JuliaCon 2022 (Times are UTC)

We present SpeedyWeather.jl, a global atmospheric model currently developed as a prototype for a 16-bit climate model incorporating machine learning for accuracy and computational efficiency on different hardware. SpeedyWeather.jl is designed for type flexibility with low precision, and automatic differentiation to replace parts of the model with neural networks for a more accurate representation of climate processes and computational efficiency.