Dynamical Tests of a Deep-Learning Weather Prediction Model

Understand

Global deep-learning weather prediction models have recently been shown to produce forecasts that rival those from physics-based models run at operational centers.

• It is unclear whether these models have encoded atmospheric dynamics, or simply pattern matching that produces the smallest forecast error.
• Answering this question is crucial to establishing the utility of these models as tools for basic science.
• Here we subject one such model, Pangu-weather, to a set of four classical dynamical experiments that do not resemble the model training data.