The El Niño Pendulum: How Warming First Amplifies, Then Damps It ✛

Original: "The Rise and Fall of ENSO in a Warming World: Insights from a Lag-Linear Model"
· PJ Tuckman, Da Yang
arXiv:2603.03458 · 2026-03-03 · CC BY 4.0 · 3 min
A simple delayed model explains why El Niño strengthens at first and then weakens under global warming, and lets you forecast its strength without running climate models.

Every few years, the Pacific Ocean off Peru warms so abruptly that fish disappear and rains flood the desert. This phenomenon is called El Niño, and it acts like a pendulum that swings the planet's climate. But when the planet itself warms, the pendulum behaves strangely: first its swing widens, then it suddenly fades. Until recently, climatologists could not explain this sequence because it arises from the competition of two processes operating at different speeds.

El Niño is the warm phase of a natural oscillation in sea surface temperature in the eastern Pacific. Its opposite, La Niña, brings unusually cold water.

The first process is the warming of the upper ocean. When the atmosphere traps more heat, the surface water warms faster than the depths. A sharp boundary forms between the warm top and cold bottom, and this boundary works like a taut string: any disturbance travels along it more strongly. So in the first decades of warming, El Niño indeed intensifies. The second process is the weakening of the trade winds, those winds that blow along the equator from east to west. They push warm water toward Indonesia, while cold deep water upwells off South America. When the trades weaken, this conveyor slows, and the temperature difference between the ocean's west and east diminishes. That means El Niño has less energy to draw from.

The Walker circulation is a giant loop of air over the tropical Pacific: warm air rises near Indonesia, flows eastward aloft, and sinks near Peru. Its weakening is directly linked to climate warming.

The key is the delay. The upper ocean responds to warming almost immediately, while deeper layers, especially water at about a hundred meters depth, warm with a lag of decades. It is like heating an old house: the radiator by the window warms up right away, but the far wall only an hour later. The scientists built a model that accounts for this delay. It takes today's surface temperature and the surface temperature from thirty-six years ago, and from these two numbers predicts El Niño's strength. Across different climate models, this simple formula explains about ninety percent of the variation, without a single run on an expensive supercomputer.

The peak swing occurs roughly fifty years after warming begins. If emissions grow rapidly, as in the scenario of unbridled coal burning, El Niño intensifies by twenty percent. If emissions are cut, as in the moderate scenario, the strengthening is smaller, about fifteen percent, and the peak comes later. But in both cases, after the peak the pendulum begins to fade. By the end of the century, El Niño's strength could drop by forty percent from preindustrial levels. Peruvian fishermen, who have lived for centuries in the rhythm of this oscillation, will find themselves in a world where familiar disasters become rarer, but so do familiar bountiful years.

The pendulum that is first swung and then damped is not just a metaphor. It is an accurate description of how the climate system works: rapid surface warming first gives El Niño extra energy, while slow deep warming takes it away. Understanding this mechanics lets you calculate the future without supercomputers: you only need today's ocean temperature and the ocean temperature from thirty-six years ago.

Economic losses from the extreme El Niño events of 1997–1998 and 2015–2016 are estimated at 4.1 and 5.7 trillion dollars, respectively, while La Niña brings only modest economic benefits.

\Delta M_{\mathrm{ENSO}}(t) = \alpha \Delta \mathrm{GMST}(t) + \beta \Delta \mathrm{GMST}(t - t_{\mathrm{lag}})
The change in ENSO strength equals the sum of contributions from the current sea surface temperature and from the temperature with a lag corresponding to the subtropical cell time.
Scientists
Ludwig BoltzmannJohn von NeumannJosiah Willard GibbsHenri Poincaré
Concepts
ENSO El Niño-Southern Oscillation El Niño index Southern Oscillation spring predictability barrier La Niña Jin-Timmermann model Multivariate ENSO Index recharge oscillator model TAO/TRITON moorings natural variability ERSST Warm water volume equatorial wave propagation interannual variability relative ONI North Equatorial Countercurrent NOAA CPC NOAA PMEL / TAO ocean-atmosphere coupling