New research could lead to faster, trustworthy AI models for climate prediction

MIT researchers developed a training technique that generates optimized synthetic climate scenarios, letting a climate emulator be trained with far less data and only one full earth system model run instead of six to eight. The resulting emulator accurately predicted scenarios it had not seen during training, while traditional emulators failed to adapt, and it captured effects such as local pollutant controls amid rising other emissions. The work was published in the Proceedings of the National Academy of Sciences.