A Google AI model is improving climate forecasting

A new Google AI tool promises to improve climate prediction. NeuralGCM, developed by Google Research, uses physics-based modelling and AI to create fast and precise simulations of Earth’s atmosphere.

Traditional climate models work by fragmenting the planet into large pixelated pieces, which makes it hard to accurately predict small-scale conditions like clouds, turbulence, and convection. The combination of physics-based simulations and AI seems to resolve this issue, and in 2020, NeuralGCM predicted annual temperature and humidity levels 15-50 percent more accurately than its non-AI counterpart X-SHiELD, and much faster – NeuralGCM generated those predictions in 8 minutes compared with 20 days for X-SHiELD.

Google claims NeuralGCM can operate on a single AI chip, or TPU (Tensor Processing Unit), while some high-resolution atmospheric models require access to expensive supercomputers, and thousands of chips called CPUs (Central Processing Unit). This means that the model will be accessible on laptops and to researchers worldwide. Better efficiency could also reduce the model’s energy consumption.

The news comes weeks after Google’s own environmental report concluded that the company’s use of energy-devouring AI over the past five years has increased its emissions by nearly 50 percent.