NASA, IBM just open sourced an AI climate model so you can fine-tune your own

Researchers at IBM and NASA this week released an open source AI climate model designed to accurately predict weather patterns while consuming fewer compute resources compared to traditional physics-based simulations.

Developed as part of a collaboration between IBM and NASA with help from the US Department of Energy's Oak Ridge National Laboratory, the 2.3 billion parameter foundation model called Prithvi WxC was trained on 40 years of observation data from NASA's Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2) dataset.

Despite the model's diminutive size, researchers say it was still able to accurately generate global surface temperatures using a random sample that contained just 5 percent of the original data. They also believe the model is particularly well suited to simulating the behavior of hurricanes and atmospheric rivers. However, the model's real advantage may just be its flexibility.

IBM and NASA aren't the only ones experimenting with AI models for weather and climate forecasting. For example, researchers at Google detailed a novel approach to bolstering the accuracy of forecasts by augmenting existing physics models with machine learning. Meanwhile, Nvidia has been hard at work expanding the capabilities of its Earth-2 climate models.

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