Every year from June to September, rains fall over India, known as the summer monsoon. Crops for a fifth of humanity depend on these rains, so it's crucial to know in advance whether the season will be wet or dry. Previously, it was thought that predicting this was nearly impossible: the weather within the season changes too chaotically, limiting forecast accuracy to about 45%. But new research shows that part of this 'unpredictability' can actually be predicted if you look at slow changes in the ocean.

Picture an octopus with its tentacles on monsoon storm statistics. Previously, those tentacles seemed to be just chaotic noise: rapid fluctuations in rainfall with periods of a few days, impossible to predict a season ahead. But the authors found that part of this 'noise' is actually driven by a slow signal: sea surface temperatures in the tropical Pacific, known as El Niño.

That is, the rapid disturbances are not random but follow slow climate changes.

To test this, the scientists took a computer model of the atmosphere and ocean and created several versions, improving the physics of clouds and snow. They ran the model 16 times over 30 years with different initial conditions to account for uncertainty. Then they compared forecasts with real observations and found that the best model version gives a correlation of 0.71, explaining about 70% of monsoon variability. And a new method for estimating the limit showed that, ideally, a correlation of 0.82 could be achieved, explaining 80% of the variability.

This means the monsoon is far more predictable than we thought.

Thanks to this discovery, more reliable seasonal forecasts for India are already possible. Farmers could plan planting and irrigation in advance, and authorities could manage water resources. In the future, with further model improvements, accuracy could increase even more. So the octopus of predictable climate patterns, once elusive, is now taking shape: its tentacles are not just chaos but responses to slow ocean changes.