From the source
Google Research describes an update to NeuralGCM, a hybrid atmospheric model that combines physics-based modeling with a neural network.
The new version is trained directly on NASA satellite-based precipitation observations (2001–2018) instead of reanalysis data, leading to improved simulations of average precipitation, precipitation extremes (especially the top 0.1% of rainfall), and the daily weather cycle.
At 280 km resolution, it outperforms a leading operational model from ECMWF on 2–15 day forecasts and shows improvements for multi-decadal climate simulations.