When we think about ocean and climate phenomena in Australia, much attention gets turned to wet La Niña and its twin dry El Niño.
But the Indian Ocean Dipole has a big influence on rainfall and weather patterns too.
The Indian Ocean Dipole (IOD) is caused by the temperature of water in the equatorial Indian Ocean.
In a neutral year, temperatures across the northern Indian Ocean are steady, and there’s little effect on Australia.
In a positive IOD phase, warmer water heads west to Africa, while cool water gathers around Indonesia and Western Australia – leading to drier air and less rainfall over southern Australia.
In a negative phase, the reverse happens, with warm water in the eastern Indian Ocean bringing more rainfall to southern Australia.
A group of Chinese and Australian researchers used a crop model and a machine learning algorithm to compare the effects of different climate drivers on wheat yields.
According to the modelling, the IOD has replaced the El Niño Southern Oscillation (ENSO) as the dominant driver of Australia’s wheat yields since the 1990s.
Read more on the Indian Ocean Dipole and other climate drivers: Climate oscillations, ENSO and more: are they changing?
Specifically, the dry conditions caused by positive Indian Ocean Dipoles has caused severe reductions in wheat yields over the past 30 years.
“Many farmers in Australia still rely on the forecasts of the ENSO to prepare for potential drought risk months in advance,” write the researchers in their paper.
“However, the impacts from the Indian and Southern Oceans receive less attention. Here we show that, across most of the Australian wheatbelt, the impacts of the IOD have been increasing in recent decades. More occurrences of positive IOD events in the future are also likely to induce more drought events.”
Do you care about the oceans? Are you interested in scientific developments that affect them? Then our new email newsletter Ultramarine, launching soon, is for you. Click here to become an inaugural subscriber.
The researchers urge for more modelling that takes different climate drivers into account in seasonal forecasts, like the Bureau of Meteorology’s ACCESS-1 models.