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GenCast is a diffusion model, similar to the machine learning models which also power generative AI. 🎨 We trained it on 40 years of historical data from ECMWF, which included variables such as temperature, wind speed, and pressure at various altitudes - enabling it to learn global weather patterns.

Google DeepMind

1,476,212 subscribers

26,360 views • 1 year ago •via X (Twitter)

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8 Comments

Google DeepMind1 year ago

Today in @Nature, we’re presenting GenCast: our new AI weather model which gives us the probabilities of different weather conditions up to 15 days ahead with state-of-the-art accuracy. ☁️⚡ Here’s how the technology works. 🧵

Google DeepMind1 year ago

Weather affects almost everything - from our daily lives 🏠 to agriculture 🚜 to producing renewable energy 🔋 and more. Forecasting traditionally uses physics based models which can take hours on a huge supercomputer. We want to do it in minutes - and better.

Google DeepMind1 year ago

Our previous AI model was able to provide a single, best estimate of future weather. But this can't be predicted exactly. So GenCast takes a probabilistic approach to forecasting. It makes 50 or more predictions of how the weather may change, showing us how likely different scenarios are.

Google DeepMind1 year ago

GenCast is able to generate a single 15-day scenario in 8 minutes on a single TPU chip. When predicting extreme heat 🌡️, cold 🧊, and high wind speeds 💨, it consistently outperformed the current best operational forecast known as ENS.

Google DeepMind1 year ago

It can also deliver superior predictions of the tracks of tropical cyclones, up to 5 days in advance. GenCast’s capabilities could not only help officials better prepare for disasters but also in other aspects of society, such as renewable energy planning. 🔋

Google DeepMind1 year ago

AI in weather forecasting will help benefit billions of people in their everyday lives. To help enable further research and accelerate advances, we’re releasing the GenCast model code to the wider community. We’ll soon be releasing real-time and historical forecasts. Find out more. ↓

Roozbeh1 year ago

@ECMWF Any link you can share that compares its ensemble accuracy vs. physics based/traditional models?

Isabel Perez1 year ago

@ECMWF How about running simulations for unknown scenarios? With global warming the predictability needs to be better than the 40 years of past data. I would love to know more about this! :)

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