El Niño: Why Did We Think It Was Fading? ✛

Original: "Is ENSO a damped or a self-sustained oscillation?"
· Elle Weeks, Eli Tziperman
arXiv:2504.05513 · 2025-04-07 · CC BY 4.0 · 2 min
The method used to gauge El Niño's strength always shows decay, even when the phenomenon is actually self-sustaining.

The Pacific Ocean knows how to 'sneeze.' Every few years, warm water from the coast of Indonesia spreads toward South America, triggering floods in some regions and droughts in others. This phenomenon is called El Niño, or ENSO. The big question is: does it fade on its own, like a swing that slows down if you stop pushing? Or is there a motor inside that keeps spinning itself up?

Testing this is tricky. Scientists use a simple model that boils everything down to two numbers: how warm the water is and how thick the warm layer is. Based on these numbers, the model says whether the anomaly is growing or fading. And here's the odd part: it almost always says 'fading.' The authors of the new study decided to check whether the model itself might be lying. They ran a computer simulation where they knew the true answer, then applied the same method they use on real data.

The result: even when ENSO in the simulation was self-sustaining, the method said it was fading. This error occurred in all 100 attempts.

Why is that? The model is too simple. It leaves out many details, and those omitted details get 'absorbed' into the parameters, skewing them. It's like looking at a pendulum through frosted glass: it will always seem to be damping down, even if a spring is driving it. So the conclusion that El Niño fades may be wrong. In reality, it might be self-sustaining. That matters because the system would then be more fragile and could shift behavior abruptly if the climate warms.

The ENSO damping time estimated from standard fitting is about 1.9 years, but analytical formulas give 3 years. This discrepancy may be a consequence of the very bias that the authors uncovered.

\gamma = \frac{R - \epsilon}{2}
The growth rate is determined by the balance between the positive Bjerknes feedback (R) and the negative feedback from wave adjustment (ε).
\omega = \sqrt{F_1 F_2 - \frac{(R + \epsilon)^2}{4}}
The oscillation period depends on the product of coupling coefficients F1 and F2 and on the sum of R and ε.
Concepts
recharge oscillator model El Niño-Southern Oscillation ENSO Jin-Timmermann model El Niño index Multivariate ENSO Index Southern Oscillation spring predictability barrier La Niña natural variability ERSST TAO/TRITON moorings relative ONI equatorial wave propagation mixed mode oscillations Warm water volume damping rate seasonal cycle interannual variability North Equatorial Countercurrent