Weather forecasting is not a perfect science, but Google's new weather model, GenCast, is becoming a force to be reckoned with.
Meteorologists and other environmental scientists rely on numerical forecast models to aid in developing a weather outlook. These models, such as the American GFS model and European ECMWF model, use physics and a series of complex mathematical equations that depict how the atmosphere works. Most of the time, the models do a pretty good job at forecasting specific weather patterns. However, these models are not perfect.
To answer it, GenCast was pitted against the ECMWF’s ensemble model, the ENS, which is one of the world’s top-tier traditional forecasting systems used today. The results were recently published in Nature, a peer-reviewed multidisciplinary science journal. The two forecast models were tested using 1,320 different weather scenarios, using a wide range of weather variables and lead times. According to the research published in Nature, GenCast was found to be more accurate than the ENS in 97.
ECMWF AI Google ENS GFS Google Deepmind AIFS Microsoft Gencast European American Aurora Gencast Nature
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