No, existing models use more numerical methods. This is using a completely different approach.
> GraphCast utilizes what researchers call a "graph neural network" machine-learning architecture, trained on over four decades of ECMWF's historical weather data. It processes the current and six-hour-old global atmospheric states, generating a 10-day forecast in about a minute on a Google TPU v4 cloud computer. Google's machine learning method contrasts with conventional numerical weather prediction methods that rely on supercomputers to process equations based on atmospheric physics, consuming significantly more time and energy.
> GraphCast utilizes what researchers call a "graph neural network" machine-learning architecture, trained on over four decades of ECMWF's historical weather data. It processes the current and six-hour-old global atmospheric states, generating a 10-day forecast in about a minute on a Google TPU v4 cloud computer. Google's machine learning method contrasts with conventional numerical weather prediction methods that rely on supercomputers to process equations based on atmospheric physics, consuming significantly more time and energy.