interests of Apple's commercial partners", according to the AGCM statement.

French antitrust authorities earlier this year handed Apple a 150-million euro fine over its app tracking privacy feature.

Authorities elsewhere in Europe have also opened similar probes over ATT, which Apple promotes as a privacy safeguard.

The feature, introduced by Apple in 2021, requires apps to obtain user consent through a pop-up window before tracking their activity across other apps and websites.

If they decline, the app loses access to information on that user which enables ad targeting.

Critics have accused Apple of using the system to promote its own advertising services while restricting competitors.