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Physics, Astronomy & Cosmology / Will AI really replace supercomputers for weather-forecasting?
« on: 06/12/2024 21:43:30 »
On today's podcast, an interview with researchers from Google DeepMind reported results of an AI doing Medium-Range weather forecasting (up to 2 weeks in advance).
- They reported huge reductions in energy consumption, number of CPUs and computation time when using a Google TPU (AI chip) compared to thousands of CPUs in a conventional supercomputer.
- Suggesting that weather forecasting would no longer need supercomputers
- The Google chip started with the current state of the world's weather as input.
5 years ago, I listened to this interview with the European Medium-Range Weather Forecasting team.
- My vague recollection was that something like 60% of their Supercomputer usage was to produce a definition of the current state of the weather, and only 40% was predicting the future of the weather, out to 2 weeks
- There are many different sources of data on the current weather, and they don't always agree
- The data collection points are closer together over land than over sea or deserts
- And so it takes a huge amount of supercomputer analysis to integrate them all to define the current global weather
So while AI might will be able to reduce supercomputer usage by 40% for weather prediction, there is still significant research if forecasters are to reduce the other 60% of supercomputer usage.
https://omegataupodcast.net/326-weather-forecasting-at-the-ecmwf/
- They reported huge reductions in energy consumption, number of CPUs and computation time when using a Google TPU (AI chip) compared to thousands of CPUs in a conventional supercomputer.
- Suggesting that weather forecasting would no longer need supercomputers
- The Google chip started with the current state of the world's weather as input.
5 years ago, I listened to this interview with the European Medium-Range Weather Forecasting team.
- My vague recollection was that something like 60% of their Supercomputer usage was to produce a definition of the current state of the weather, and only 40% was predicting the future of the weather, out to 2 weeks
- There are many different sources of data on the current weather, and they don't always agree
- The data collection points are closer together over land than over sea or deserts
- And so it takes a huge amount of supercomputer analysis to integrate them all to define the current global weather
So while AI might will be able to reduce supercomputer usage by 40% for weather prediction, there is still significant research if forecasters are to reduce the other 60% of supercomputer usage.
https://omegataupodcast.net/326-weather-forecasting-at-the-ecmwf/