The Climate Pendulum: How Extreme El Niño Events Are Born ✎

Original: "Understanding the origin of extreme events in El Niño-Southern Oscillation"
arXiv:2006.11969 · 2020-06-22 · arXiv non-exclusive · independent analysis · 2 min
An interior crisis in a slow-fast ENSO model explains why rare giant events behave differently from ordinary ones.

Every few years, the Pacific Ocean off the coast of Peru warms up, and then fields dry out in Australia while deserts in Chile get drenched. This phenomenon is called El Niño. Usually it arrives with nearly the same intensity, but sometimes the ocean heats up as if someone had given the pendulum a mighty shove: the heat lasts longer, and the consequences are devastating. Why this happens has long remained a puzzle.

Scientists have built a simplified model in which the ocean and atmosphere exchange heat. The model has one slow variable, the depth of the warm water layer in the western Pacific, and fast variables, the surface temperatures in the east and west. When the parameter controlling heat transport along the equator crosses a critical value, the system's behavior changes abruptly. What mathematicians call an interior crisis occurs: the chaotic attractor suddenly expands, and trajectories begin to visit regions that were previously inaccessible.

An interior crisis is like a river bursting its banks after prolonged rains: the channel remains the same, but water now floods the floodplain, and the current becomes unpredictable.

A key role is played by a channel in phase space, a narrow passage that trajectories must go through. If the channel is wide, events occur one after another with similar strength, like ordinary El Niños. But if the channel narrows, trajectories get stuck and then break out with a giant temperature surge. That is why rare extreme events show large variability in amplitude and return time, and their height distribution is multimodal with a bounded tail.

The intervals between extreme events are best described by a lognormal distribution, and the autocorrelation function shows short-term dependence. This means that partial prediction is possible, but only over short horizons.

It was previously known that El Niño manifests as chaotic mixed oscillations, but the origin of rare giant events remained unclear. Now it has been shown that they arise through a specific mechanism: a period-doubling cascade merges with a period-adding cascade, and at that moment the attractor expands. This explains why strong El Niños are fundamentally less predictable than ordinary ones. For climatology, this means that even a simple model can reproduce the complex statistics of extreme events, and similar mechanisms should be sought in more realistic models and in observational data. Today, this approach helps improve our understanding of how the ocean and atmosphere generate rare catastrophic events, although accurate prediction is still far off.

The threshold for an extreme event in the model is about 25.5°C for sea surface temperature in the eastern Pacific, close to real values at which El Niño is considered strong. The time series for statistics was generated over $10^{12}$ iterations, corresponding to thousands of years of model time.

G_{\xi,\gamma}(x) = \frac{1}{\gamma}\left(1+\frac{\xi x}{\gamma}\right)^{-1/\xi-1}
Used to describe the distribution of exceedances over a threshold; the sign of the shape parameter ξ determines whether the tail is bounded above.
e(u) = E(X-u \mid X>u)
The average excess of a random variable over a threshold u; used to select the extremality threshold.
e(u) \approx \frac{\gamma}{1-\xi} + \frac{\xi}{1-\xi}u
Allows estimation of the shape parameter ξ from the slope of the linear part of the e(u) plot.
Concepts
El Niño-Southern Oscillation El Niño Multivariate ENSO Index Westerly wind burst ENSO recharge oscillator model Southern Oscillation Jin-Timmermann model mixed mode oscillations interannual variability natural variability epidemic seasonal cycle intermittency hopf bifurcation avalanche spring predictability barrier saddle node bifurcation La Niña Madden–Julian Oscillation