The Quiet AI Revolution in Weather Forecasting

Professor Richard Turner

  • 20 November 2023, 18:00 – 19:00
  • Bristol-Myers Squibb Lecture Theatre
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Overview

Over the last 18 months a quiet AI revolution has begun in the field of numerical weather prediction. Medium-term weather prediction involves forecasting several days to a couple of weeks in the future and these forecasts are critical for making many social and economic decisions. The standard approach to this problem is to run detailed global simulations of the earth's atmosphere using a supercomputer, so-called numerical weather prediction (NWP). As little as one year ago, researchers in this field had thought it unlikely that machine learning approaches would be competitive with numerical weather prediction any time soon. However, over the last year, the same advances that underpin large language models, like ChatGPT, have been applied to weather prediction. Surprisingly, these models achieve a performance which is already competitive with standard NWP, but with a computational cost that is 1000s of times cheaper. The deep learning based forecasts have also been shown to be surprisingly robust, performing reasonably even when faced with rare or extreme events. Consequently, weather prediction centres like the World Meteorological Organisation and the European Centre for Medium-Range Weather Forecasts (ECMWF) are now racing to build machine learning teams and publicly testing AI forecasts. This talk will describe this quieter AI revolution and it will end with a discussion of the opportunities for AI and machine learning in weather and climate, and speak a little more widely about the balancing act that must be struck between regulation and adoption of AI technology.

Biography

Dr. Turner is a Professor of Machine Learning in the Department of Engineering at the University of Cambridge and a Visiting Researcher at Microsoft Research Cambridge. Dr. Turner is Course Director of the Machine Learning and Machine Intelligence MPhil programme. He was Co-Director of the UKRI Centre for Doctoral Training in the Application of Artificial Intelligence to the study of Environmental Risks (AI4ER CDT) and he spent two years at Microsoft Research as a visiting researcher.

Over the last two years his work has been presented in oral presentations at top machine learning conferences including AAAI, AIStats, ICLR, ICML and NeurIPS and he has given keynote lectures and tutorials at the Machine Learning and Signal Processing Summer School, the International Conference on Machine Learning, Optimization & Data Science, and the Machine Learning Summer School. He has been the lead supervisor for 13 PhD students (6 now graduated) and three RAs. He has received over £5M of industrial funding from Microsoft, Toyota, Google, DeepMind, Amazon, and Improbable and over £9M of funding from the EPSRC. Dr. Turner is on the Steering Committee for the Cambridge Centre for Data Driven Discovery (C2D3). He has been awarded the Cambridge Students' Union Teaching Award for Lecturing. His work has featured on BBC Radio 5 Live’s The Naked Scientist, BBC World Service’s Click and in Wired Magazine.


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