Dmitrii Kochkov

Making artificial-intelligence tools to predict what climate change will mean for extreme weather

Stylized illustration portrait of Dmitrii Kochkov by Jessine Hein.

Jessine Hein

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As a child in Petrozavodsk, Russia, Dmitrii Kochkov loved solving geometry puzzles with his parents. In high school he participated in math and physics competitions. By the time he reached graduate school, he had turned toward machine learning and quantum physics to solve tough problems. The now 34-year-old joined Google Research as an AI resident in 2019, using machine learning to create programs that could solve interesting equations. His career then turned toward weather and climate change.

Weather is governed by fluid dynamics, described in part through partial differential equations. These equations underpin the computer models that meteorologists use to forecast daily and weekly weather. The model then applies global weather data to tell us whether we should expect rain, sunshine or extreme heat. But some processes, such as cloud formation, must be approximated in the models, which can lead to errors and biases. Kochkov and his teammates built NeuralGCM (for “general circulation model”) to replace those approximations with machine-learning predictions trained on past weather data. The system can predict weather conditions on par with the best models (up to 15 days out) and reproduce past temperature patterns as accurately or more so than current gold-standard models.


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Portrait photograph of Dmitrii Kochkov by Christie Hemm Klok.

Christie Hemm Klok

NeuralGCM is starting to show results. Researchers at the University of Chicago have used it to forecast the start of monsoon rains in India up to one month in advance, providing crucial information to millions of farmers. Kochkov’s team is creating a newer version of the model that is easier to use, which will eventually allow scientists to study how climate change is altering weather extremes and water availability. This comes at a time when funding for this kind of research is unstable. “Enabling people to do the best work they can with given resources seems more important than ever before,” he says.

This article is part of The Young American Scientists, an editorially independent project that was produced with financial support from Regeneron.

Andrea Thompson is senior desk editor for life science at Scientific American, covering the environment, energy and earth sciences. She has been covering these issues for nearly two decades. Prior to joining Scientific American, she was a senior writer covering climate science at Climate Central and a reporter and editor at Live Science, where she primarily covered earth science and the environment. She has moderated panels, including as part of the United Nations Sustainable Development Media Zone, and appeared in radio and television interviews on major networks. She holds a graduate degree in science, health and environmental reporting from New York University, as well as a B.S. and an M.S. in atmospheric chemistry from the Georgia Institute of Technology. Follow Thompson on Bluesky @andreatweather.bsky.social

More by Andrea Thompson
Scientific American Magazine Vol 335 Issue 1This article was published with the title “Dmitrii Kochkov” in Scientific American Magazine Vol. 335 No. 1 (), p. 51
doi:10.1038/scientificamerican072026-1qskwvNTHlsypkTEddEceB

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