By Attracta Mooney in Oxford, Susannah Savage in Rome, Michael Peel in Geneva and Steven Bernard in London
For the past seven months, Giancarlo Pini has been scrutinising a small stretch of water in the Pacific Ocean, watching as it has grown hotter and hotter.
The warming waters herald the arrival of what Pini, an earth observation expert at the UN’s World Food Programme, describes as a “Godzilla” El Niño. Every few years, the naturally occurring phenomenon causes drastic disturbance to global weather patterns when normal trade winds weaken and warm waters spread eastward across the tropical Pacific. Harvests are devastated, electricity supplies strained and shipping can be pushed off course.
But even before its expected peak, this year’s El Niño is already the strongest on record in absolute terms. “It’s really a historic one,” says Pini.
To deal with that monster — and help anticipate and minimise its effects on people’s food and livelihoods — he and many others are now looking to AI. Those seeking to profit from such predictions range from crop farmers in Kenya to hedge funds focusing on sugar futures.
But some scientists think the world is putting too much store on a flawed technology that is not fundamentally suited to an intrinsically unpredictable weather phenomenon, especially at a time of rising global temperatures.
Months before the El Niño was officially declared in June, Pini was already using AI as well as traditional weather forecasts to issue warnings about hits to food production. By August, his UN body predicted that El Niño would lead to 274mn more people being acutely “food insecure” by the end of 2027 across 45 countries.
A separate report from the Climate Impact Lab, a joint research project from the universities of California, Chicago, Rutgers and others, in September predicted at least 451,000 heat-related deaths linked to El Niño, with countries including Nigeria, Indonesia and Sudan among the worst affected.
