Why El Niño Sometimes Turns into a Giant ✎

Original: "Understanding the origin of extreme events in El Niño-Southern Oscillation"

· Arnob Ray, Sarbendu Rakshit, Gopal K. Basak, Syamal K. Dana, Dibakar Ghosh

arXiv:2006.11969 · 2020-06-22 · arXiv non-exclusive · independent analysis · 1 min

The ocean and atmosphere work like a pendulum that occasionally slips off its axis and makes a huge swing.

The Pacific Ocean off the coast of Peru sometimes warms dramatically, bringing drought to Australia and floods to South America. This phenomenon is called El Niño. Usually it arrives with similar strength, but occasionally the ocean heats up much more intensely, with devastating consequences. Scientists have long struggled to understand why.

They built a simple model in which the ocean and atmosphere exchange heat. The model has a slow component, the depth of the warm water layer, and fast components, the surface temperatures. When a parameter governing heat transport along the equator crosses a critical value, the system's behavior changes abruptly. It is like a pendulum that normally swings steadily but sometimes slips off its axis and makes a huge arc. An internal crisis emerges: the trajectory begins to explore new regions that were previously inaccessible.

The key role is played by a narrow channel through which the trajectory must pass. If the channel is wide, events follow one another with similar strength. If the channel narrows, the trajectory gets stuck, then bursts out with a giant temperature surge.

Previously, El Niño was thought to be always chaotic, but now it is clear that rare giant events are born differently. That is why they are so hard to predict in advance. This finding helps us better understand how the ocean and atmosphere generate extreme phenomena, and could aid in improving forecasts in the future.

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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

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Why El Niño Sometimes Turns into a Giant ✎