Every year, the South Asian monsoon season brings heavy rain to over a billion people in the Indian subcontinent between June and September. The rain falls in oscillations: Some weeks see 1 to 4 inches of water, while other weeks are mostly dry. Predicting when these dry and wet periods will occur is critical for agricultural and urban planning, enabling farmers to know when to harvest crops and helping city officials prepare for flooding. However, while weather predictions are mostly accurate within one or two days, precisely predicting the weather a week or month out is very difficult.

Now, a new machine-learning-based forecast has been shown to more accurately predict the South Asian monsoon rainfall 10 to 30 days in advance, a significant improvement on current state-of-the-art forecasts that use numerical modeling rather than artificial intelligence to make predictions. Understanding monsoon behavior is also important because this type of rainfall is a major atmospheric feature in the global climate.

The research was led by Eviatar Bach, the Foster and Coco Stanback Postdoctoral Scholar Research Associate in Environmental Science and Engineering, who works in the laboratories of Tapio Schneider, the Theodore Y. Wu Professor of Environmental Science and Engineering and JPL senior research scientist; and Andrew Stuart, the Bren Professor of Computing and Mathematical Sciences. A paper describing the new method appears in the Proceedings of the National Academy of Sciences on April 1.

"There is a lot of concern about how climate change will affect the monsoon and other weather events like hurricanes, heat waves, and so on," Bach says. "Improving predictions on shorter timescales is an important part of responding to climate change because we need to be able to improve preparedness for these events."

Predicting the weather is difficult because the atmosphere contains numerous instabilities—for example, the atmosphere is continually heated from the earth below, leading to cold, denser air above hotter, less dense air—as well as instability caused by uneven heating and Earth‘s rotation. These instabilities lead to a chaotic situation in which the errors and uncertainties in modeling the atmosphere‘s behavior quickly multiply, making it nearly impossible to predict further into the future.