By Clara Hudson
India’s monsoon season was unusual this year, but many farmers there had new AI weather-forecasting tools to help them ride out the storms.
Google’s open-source artificial intelligence model NeuralGCM and the European Center for Medium-Range Weather Forecasts’s AI systems are making sophisticated and granular forecasting data available to even the smallest farms in poor areas. Thanks to the open-source AI, and decades of rainfall data, the Indian government sent out forecasts to 38 million farmers to warn them about looming monsoons.
The initiative to help farmers adapt is the latest example of how companies are expanding their weather-tracking capabilities amid mounting concerns about extreme weather and climate change.
The effort is part of a growing “democratization of weather forecasting,” said Pedram Hassanzadeh, a researcher at the University of Chicago who focuses on machine learning and extreme weather. Researchers from the university partnered with the Indian government to gather and send out the monsoon predictions.
“Up until very recently, to run a weather model, you needed a 100 million-dollar supercomputer,” said Olivia Graham, a product manager at Google Research. But now, farmers in India can make better-informed agricultural decisions quickly, she said.
“Maybe they buy more seed, maybe they buy different kinds of seed, maybe they wait to plant, maybe they plant early, but they can do so with high quality forecasts,” Graham said.
The Indian government said the monsoon season arrived early this year, but stalled midseason for 20 days. The AI forecasts accurately predicted the rain hiatus, the government said. Indian farmers grow a range of crops from rice to wheat and sugar cane.
“Before this, I mostly relied on my own experience and local knowledge to know when the monsoon would arrive,” said Parasnath Tiwari, a farmer from Madhya Pradesh in India who received forecasts on his phone.
Some businesses are turning to a growing commercial weather-tracking industry that uses AI to quickly gather data. A handful of startups have entered the AI weather space, and Microsoft has developed AI forecasting model Aurora to predict weather patterns.
Companies across industries are also investing in new ways to track the effects of climate change on their buildings, employees, operations and supply chains, including mini weather stations on their sites.
The weather forecasting industry is growing amid worries over climate and weather data availability in the U.S. following staff cuts at the National Oceanic and Atmospheric Administration under the Trump administration.
The Indian agriculture project stands out because it provided warnings to farmers specific to their needs, rather than broader information that they would have to parse, said Amir Jina, an assistant professor at the University of Chicago who also worked on the project and studies how the environment shapes societies.
“What dots hadn’t been connected before was this tailoring of forecast to purpose,” he said.
Smallholder farmers, who make up much of the agricultural industry in India, are some of the poorest people in the world, said Michael Kremer, an economics professor at the University of Chicago who studies agriculture in developing countries.
“Climate change is really threatening their livelihoods in many cases,” he said.