Seasonal Climate Seesaw: How El Niño and the Indian Ocean Dipole Are Linked ✎

Original: "Coupling functions in climate"
· Woosok Moon, John S. Wettlaufer
arXiv:1909.05096 · 2019-09-03 · arXiv non-exclusive · independent analysis · 2 min
A two-dimensional stochastic model with coupling functions shows that El Niño drives the seasonal variability of the Indian Ocean Dipole, not the other way around.

On a playground, two swings stand side by side. One child pumps on their own, while the other barely moves until the first gives a push with their foot. Something similar happens in the tropical Pacific and Indian Oceans, except instead of children, there are warm and cold masses of water.

El Niño is the warm phase of an ocean temperature oscillation that occurs every few years and changes weather across the planet. The Indian Ocean Dipole is the temperature difference between the western and eastern parts of that ocean. Both phenomena have long been studied separately, but exactly how they influence each other remained unclear. Scientists built a mathematical model linking these two indices and calculated who is pushing whom.

The model works like two equations with cross terms. Each equation describes how temperature changes in its own region, but with an additional term that depends on the temperature difference between the regions. This term is called the coupling function, and it shows how strongly one phenomenon drags the other along.

It turned out that the Indian Ocean Dipole has almost no influence on El Niño: its coupling function hovers near zero all year. But El Niño acts noticeably on the dipole, especially in August, when the dipole is just beginning to mature. At that moment, El Niño stabilizes it, preventing the temperature from straying too far from the average value.

Validation against 149 years of data confirmed that the model reproduces the real fluctuations of both indices and their joint behavior. The coupling peaks in October, when the dipole reaches its maximum variability. This means that warm Pacific waters indeed drive the seasonal rhythm of the Indian Ocean.

This approach can be applied to any pair of climate indices to build a network of interactions. Linking several such models would yield a tool for seasonal forecasting of anomalies in different regions. The swings on the playground turn out to be not random neighbors but a coupled system, where one child sets the rhythm for the other.

The names El Niño and La Niña are linked to Christmas: the warm phase often peaks in December, and Peruvian fishermen named it after the Christ child.

\frac{d\eta_1}{dt} = a_1(t)\eta_1 + N_1(t)\xi_1(t) + b_{12}(t)(\eta_2-\eta_1), \quad \frac{d\eta_2}{dt} = a_2(t)\eta_2 + N_2(t)\xi_2(t) + b_{21}(t)(\eta_1-\eta_2)
The change of each variable is determined by its own stability, noise, and the difference with the other variable multiplied by the coupling function.
Concepts
ocean-atmosphere coupling Indian Ocean Dipole ENSO TAO/TRITON moorings Multivariate ENSO Index zebiak cane model interannual variability Jin-Timmermann model climate network El Niño index Teleconnection El Niño NOAA CPC seasonal cycle IRI North Atlantic Oscillation tropospheric biennial oscillation mixed mode oscillations seasonal forcing empirical orthogonal function