Two Orchestras, One Score: How El Niño Splits the Midlatitude Climate ✎

Original: "Extratropical low-frequency variability with ENSO forcing: A reduced-order coupled model study"
arXiv:2103.00517 · 2021-02-28 · arXiv non-exclusive · independent analysis · 3 min
The same tropical forcing gives rise to two coexisting climate regimes in the midlatitudes, and their predictability differs radically.

Two orchestras play from the same score, but in different keys. The score is the warm El Niño current, which every few years heats the tropical Pacific. The key is the regime in which the midlatitude atmosphere responds to that heating. One orchestra plays steadily and predictably; the other keeps stumbling, yet its playing carries deep bass notes that the first lacks.

Climate scientists built a simplified two-part model. The tropical part describes El Niño itself with three equations, while the extratropical part describes the midlatitude atmosphere and ocean with thirty-six variables. The tropics act on the midlatitudes like a conductor: the warm current strengthens the westerly wind, and that command feeds into the atmospheric equations. The model was run hundreds of times from different initial states, each time fifteen thousand years into the future, and the researchers watched what the system settled toward.

The attracting set here does not sit still, because time enters the equations explicitly. Such a set is called a time-dependent attractor, or pullback attractor. The system starts in the distant past and gradually gets pulled toward this moving set, like a speck of dust toward a spinning fan.

It turned out that under the same forcing, two such attractors exist. The first, with a Lyapunov exponent of about 0.25 per day, has almost no intrinsic slow oscillations: its variability is tied to the rhythm of El Niño. The second, with an exponent of about 0.1 per day, produces pronounced oscillations with a period of about 58 years. The difference in predictability is twofold: the second regime can be forecast twice as far ahead as the first. When the forcing is chaotic and irregular, the second attractor becomes metastable: even a tiny perturbation, one hundred million times smaller than the main signal, can knock the system into the first regime. The reverse transition requires a perturbation a thousand times stronger.

In the oceanic variables, the second regime looks like three strands shifted in phase by 35 years. Each strand is a set of trajectories that run almost in sync, even though each one is chaotic. Like three columns of soldiers marching in step, but within each column the step falters a little.

This result changes how we view climate prediction. The standard approach is to average over many runs to get the most likely scenario. But if the system can jump between two regimes with different statistics, the arithmetic mean describes neither. It is like averaging the sound of two orchestras playing in different keys: you would get a cacophony unlike either part. Hence the practical takeaway: to properly assess uncertainty, you need very long runs and a large ensemble size; otherwise you might simply miss the second regime.

Two orchestras play from the same score, and now we know they are in different keys. Previously it seemed that the midlatitude climate under El Niño had a single regime, just with noise. Now we see there are two regimes that coexist, and transitions between them are rare but possible. This knowledge does not give a ready forecast, but it warns against naive averaging and points to where to look next.

In the chaotic regime, the oceanic trajectories of PBA2 align into three distinct bundles, shifted in phase by 35 years. This resembles a troop of soldiers marching in lockstep, even though each one follows its own chaotic trajectory.

The idea of multiple climate regimes, between which the system can jump, echoes Kim Stanley Robinson's novel 'Forty Signs of Rain', where climatologists confront unexpected and abrupt shifts in the climate system that do not fit linear forecasts.

Concepts
ENSO spring predictability barrier El Niño-Southern Oscillation TAO/TRITON moorings Multivariate ENSO Index Jin-Timmermann model El Niño index Southern Oscillation recharge oscillator model seasonal forcing La Niña equatorial wave propagation natural variability mixed mode oscillations Westerly wind burst North Equatorial Countercurrent interannual variability ocean-atmosphere coupling Bjerknes feedback seasonal cycle