Heavy Turbulence on Flights Is Likely to Get Worse
Meteorologists predict more bumpy flights as climate change makes hard-to-detect clear-air turbulence more common
Meteorologists predict more bumpy flights as climate change makes hard-to-detect clear-air turbulence more common
Flights headed to Honolulu, Tampa, Fla., and Frankfurt in recent months hit turbulence so severe that some passengers and crew ended up in the hospital with injuries.
Actor Matthew McConaughey was a passenger on the Lufthansa flight to Germany. In a recent podcast interview with Kelly Ripa, he described seeing red wine suspended in midair before it crashed down.
“It was a hell of a scare,” Mr. McConaughey, who wasn’t hospitalised, said on the podcast. “A complete loss of control.”
Pilots and meteorologists say bumps are a normal part of flying. The Federal Aviation Administration is still investigating the Lufthansa flight. But meteorologists say climate change is distorting the jet stream, making a certain type of severe turbulence—called clear-air turbulence—more likely in the future.
Severe turbulence injuries are rare. Between 2009 and 2022, 163 people were seriously injured during turbulence, according to National Transportation Safety Board data. Flight attendants, who are more likely to be standing during flights, are most likely to get injured, the data show.
Though technology that reports turbulence has vastly improved in recent decades, it can be tough to predict.
“You’re talking about a little pin drop in the atmosphere,” says Bill Duncan, head of aviation forecasting operations at the Weather Co., which supplies turbulence forecasts and weather insights to major airlines.
Turbulence happens when swirling air currents push against the wing of the plane, which then moves the wings up and down or the body of the plane from side to side, says Paul D. Williams, a professor of atmospheric science at the University of Reading in England.

Atmospheric pressure, changing wind direction, air around mountains and cold- or warm-weather fronts can cause turbulence, physicists say.
Turbulence caused by wind shear, meaning sudden changes in the speed and direction of wind, is called clear-air turbulence. It is called this because it occurs at higher altitudes in cloudless areas. Aircraft can change altitude suddenly, and pilots usually can’t detect this type of turbulence in advance.
Since 1979, the amount of wind shear in the jet stream has increased 15%, according to a study Dr. Williams co-wrote that was published in the science journal Nature in 2019. At higher altitudes where planes fly, climate change is altering temperature patterns, which creates more wind shear, he says.

Dr. Williams’s research predicts that the amount of clear-air turbulence in the atmosphere in the mid-Northern Hemisphere is expected to more than double over the next three to six decades.
Some of the more popular international flight routes from the U.S., such as New York-London and San Francisco-Tokyo, will experience more clear-air turbulence because they fly in the mid-Northern Hemisphere, he says.
Flight crews now use more specific language to address different levels of turbulence, says Dennis Tajer, a captain for American Airlines and spokesman for the Allied Pilots Association, a union. He began flying for commercial airlines about 30 years ago and says he encounters more clear-air turbulence now compared with early in his career.

American Airlines updated its flight manual in May 2022 to better define turbulence procedures for flight crews. The captain turns on the seat belt sign for all types of turbulence, but crews now take specific actions depending on the severity of the turbulence, he says.
During severe turbulence, flight attendants need to secure carts, place hot liquids in carts or on the floor and secure themselves as quickly as possible by sitting down in the nearest seat or on the floor.
American and United are among the airlines that give pilots access to software called SkyPath, which crowdsources turbulence reports from pilots’ iPads in real time.
SkyPath uses vibrations from the pilot’s iPad to measure turbulence and reports out to other nearby aircraft, providing advance warning of the conditions in real time, a United spokeswoman said in an email.
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AI doesn’t rebel—people design, deploy and profit from it. The real danger lies in allowing tech companies to escape accountability while shaping regulations that protect their dominance.
A wave of corporate warnings and technical disclosures has flooded the media, with headlines worrying over “swarms” of rogue artificial-intelligence agents launching “unprecedented” cyberattacks, outsmarting their makers, and inching toward a terrifying autonomy. The most revealing part of this narrative isn’t what the software did. It’s who is telling the story—and why. When corporate leaders publicly insist that the systems they financed, engineered and deployed are suddenly beyond their power to contain, skepticism isn’t only healthy; it is essential.
For years, Silicon Valley has drawn scrutiny from civil society and global regulators over tangible harms such as youth mental health deterioration and systematic privacy violations. Today, industry figures seem to be trying to change that public image. Loudly blowing the whistle on their own systems—just as two of the leading companies were preparing for massive initial public offerings—lets AI executives position themselves as a new generation of leaders who have come to terms with their societal responsibilities. They seem to want us to believe that they no longer want to “move fast and break things” but will instead stand as vigilant guardians between humanity and a technological apocalypse.
There is one glaring problem: Software doesn’t rebel. A mathematical model possesses neither intent, malice nor the will to defy its creators, let alone extinguish our species. AI is a human artifact, engineered for profit.
When an agentic model in an evaluation sandbox connects to an unauthorized server or executes an exploit, it hasn’t staged a coup. It has tried to meet the human-defined objectives set out before it through a path its designers failed to constrain. It’s the digital equivalent of the King Midas myth, in which the king’s ill-defined wish turns even his food and drink into gold.
That powerful experimental models were able to discover novel vulnerabilities and breach external systems isn’t a sign of a dangerous superintelligence but of human error or negligence. There is no sentient actor lurking in the weights to be reasoned with, feared or pacified. There are only human software engineers, product managers and corporate boards deciding which guardrails are worth the latency cost and which permissions can be skipped in the race to market.
Policymakers and voters need to resist AI exceptionalism. In any other discipline—from civil engineering to pharmaceuticals—courts and regulators treat a system failure as evidence of bad product design and inadequate safety testing. If an aircraft crashes, we focus on finding the engineering defect, correcting it, and enforcing established liability standards for the damage created.
By leaning on an anthropomorphic narrative, Silicon Valley attempts to repackage its specific human choices that led to experimental, powerful models behaving unexpectedly during tests as an existential peril. Elevating the issue to a cosmic scale leaves the public paralyzed and takes ordinary product accountability off the table.
In the cutthroat race for venture capital and market dominance, building guardrails slows down deployment. Grandstanding about uncontrollable power costs nothing and generates billions of dollars in free publicity, justifying stock prices, all while cultivating an aura of technological capability not only to build the frontier but also ultimately to rein it in.
Governments need to recognize regulatory capture when it stares them in the face. Tech leaders’ strategy looks transparent: Alarm Washington and Brussels into creating a regime in which only trillion-dollar incumbents with fully staffed compliance and safety departments can legally operate. By sitting at the policymakers’ tables before anyone else, these companies can help draft rules digging an impassable moat protecting them from open-source developers and upstart competitors, domestic or international. The real danger is in further concentrating the tech industry into the hands of only a few companies with deep pockets.
Beijing and Washington have brushed off those tech leaders’ calls, albeit for very different reasons. Chinese state media dismissed them as part of the “Cold War playbook” and intended to preserve U.S. dominance. Xi Jinping argued for exactly the opposite at the Brics Summit on Sept. 12, calling on Brics countries to “strengthen cooperation in the field of AI, encourage open source, openness, collaboration and sharing, and break new grounds and scale new heights.” President Trump, steeped in a doctrine of unfettered capitalism and technological supremacy, called fears that AI could destroy humanity a “hoax.” Vice President JD Vance warned that AI companies “begging the government to regulate them” looked like a “Trojan Horse.”
Striving to pursue its “European way” on AI and assert regulatory leadership, Europe, by contrast, welcomed the call. European Union President Ursula von der Leyen made this clear at the State of the EU speech last Wednesday and announced that the EU will invite “the main frontier labs for a discussion on how we can support ongoing industry efforts to pace the frontier.”
Europe has been here before. In an effort to lead global regulation and react to fears borne from ChatGPT, Europe rushed its landmark AI Act into law in 2024. Already the world’s most restrictive rulebook, the framework quickly proved too broad and complex to enforce. Stalled by implementation delays and concerns about European competitiveness, the EU postponed the law’s full rollout, leaving regulations uncertain.
AI should be regulated—risks exist and should be taken seriously. But governments need to act based on available evidence and verified facts, not corporate PR panic, the views of industry insiders, or the desire for quick political wins. The greatest danger facing society isn’t that software will awaken and overthrow its human masters. It is that we will allow the creators of the software to abdicate human responsibility for the systems they choose to build and help them pull up the ladder to market access behind them.
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