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Google says new AI models allow for ‘nearly instantaneous’ weather forecast

Google’s researchers describe how they were able to generate accurate rainfall predictions up to six hours ahead of time at a 1km resolution from just “minutes” of calculation.

The biggest advantage Google’s approach offers over traditional forecasting techniques is speed. The company’s researchers compared their work to two existing methods: optical flow (OF) predictions, which look at the motion of phenomenon like clouds, and simulation forecasting, which creates detailed physics-based simulations of weather systems.

The problem with these older methods — particularly the physics-based simulation — is that they’re incredibly computationally intensive. Simulations made by US federal agencies for weather forecasting, for example, have to process up to 100 terabytes of data from weather stations every day and take hours to run on expensive supercomputers.

If it takes 6 hours to compute a forecast, that allows only 3-4 runs per day and resulting in forecasts based on 6+ hour old data, which limits our knowledge of what is happening right now,” wrote Google software engineer Jason Hickey in a blog post.

Google’s methods, by comparison, produce results in minutes because they don’t try to model complex weather systems, but instead make predictions about simple radar data as a proxy for rainfall.

Preuzeto sa: https://www.theverge.com/2020/1/14/21065095/google-ai-weather-forecast-predictions-rainfall-research

Više informacija na: https://ai.googleblog.com/2020/01/using-machine-learning-to-nowcast.html

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